Key benefits ADF modeling suite
One-stop modeling shop
Excellent software suite for tackling the most challenging problems in materials science and chemistry. Easy set up and analysis with GUI.
Fast computational toolbox
Working with hardware vendors, we optimize our codes for desktop computers and parallel supercomputers. Latest algorithms.
Heavy elements, spectroscopy, organic electronics
High-quality all-electron Slater basis sets for all elements. Accurate relativity. Many spectroscopic properties, from NMR to X-ray.
Unique organic electronics tools: charge transport, phosphorescence.
Understand chemical bonding
Unique insight in chemical bonds with many chemical analysis tools. Balanced charge decomposition schemes and density analysis tools.
Hassle-free installation, free trial
With parallel binaries for all popular platforms, the entire ADF suite installs out of the box. Try out our powerful modeling tools for free: http://www.scm.com/trial
Discuss your science with experts
With decades of experience, our expert support team (PhDs in chemistry & physics) will help you with any queries that may arise.
The ADF Modeling Suite is a fully integrated software package for computational chemistry developed by Software for Chemistry & Materials. It contains modules for molecular and periodic DFT (ADF and BAND), semi-empirical methods (DFTB and MOPAC), reactive molecular dynamics (ReaxFF), and fluid thermodynamics (COSMO-RS). The suite has an excellent graphical user interface that makes setup and analysis easy across different calculation types on Windows, Mac, and Linux. It is used widely in academia and industry for research in areas like inorganic chemistry, materials science, pharma, and nanoscience.
Introductory slides for workshop at George Washington University: ADF for molecular properties, BAND for periodic DFT, DFTB for large electronic structure calculations and ReaxFF for molecular dynamics. Get started with the excellent graphical interface.
Overview of unique capabilities of the ADF modeling suite to model properties of organic electronics (charge transport, phosphorescence, light absorbance). Highlighted with examples from the recent literature.
Quantum Computation for Predicting Electron and Phonon Properties of SolidsKAMAL CHOUDHARY
This document outlines a workflow for using quantum computing to simulate electron and phonon properties of solids. It discusses the motivation for using quantum bits to simulate quantum systems more easily. It provides background on band theory of solids, quantum algorithms like VQE and circuit models. The workflow is then applied to calculate properties of aluminum metal and over 1000 other materials using classical and quantum solvers. Future opportunities and challenges are also discussed.
This document discusses several projects related to plasma physics and nuclear physics that the author has worked on. It includes projects studying nuclear reactions in metals using deuterium absorption, characterizing electric arcs using electrical probes, using inductively coupled plasma for optical manufacturing, producing nanoparticles via laser ablation, and using neutron and gamma interrogation for security screening of luggage and parcels. Diagrams and images from various experiments and equipment are provided.
Hpc, grid and cloud computing - the past, present, and future challengeJason Shih
This document discusses trends in high performance computing (HPC), grid computing, and cloud computing. It provides an overview of HPC cluster performance and interconnects. Grid computing enabled large-scale scientific collaboration through infrastructures like EGEE. The LHC requires petascale computing capabilities. Cloud computing hype is discussed alongside observations of performance and virtualization challenges. The future of computing may involve more sophisticated tools and dynamic, small computing elements.
This document summarizes Tim Bell's presentation on big data science and computing at CERN. It discusses:
1) The large volumes of data generated by the LHC experiments, including 40 million pictures per second and over 800 petabytes of stored data worldwide.
2) The worldwide computing grid used to store, process and analyze LHC data across over 170 computing centers in 42 countries.
3) How CERN has transitioned its computing infrastructure from mainframes to Linux and open source cloud technologies like OpenStack to manage its increasing data needs.
This document presents a quantum computer architecture tailored for an electron-spin qubit implementation on liquid helium (eSHe) that has highly mobile qubits. The architecture takes advantage of the fast qubit transportation speeds relative to operation times in eSHe. It uses shift registers and buses to transport many qubits in parallel to execution units to enable high parallelism. Error correction procedures are also analyzed and show idle qubits only need refreshing about once every 100 operation cycles. Compiler optimizations can reduce hardware requirements by 25% with no performance loss.
The ADF Modeling Suite is a fully integrated software package for computational chemistry developed by Software for Chemistry & Materials. It contains modules for molecular and periodic DFT (ADF and BAND), semi-empirical methods (DFTB and MOPAC), reactive molecular dynamics (ReaxFF), and fluid thermodynamics (COSMO-RS). The suite has an excellent graphical user interface that makes setup and analysis easy across different calculation types on Windows, Mac, and Linux. It is used widely in academia and industry for research in areas like inorganic chemistry, materials science, pharma, and nanoscience.
Introductory slides for workshop at George Washington University: ADF for molecular properties, BAND for periodic DFT, DFTB for large electronic structure calculations and ReaxFF for molecular dynamics. Get started with the excellent graphical interface.
Overview of unique capabilities of the ADF modeling suite to model properties of organic electronics (charge transport, phosphorescence, light absorbance). Highlighted with examples from the recent literature.
Quantum Computation for Predicting Electron and Phonon Properties of SolidsKAMAL CHOUDHARY
This document outlines a workflow for using quantum computing to simulate electron and phonon properties of solids. It discusses the motivation for using quantum bits to simulate quantum systems more easily. It provides background on band theory of solids, quantum algorithms like VQE and circuit models. The workflow is then applied to calculate properties of aluminum metal and over 1000 other materials using classical and quantum solvers. Future opportunities and challenges are also discussed.
This document discusses several projects related to plasma physics and nuclear physics that the author has worked on. It includes projects studying nuclear reactions in metals using deuterium absorption, characterizing electric arcs using electrical probes, using inductively coupled plasma for optical manufacturing, producing nanoparticles via laser ablation, and using neutron and gamma interrogation for security screening of luggage and parcels. Diagrams and images from various experiments and equipment are provided.
Hpc, grid and cloud computing - the past, present, and future challengeJason Shih
This document discusses trends in high performance computing (HPC), grid computing, and cloud computing. It provides an overview of HPC cluster performance and interconnects. Grid computing enabled large-scale scientific collaboration through infrastructures like EGEE. The LHC requires petascale computing capabilities. Cloud computing hype is discussed alongside observations of performance and virtualization challenges. The future of computing may involve more sophisticated tools and dynamic, small computing elements.
This document summarizes Tim Bell's presentation on big data science and computing at CERN. It discusses:
1) The large volumes of data generated by the LHC experiments, including 40 million pictures per second and over 800 petabytes of stored data worldwide.
2) The worldwide computing grid used to store, process and analyze LHC data across over 170 computing centers in 42 countries.
3) How CERN has transitioned its computing infrastructure from mainframes to Linux and open source cloud technologies like OpenStack to manage its increasing data needs.
This document presents a quantum computer architecture tailored for an electron-spin qubit implementation on liquid helium (eSHe) that has highly mobile qubits. The architecture takes advantage of the fast qubit transportation speeds relative to operation times in eSHe. It uses shift registers and buses to transport many qubits in parallel to execution units to enable high parallelism. Error correction procedures are also analyzed and show idle qubits only need refreshing about once every 100 operation cycles. Compiler optimizations can reduce hardware requirements by 25% with no performance loss.
Materials Design in the Age of Deep Learning and Quantum ComputationKAMAL CHOUDHARY
The document discusses recent developments in materials design using deep learning (DL) and quantum computation. It introduces several DL and quantum computation models developed at NIST including:
- ALIGNN, a graph neural network model that predicts materials properties from crystal structure.
- AtomVision, a DL framework for analyzing scanning probe microscopy and electron microscopy images of materials.
- AtomQC, which uses variational quantum algorithms like VQE to perform quantum simulations of materials on quantum computers.
The models have been applied to datasets containing thousands of materials to predict properties and analyze experimental images. Future work aims to integrate DL and quantum computation for accelerated materials discovery and design.
DOE Efficiency Enhancing Solar Downconverting Phosphor Layerjeep82cj
This document summarizes a project to develop efficiency-enhancing down-shifting layers for photovoltaic modules. The project aims to develop low-cost down-shifting layers that can down-convert high-energy solar photons to lower-energy photons to boost photovoltaic efficiency. Modeling shows these layers could provide over 10% relative efficiency gains. The project has fabricated down-shifting materials with quantum efficiencies over 90% and demonstrated quantum splitting. Prototype down-shifting films have been fabricated and show promising optical properties without reducing solar cell efficiency. Future work will optimize down-shifting film and material properties and demonstrate efficiency gains on solar cells.
Core Objective 1: Highlights from the Central Data ResourceAnubhav Jain
The Central Data Resource develops and disseminates solar-related data, tools, and software. It hosts a central data hub that securely stores both private and public data from DuraMat projects. It also develops open-source software libraries that apply data analytics to solve module reliability challenges. The data hub currently has over 60 projects, 128 datasets including 70 public datasets, and over 2000 files and resources accessible to its 137 users.
Constraints on the gluon PDF from top quark differential distributions at NNLOjuanrojochacon
- The document discusses constraints on the gluon PDF from top quark production at hadron colliders.
- It describes using the inclusive top quark pair production cross section to reduce uncertainties in the gluon PDF, especially in the large-x region between 0.1 and 0.5.
- Cross section ratios between different beam energies, such as 8 TeV/7 TeV, are highlighted as powerful precision tests that can discriminate between PDFs and probe BSM physics.
1) Software parallelization is required to handle the increasing scale and complexity of high-energy physics (HEP) experiments, which produce vast amounts of data from particle collisions.
2) The authors developed a programming model called Communication Capability (CoCa) that allows parallelization at different levels of granularity and reduces software complexity.
3) CoCa is based on the database transaction paradigm and allows the results of components executing in parallel to be combined while ensuring consistency, as required for HEP event reconstruction.
The document discusses how the TeraGrid initiative provides US researchers with access to large scale high performance computing resources for physics research. It describes the diverse computing resources available through TeraGrid including supercomputers, clusters, and visualization resources. It provides examples of how physics domains like lattice QCD, astrophysics, and nanoscale electronic structure are using TeraGrid resources to enable large simulations and address research challenges. Training and support resources for users are also summarized.
Computational Discovery of Two-Dimensional Materials, Evaluation of Force-Fie...KAMAL CHOUDHARY
JARVIS (Joint Automated Repository for Various Integrated Simulations) is a repository designed to automate materials discovery using classical force-field, density functional theory, machine learning calculations and experiments.
The Force-field section of JARVIS (JARVIS-FF) consists of thousands of automated LAMMPS based force-field calculations on DFT geometries. Some of the properties included in JARVIS-FF are energetics, elastic constants, surface energies, defect formations energies and phonon frequencies of materials.
The Density functional theory section of JARVIS (JARVIS-DFT) consists of thousands of VASP based calculations for 3D-bulk, single layer (2D), nanowire (1D) and molecular (0D) systems. Most of the calculations are carried out with optB88vDW functional. JARVIS-DFT includes materials data such as: energetics, diffraction pattern, radial distribution function, band-structure, density of states, carrier effective mass, temperature and carrier concentration dependent thermoelectric properties, elastic constants and gamma-point phonons.
The Machine-learning section of JARVIS (JARVIS-ML) consists of machine learning prediction tools, trained on JARVIS-DFT data. Some of the ML-predictions focus on energetics, heat of formation, GGA/METAGGA bandgaps, bulk and shear modulus. The ML webpage is visible to NIST employees only right now, but will be available publicly soon.
The document discusses JARVIS-ML, an AI system for fast and accurate screening of materials properties. It uses machine learning models trained on a large dataset of materials properties calculated using density functional theory. Some key points:
- JARVIS-ML uses gradient boosting decision trees to predict properties like formation energies, bandgaps, and elastic moduli, achieving good accuracy compared to DFT calculations.
- Feature selection is important, and JARVIS-ML uses over 1,500 descriptors of atomic structure. Chemical features are most important for predictions.
- The models can screen thousands of materials in seconds, much faster than DFT. This enables large-scale materials discovery tasks like genetic algorithm searches.
The document discusses grid computing at CERN for the Large Hadron Collider experiment. CERN operates a worldwide computing grid with tiered levels to handle the massive computing and storage needs. Tier 0 is at CERN for data acquisition and distribution. Tier 1 centers have large storage and do data analysis. Tier 2 centers participate in simulation and analysis. The LHC generates 40 million collision events per second that are filtered and recorded, resulting in 15 petabytes of data per year. The computing grid is necessary to process and store this huge volume of data across the distributed centers.
The impact of new collider data into the NNPDF global analysisJuan Rojo
The document summarizes Juan Rojo's presentation on the impact of new collider data in the NNPDF global analysis. It discusses updates and improvements to the NNPDF methodology, including adopting the public code APFEL, adding new LHC datasets like LHCb and top quark pair differential distributions, and analyzing the impact on parton distributions from including precise Tevatron and LHC Z boson data. Preliminary results from NNPDF3.1 indicate good stability compared to the previous NNPDF3.0 analysis, with reduced uncertainties and improved flavor separation from new experimental inputs.
The document summarizes electrical characterization work on graphene and molybdenum disulfide samples. Key points:
- Graphene and MoS2 devices were fabricated and their electrical properties tested under varying conditions like annealing.
- Annealing graphene in argon caused a negative shift in the Dirac point that reversed over time. Samples in FeCl3 were heavily p-doped while in HCl they were mildly n-doped.
- Longer MoS2 growth times led to higher mobility samples. Transferred and lower purity sulfur samples showed degraded properties.
- Python scripts were developed to analyze large amounts of electrical data from the Keithley faster than manual methods. Mobility, Dirac
This document summarizes a presentation about the Worldwide LHC Computing Grid (WLCG) and how it provides computing resources for experiments at the Large Hadron Collider (LHC). The WLCG links computing grids from different regions to coordinate resources across over 300 computer centers. It provides over 340,000 CPU cores and moves about 10GB/s of data for each LHC experiment. The WLCG archives about 15 petabytes of data per year from the LHC experiments. The presentation discusses how the WLCG uses open source software like the Globus Toolkit, Scientific Linux, ROOT, and RooFit to provide its distributed computing services.
Smart Metrics for High Performance Material Designaimsnist
This document discusses smart metrics for high-performance material design using density functional theory (DFT), classical force fields (FF), and machine learning (ML). It provides an overview of the JARVIS database and tools containing over 35,000 materials and classical properties calculated using DFT, FF, and ML methods. Metrics discussed include formation energy, exfoliation energy, elastic constants, surface energy, vacancy energy, grain boundary energy, bandgaps, and other electronic and optical properties important for applications like solar cells. ML models are developed to predict these properties with mean absolute errors within chemical accuracy compared to DFT benchmarks.
Coating Thickness Test with Portable XRFOlympus IMS
1. Coatings - overview
2. Short Introduction to XRF
3. Range of Applications for the Vanta Coating App
4. 3 Steps to Create a Coating Template
5. Some Examples
6. Summary
The Materials Project and computational materials discoveryAnubhav Jain
1. The Materials Project aims to accelerate materials discovery through high-throughput computational screening of materials properties using density functional theory calculations.
2. Over 60,000 compounds have been computed so far, with properties including total energies, optimized structures, band structures, and elastic tensors.
3. The goal is to compute properties for over 90,000 materials to help researchers discover new materials for applications like batteries, thermoelectrics, and other energy technologies.
IRJET- Application of Artificial Neural Networking Technique for the Lifecycl...IRJET Journal
This document presents a study that uses an artificial neural network technique to compare the lifecycle assessment of regular concrete to recycled aggregate concrete. Experimental testing was conducted on concrete mixes with different percentages of recycled coarse aggregate replacement. An artificial neural network was trained on literature data to predict the compressive strength of mixes. An "every possible combination" matrix was generated to find a normal concrete mix with equivalent predicted strength to the experimental recycled aggregate mixes. Lifecycle parameters like embodied energy, emissions, waste etc. were then compared between the equivalent mixes to analyze the environmental impacts. The results showed better performance for recycled aggregate concrete, suggesting its increased usage could support more sustainable construction practices. The study demonstrated a viable method for composition analysis but noted further validation was
European imperialism in the late 1800s was driven by two main factors: the need for new resources as populations in Europe grew and existing resources diminished, and the prospect of enormous wealth from exploiting resource-rich lands. The end of the Age of Imperialism is widely considered to be the start of World War I in 1914, as imperialist nations could no longer spare resources and manpower on further colonial expansion during the war.
(APP402) Serving Billions of Web Requests Each Day with Elastic Beanstalk | A...Amazon Web Services
AWS Elastic Beanstalk provides a number of simple and flexible interfaces for developing and deploying your applications. Follow Thinknear's rapid growth from inception to acquisition, scaling from a few dozen requests per hour to billions of requests served each day with AWS Elastic Beanstalk. Thinknear engineers demonstrate how they extended the AWS Elastic Beanstalk platform to scale to billions of requests while meeting response times below 100 ms, discuss tradeoffs they made in the process, and what did and did not work for their mobile ad bidding business.
Materials Design in the Age of Deep Learning and Quantum ComputationKAMAL CHOUDHARY
The document discusses recent developments in materials design using deep learning (DL) and quantum computation. It introduces several DL and quantum computation models developed at NIST including:
- ALIGNN, a graph neural network model that predicts materials properties from crystal structure.
- AtomVision, a DL framework for analyzing scanning probe microscopy and electron microscopy images of materials.
- AtomQC, which uses variational quantum algorithms like VQE to perform quantum simulations of materials on quantum computers.
The models have been applied to datasets containing thousands of materials to predict properties and analyze experimental images. Future work aims to integrate DL and quantum computation for accelerated materials discovery and design.
DOE Efficiency Enhancing Solar Downconverting Phosphor Layerjeep82cj
This document summarizes a project to develop efficiency-enhancing down-shifting layers for photovoltaic modules. The project aims to develop low-cost down-shifting layers that can down-convert high-energy solar photons to lower-energy photons to boost photovoltaic efficiency. Modeling shows these layers could provide over 10% relative efficiency gains. The project has fabricated down-shifting materials with quantum efficiencies over 90% and demonstrated quantum splitting. Prototype down-shifting films have been fabricated and show promising optical properties without reducing solar cell efficiency. Future work will optimize down-shifting film and material properties and demonstrate efficiency gains on solar cells.
Core Objective 1: Highlights from the Central Data ResourceAnubhav Jain
The Central Data Resource develops and disseminates solar-related data, tools, and software. It hosts a central data hub that securely stores both private and public data from DuraMat projects. It also develops open-source software libraries that apply data analytics to solve module reliability challenges. The data hub currently has over 60 projects, 128 datasets including 70 public datasets, and over 2000 files and resources accessible to its 137 users.
Constraints on the gluon PDF from top quark differential distributions at NNLOjuanrojochacon
- The document discusses constraints on the gluon PDF from top quark production at hadron colliders.
- It describes using the inclusive top quark pair production cross section to reduce uncertainties in the gluon PDF, especially in the large-x region between 0.1 and 0.5.
- Cross section ratios between different beam energies, such as 8 TeV/7 TeV, are highlighted as powerful precision tests that can discriminate between PDFs and probe BSM physics.
1) Software parallelization is required to handle the increasing scale and complexity of high-energy physics (HEP) experiments, which produce vast amounts of data from particle collisions.
2) The authors developed a programming model called Communication Capability (CoCa) that allows parallelization at different levels of granularity and reduces software complexity.
3) CoCa is based on the database transaction paradigm and allows the results of components executing in parallel to be combined while ensuring consistency, as required for HEP event reconstruction.
The document discusses how the TeraGrid initiative provides US researchers with access to large scale high performance computing resources for physics research. It describes the diverse computing resources available through TeraGrid including supercomputers, clusters, and visualization resources. It provides examples of how physics domains like lattice QCD, astrophysics, and nanoscale electronic structure are using TeraGrid resources to enable large simulations and address research challenges. Training and support resources for users are also summarized.
Computational Discovery of Two-Dimensional Materials, Evaluation of Force-Fie...KAMAL CHOUDHARY
JARVIS (Joint Automated Repository for Various Integrated Simulations) is a repository designed to automate materials discovery using classical force-field, density functional theory, machine learning calculations and experiments.
The Force-field section of JARVIS (JARVIS-FF) consists of thousands of automated LAMMPS based force-field calculations on DFT geometries. Some of the properties included in JARVIS-FF are energetics, elastic constants, surface energies, defect formations energies and phonon frequencies of materials.
The Density functional theory section of JARVIS (JARVIS-DFT) consists of thousands of VASP based calculations for 3D-bulk, single layer (2D), nanowire (1D) and molecular (0D) systems. Most of the calculations are carried out with optB88vDW functional. JARVIS-DFT includes materials data such as: energetics, diffraction pattern, radial distribution function, band-structure, density of states, carrier effective mass, temperature and carrier concentration dependent thermoelectric properties, elastic constants and gamma-point phonons.
The Machine-learning section of JARVIS (JARVIS-ML) consists of machine learning prediction tools, trained on JARVIS-DFT data. Some of the ML-predictions focus on energetics, heat of formation, GGA/METAGGA bandgaps, bulk and shear modulus. The ML webpage is visible to NIST employees only right now, but will be available publicly soon.
The document discusses JARVIS-ML, an AI system for fast and accurate screening of materials properties. It uses machine learning models trained on a large dataset of materials properties calculated using density functional theory. Some key points:
- JARVIS-ML uses gradient boosting decision trees to predict properties like formation energies, bandgaps, and elastic moduli, achieving good accuracy compared to DFT calculations.
- Feature selection is important, and JARVIS-ML uses over 1,500 descriptors of atomic structure. Chemical features are most important for predictions.
- The models can screen thousands of materials in seconds, much faster than DFT. This enables large-scale materials discovery tasks like genetic algorithm searches.
The document discusses grid computing at CERN for the Large Hadron Collider experiment. CERN operates a worldwide computing grid with tiered levels to handle the massive computing and storage needs. Tier 0 is at CERN for data acquisition and distribution. Tier 1 centers have large storage and do data analysis. Tier 2 centers participate in simulation and analysis. The LHC generates 40 million collision events per second that are filtered and recorded, resulting in 15 petabytes of data per year. The computing grid is necessary to process and store this huge volume of data across the distributed centers.
The impact of new collider data into the NNPDF global analysisJuan Rojo
The document summarizes Juan Rojo's presentation on the impact of new collider data in the NNPDF global analysis. It discusses updates and improvements to the NNPDF methodology, including adopting the public code APFEL, adding new LHC datasets like LHCb and top quark pair differential distributions, and analyzing the impact on parton distributions from including precise Tevatron and LHC Z boson data. Preliminary results from NNPDF3.1 indicate good stability compared to the previous NNPDF3.0 analysis, with reduced uncertainties and improved flavor separation from new experimental inputs.
The document summarizes electrical characterization work on graphene and molybdenum disulfide samples. Key points:
- Graphene and MoS2 devices were fabricated and their electrical properties tested under varying conditions like annealing.
- Annealing graphene in argon caused a negative shift in the Dirac point that reversed over time. Samples in FeCl3 were heavily p-doped while in HCl they were mildly n-doped.
- Longer MoS2 growth times led to higher mobility samples. Transferred and lower purity sulfur samples showed degraded properties.
- Python scripts were developed to analyze large amounts of electrical data from the Keithley faster than manual methods. Mobility, Dirac
This document summarizes a presentation about the Worldwide LHC Computing Grid (WLCG) and how it provides computing resources for experiments at the Large Hadron Collider (LHC). The WLCG links computing grids from different regions to coordinate resources across over 300 computer centers. It provides over 340,000 CPU cores and moves about 10GB/s of data for each LHC experiment. The WLCG archives about 15 petabytes of data per year from the LHC experiments. The presentation discusses how the WLCG uses open source software like the Globus Toolkit, Scientific Linux, ROOT, and RooFit to provide its distributed computing services.
Smart Metrics for High Performance Material Designaimsnist
This document discusses smart metrics for high-performance material design using density functional theory (DFT), classical force fields (FF), and machine learning (ML). It provides an overview of the JARVIS database and tools containing over 35,000 materials and classical properties calculated using DFT, FF, and ML methods. Metrics discussed include formation energy, exfoliation energy, elastic constants, surface energy, vacancy energy, grain boundary energy, bandgaps, and other electronic and optical properties important for applications like solar cells. ML models are developed to predict these properties with mean absolute errors within chemical accuracy compared to DFT benchmarks.
Coating Thickness Test with Portable XRFOlympus IMS
1. Coatings - overview
2. Short Introduction to XRF
3. Range of Applications for the Vanta Coating App
4. 3 Steps to Create a Coating Template
5. Some Examples
6. Summary
The Materials Project and computational materials discoveryAnubhav Jain
1. The Materials Project aims to accelerate materials discovery through high-throughput computational screening of materials properties using density functional theory calculations.
2. Over 60,000 compounds have been computed so far, with properties including total energies, optimized structures, band structures, and elastic tensors.
3. The goal is to compute properties for over 90,000 materials to help researchers discover new materials for applications like batteries, thermoelectrics, and other energy technologies.
IRJET- Application of Artificial Neural Networking Technique for the Lifecycl...IRJET Journal
This document presents a study that uses an artificial neural network technique to compare the lifecycle assessment of regular concrete to recycled aggregate concrete. Experimental testing was conducted on concrete mixes with different percentages of recycled coarse aggregate replacement. An artificial neural network was trained on literature data to predict the compressive strength of mixes. An "every possible combination" matrix was generated to find a normal concrete mix with equivalent predicted strength to the experimental recycled aggregate mixes. Lifecycle parameters like embodied energy, emissions, waste etc. were then compared between the equivalent mixes to analyze the environmental impacts. The results showed better performance for recycled aggregate concrete, suggesting its increased usage could support more sustainable construction practices. The study demonstrated a viable method for composition analysis but noted further validation was
European imperialism in the late 1800s was driven by two main factors: the need for new resources as populations in Europe grew and existing resources diminished, and the prospect of enormous wealth from exploiting resource-rich lands. The end of the Age of Imperialism is widely considered to be the start of World War I in 1914, as imperialist nations could no longer spare resources and manpower on further colonial expansion during the war.
(APP402) Serving Billions of Web Requests Each Day with Elastic Beanstalk | A...Amazon Web Services
AWS Elastic Beanstalk provides a number of simple and flexible interfaces for developing and deploying your applications. Follow Thinknear's rapid growth from inception to acquisition, scaling from a few dozen requests per hour to billions of requests served each day with AWS Elastic Beanstalk. Thinknear engineers demonstrate how they extended the AWS Elastic Beanstalk platform to scale to billions of requests while meeting response times below 100 ms, discuss tradeoffs they made in the process, and what did and did not work for their mobile ad bidding business.
Research on shakespeare, england in his timeNg Sze Hian
William Shakespeare was an English playwright and poet born in 1564 in Stratford-upon-Avon. He wrote over 30 plays and 150 sonnets that are still performed widely today. England during Shakespeare's time was ruled by Queen Elizabeth I and was experiencing a cultural renaissance with developments in art, literature, and theater. Shakespeare drew inspiration from this renaissance and other writers to create complex, psychologically realistic plays that were well-received and helped establish him as one of the greatest playwrights of all time.
Progressives became concerned about long work hours and poor wages damaging the health of factory workers, especially women and children. Reformers like Florence Kelley lobbied for protective legislation. Jacob Riis documented poor living conditions in tenement housing. Muckraking journalists like Ida Tarbell exposed corruption and fraud in big business, such as Standard Oil. Theodore Roosevelt, as president, took steps to regulate industry and break up trusts in the interest of public welfare, while also establishing national parks and promoting conservation. Upton Sinclair's The Jungle drew attention to unsanitary conditions in the meatpacking industry and spurred passage of new food safety laws.
This presentation discusses socio-economic problems in Pakistan. It divides the problems into social problems like poverty, illiteracy, corruption, and unemployment, and economic problems like power crises, the war on terrorism, lack of tourism, and loss of business. Poverty is a major issue, with a large population living below the poverty line in miserable conditions. Corruption and unemployment are also significant social problems impacting the economy. On the economic side, power crises, terrorism, lack of tourism, and businesses leaving Pakistan have negatively impacted the country's economy. The conclusion calls for both government and citizens to play a role in creating positive change.
El virreinato operó bajo los principios del mercantilismo, exclusivismo e intervencionismo impuestos por España. La economía se centró en la minería de plata y mercurio usando trabajo forzado de indígenas, y en la agricultura y ganadería en haciendas. También hubo talleres textiles que usaron la mita. El comercio fue regulado por la Casa de Contratación y el Tribunal del Consulado, e impuestos gravaban las importaciones, exportaciones, transacciones y producción.
Soil erosion is a major global problem, with 75 billion tons of fertile soil lost annually worldwide. Wind erosion is a significant issue, removing 40% of Pakistan's soil over time. Several factors influence wind erosion, including soil texture, structure, protection by plants, rainfall, and wind force. Methods to control wind erosion include planting shelterbelts, increasing soil organic matter, strip cropping perpendicular to winds, leaving stubble barriers, and reducing tillage. Proper land management is key to reducing the effects of wind on soils.
Songs can be a useful tool in teaching young language learners. They provide variety, help improve listening skills and pronunciation, and aid in vocabulary acquisition. Songs also make learning enjoyable and help create a relaxed classroom environment. However, teachers must select songs carefully to match the target language structures and avoid songs with complex or unfamiliar language. While fun, songs alone are not enough for communication and must be supplemented with other activities.
ENVIRONMENTAL IMPACT OF EMISSION OF POWER PLANTSMr. Mrunal Raut
This document discusses the environmental impacts of emissions from power plants in India, Japan, and the US. It notes that coal is the primary fuel source for power generation in India and the US. The main issues are air pollution from fly ash and emissions of SO2, NOx, and CO2, as well as water pollution, noise pollution, and land degradation from disposal of fly ash. Thermal power plants account for the majority of particulate matter and SO2 emissions in India. The document recommends the adoption of clean coal technologies like flue gas desulfurization systems and electrostatic precipitators to reduce environmental impacts while meeting increasing energy demands.
This document discusses microorganisms and contains several activities:
1. An exercise with true/false and multiple choice questions about microorganisms, including that they are living things, are tiny, and can be seen with a microscope.
2. A true/false activity about microorganisms, including that some can be seen with the naked eye and undergo life processes like humans.
3. A fill-in-the-blank activity about microorganisms undergoing life processes and their different shapes, sizes, and viewing with microscopes.
4. An activity to classify types of microorganisms like bacteria, fungi, protozoa, and algae.
5. A fill-
Religion creates social order by unifying people around shared sacred symbols and collective representations of morality. Without a shared system of religious beliefs and practices, social order and solidarity would break down.
El amor ha sido un tema de debate a través de los siglos. Filósofos como Nietzsche y Platón han propuesto que el amor no es ni bueno ni malo, sino más allá de esas categorías. San Agustín argumenta que el amor puede ser bueno o malo dependiendo de si está ordenado hacia Dios o no. El ser humano está condenado a amar para poder sentirse realizado y satisfacer sus necesidades, y el amor es la fuente de toda acción humana y lo que permite la supervivencia.
This document provides information about a study on employee welfare facilities at HLL Lifecare Limited in Kanagala, India. It includes the company profile, objectives of the study which are to study existing welfare facilities, employee opinions, satisfaction levels, and suggestions for improvement. The methodology involved questionnaires and interviews. Key findings were that 90% of employees were aware of welfare facilities but 10% were not, and 70% felt satisfied with current facilities. Suggestions included improving canteen food quality and providing transportation for contract workers. The conclusion is that welfare facilities play an important role in employee motivation and productivity.
A Project Feasibility Study for the Establishment of E&J FarmsJandel Gimeno
This is a feasibility study made and conducted by our group entitled "A Project Feasibility Study for the Establishment of E&J FARM in ALFONSO, CAVITE". The group was composed of Mr. Alvin Hermoso, Efren Paul Vicedo, Jandel Gimeno, Mary Grace Orpia, Diana Ruado, Kristine Mendoza and Analyn Odal. The said Project Study was submitted to the Faculty of Business Administration & Accountancy Department of the Rogationist College.
(It was so CHALLENGING FOR US, yet so Successful! : )
Kevyn introduced a concept of planning that was the base for understanding and visualising The Planning Aspects; important for the budding planners.
The presentation initiates the same understanding and invokes a means for better understanding of 'Planning'.
El documento presenta un problema de proporcionalidad sobre la cantidad de fotos que Max puede escanear y retocar en 9 horas. Se proporcionan tablas de datos sobre fotos escaneadas vs horas y se pide expresar relaciones como proporciones. También contiene ejemplos resueltos de problemas de proporcionalidad directa e inversa y solicita resolver ejercicios de un taller.
Diana Marisol García Gómez tiene 15 años y vive en Guadalajara, Jalisco, México. Actualmente asiste a la preparatoria y participa en un movimiento católico para adolescentes llamado "Pandillas de Cristo". Le gusta bailar música banda y reggae, y pasar tiempo con sus amigos y familia. Sus aspiraciones futuras incluyen estudiar arquitectura, ciencias de la comunicación o modelaje.
This document discusses key performance indicators (KPIs) for a key account manager position. It provides information on developing KPIs, including defining objectives and key result areas, identifying tasks, and determining how to measure results. Mistakes to avoid in creating KPIs, such as having too many metrics or metrics that do not change over time, are also outlined. The document recommends that KPIs be clearly linked to strategy and empower employees. It also describes different types of KPIs and provides a link to additional KPI materials and resources.
For my final, capstone marketing class, marketing strategies, my team and I were confronted with the challenge of developing a marketing plan for a specific industry, and a company within that industry. We chose the smartphone industry, and within that, the company Samsung. After thorough research, we presented a marketing plan to evaluate their marketing mix moving forward.
This document advertises that 50 fully-editable PowerPoint templates are available for free by visiting a website and liking them on Facebook. It includes examples of common business diagrams like the Boston Consulting Group matrix, SWOT analysis, decision matrix, fishbone diagram, and component list.
Implementing a neural network potential for exascale molecular dynamicsPFHub PFHub
The document discusses implementing a neural network potential for molecular dynamics simulations using the CabanaMD framework. Key points include:
- A neural network potential was implemented in CabanaMD using Kokkos/Cabana constructs, offering significant on-node scalability and the first GPU implementation of a neural network potential, showing up to 10x speedup over CPU.
- Data layout changes provided an additional 10% performance gain for the GPU implementation.
- For a nickel system, the GPU implementation achieved over 1 million atomsteps per second, vastly outperforming the water system.
- Future work includes exploring hierarchical parallelism and MPI scaling as well as applying machine learning techniques to other computational materials problems like phase
Photophysical properties of light harvesting molecules: three different approaches (of increasing complexity and accuracy) to foresee the harvesting behaviour are reviewed with a highly didactic flow. Design principles are highlighted.
A supplementary set of slides is available among my uploads.
This document is a self-made research I did for a photochemistry course. I don't own part of the shown material and references for many public images are reported at the end.
This thesis extends the electromagnetic field calculation capabilities of the open-source CFD software OpenFOAM. It develops new solvers within OpenFOAM to solve magnetostatic problems for materials like copper, steel, and permanent magnets. Two formulations (A-V and A-J) are derived from Maxwell's equations and implemented as OpenFOAM solvers through custom C++ code. Force calculation methods are also implemented to calculate Lorenz force and Maxwell stress. Simple test cases are modeled and solved to validate the new solvers. Results are compared to COMSOL Multiphysics and good agreement is found. The developed solvers could be applied to the design of electromagnetic devices like electric machines.
This dissertation develops first-principles thermodynamic models for the hexagonal close-packed ε-Fe-N system. The work is divided into two parts. The first part develops a generalized quasiharmonic phonon model to describe the vibrational contributions to the thermodynamics. This model is applied to ε-Fe3N and accurately predicts its thermal expansion and volume-pressure relationship. The second part uses thermodynamic statistical sampling via Monte Carlo simulations and a cluster expansion to describe the configurational degrees of freedom of nitrogen occupation in the system. This allows modeling of ordering phenomena and phase transitions. The model predicts an ε → ζ phase transition in agreement with experiments.
Nanometric Modelization of Gas Structure, Multidimensional using COMSOL Soft...IJECEIAES
In structures with GaAs, which are the structures most used, because of their physical and electronic proprieties, nevertheless seems a compromise between the increase of doping and reduced mobility. The use of quantum hetero structures can overcome this limitation by creating a 2D carrier gas. Using the COMSOL software this work present three models: the first model computes the electronic states for the heterojunction AlGaAs/GaAs in 1D dimension, the second model computes the electronic states for the heterojunction AlGaAs/GaAs but in 2D dimension (nanowire) and the third model we permitted the study of this hetero junction (steep) wich inevitably involves the resolution of the system of equations Schrödinger-Poisson due to quantum effects that occur at the interface. The validity of this model can be effectuated with a comparison of our results with the result of different models developed in the literature of the related work, from this point of view the validity of our model is confirmed.
The document discusses several topics related to semiconductor manufacturing processes and design for manufacturability (DFM). It summarizes resolution enhancement techniques used in lithography like RET and OPC. It also discusses DFM techniques like process characterization of IP libraries using yield models, addressing systematic and random yield loss mechanisms, and the need for proactive DFM using accurate process models early in the design flow. Finally, it briefly mentions the use of automated test equipment for testing chips after manufacturing.
Product failure analysis using Explicit dynamicnaga ram
This document discusses using ANSYS Autodyn, an explicit dynamics solver, to simulate product failures through drop tests. The case study analyzes dropping electronic devices from 50mm onto a concrete floor to test for cracks or fractures. Autodyn uses the explicit solver to iteratively simulate the dynamic impact in small time increments using hexagonal meshing for accurate results. Finite element analysis is introduced as a way to approximate complex problems by subdividing a domain into simpler elements and recombining them. Autodyn provides finite element and finite volume solvers as well as material models to simulate the nonlinear dynamics of solids and fluids interacting over very short time scales of 0.1 seconds for this case study.
This thesis examines calculations of binding free energies between cucurbit[7]uril and small ligands using end-state molecular modeling methods. The author conducted molecular dynamics simulations using AMBER with implicit solvent models to calculate binding free energies, which were then compared to experimental values from the SAMPL4 challenge. Various error metrics including R2 correlation, root mean squared error, and linear regression slope were used to evaluate the results. The author found some improvement over previous methods, suggesting further refinement of conformational sampling could enhance the accuracy of binding free energy predictions.
Overview combining ab initio with continuum theoryDierk Raabe
Multi-methodological approaches combining quantum-mechanical and/or atomistic simulations
with continuum methods have become increasingly important when addressing multi-scale phenomena in
computational materials science. A crucial aspect when applying these strategies is to carefully check,
and if possible to control, a variety of intrinsic errors and their propagation through a particular multimethodological
scheme. The first part of our paper critically reviews a few selected sources of errors
frequently occurring in quantum-mechanical approaches to materials science and their multi-scale propagation
when describing properties of multi-component and multi-phase polycrystalline metallic alloys.
Our analysis is illustrated in particular on the determination of i) thermodynamic materials properties at
finite temperatures and ii) integral elastic responses. The second part addresses methodological challenges
emerging at interfaces between electronic structure and/or atomistic modeling on the one side and selected
continuum methods, such as crystal elasticity and crystal plasticity finite element method (CEFEM and
CPFEM), new fast Fourier transforms (FFT) approach, and phase-field modeling, on the other side.
This document discusses quantitative structure-activity relationship (QSAR) modeling and 3D-QSAR techniques. It explains that QSAR aims to find consistent relationships between biological activity and molecular properties in order to predict activity of new compounds. It also describes several common 3D-QSAR software programs and techniques, including CoMFA, VolSurf, Catalyst, and DOCK, and provides examples of their applications to modeling various cytochrome P450 enzymes.
This document is an internship report submitted by Yiteng Dang to the École Normale Supérieure on applying mean-field theory to study charge density waves in rare-earth nickelates. Chapter 1 provides theoretical background, discussing concepts like density of states calculations, the nearly free electron model, mean-field theory applied to ferromagnetism and antiferromagnetism, and Green's functions. Chapter 2 focuses on nickelates, introducing a low-energy two-orbital Hamiltonian and applying mean-field theory to obtain results like a phase diagram at half-filling and quarter-filling. Numerical methods are used throughout to solve problems in condensed matter theory.
1. The document describes COMSOL Multiphysics software, which is an interactive environment for modeling and solving scientific and engineering problems based on partial differential equations.
2. It can model coupled physics phenomena simultaneously using finite element analysis. It has various application modules for topics like acoustics, electromagnetics, heat transfer, fluid flow, and more.
3. An example is provided of modeling laminar fluid flow between two parallel plates to study inlet effects using the Chemical Engineering Module of COMSOL Multiphysics.
The document discusses performing molecular dynamics simulations using GROMACS to minimize the energy of a protein structure. It describes converting protein data files, setting up the simulation box, running the simulation with tools like grompp and mdrun, and analyzing the results by visualizing trajectories and the minimized protein structure.
The document presents a comprehensive evaluation and comparison of four machine learning interatomic potential (ML-IAP) methods: the Gaussian approximation potential (GAP), moment tensor potential (MTP), high-dimensional neural network potential (NNP), and spectral neighbor analysis potential (SNAP). It assesses the accuracy, data requirements, and computational cost of each method using standardized density functional theory data sets of six materials (Li, Mo, Cu, Ni, Si, Ge) spanning different crystal structures and bonding types. The evaluation shows that all ML-IAP methods achieve near density functional theory accuracy in predicting energies and forces, with trade-offs between accuracy and computational cost depending on the model complexity.
Materials Modelling: From theory to solar cells (Lecture 1)cdtpv
This document provides an overview of a mini-module on materials modelling for solar energy applications. It introduces the lecturers and outlines the course structure, which includes lectures on modelling, interfaces, and multi-scale approaches. It also describes a literature review activity where students will present a research paper using materials modelling in photovoltaics. Recommended textbooks are provided on topics like bonding in solids, computational chemistry, and density functional theory for solids.
In this deck from the HPC User Forum at Argonne, Andrew Siegel from Argonne presents: ECP Application Development.
"The Exascale Computing Project is accelerating delivery of a capable exascale computing ecosystem for breakthroughs in scientific discovery, energy assurance, economic competitiveness, and national security. ECP is chartered with accelerating delivery of a capable exascale computing ecosystem to provide breakthrough modeling and simulation solutions to address the most critical challenges in scientific discovery, energy assurance, economic competitiveness, and national security. This role goes far beyond the limited scope of a physical computing system. ECP’s work encompasses the development of an entire exascale ecosystem: applications, system software, hardware technologies and architectures, along with critical workforce development."
Watch the video: https://wp.me/p3RLHQ-kSL
Learn more: https://www.exascaleproject.org
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Quantitative structure-activity relationships (QSAR) use mathematical models to predict biological activity based on molecular properties. QSAR models are developed using statistical methods like partial least squares on datasets of compounds with known activities. Three-dimensional (3D) QSAR extends this approach by incorporating 3D structural descriptors and molecular fields derived from programs like CoMFA, VolSurf, and Catalyst to model activity based on interactions at binding sites. These 3D-QSAR models can be used to predict activity and design new compounds with improved properties.
The MCSP system is a mobile concentrating solar power technology being developed to efficiently charge electronic devices from solar energy. It uses a ball lens and dual-axis tracking mechanism to concentrate sunlight over 500 times onto small multi-junction solar cells. This allows the system to generate enough electricity with 2.5 times less cell material than flat plate PV systems. It is designed to be compact, portable, and provide off-grid power to consumer electronics using natural resources with minimal components and maintenance.
Characterization of the Scattering Properties of a Spherical Silver Nanoparti...AI Publications
Within this work Lumerical FDTD is applied to simulate how plane polarized light interacts with a single spherical silver nanoparticle. It allows for the determination of the light retention capability of the particle based upon counting how much light is scattered away from the particle after a long period as compared to how much enters the simulation region. This quantity, the nanoparticle albedo, is a key parameter in relating the scattering enhanced out-coupling efficiency. The two-dimensional finite-difference time-domain (FDTD) simulations are described for scattering layers with spherical nanoparticles in various external media for non-dispersive and have external indices from 1.0 to 2.0. FDTD takes into account this dispersive nature of the refractive index, which analytical solutions do not. A comparison between these two results will indicate that they agree within expected errors. The scattering and absorption cross-sections (CScat and CAbs), scattering and absorption efficiencies (QScat and QAbs), and albedo are calculated from this data. The albedo values are then output to the isotropic scattering model and an expected out-coupling factor is determined.
This document provides an overview of selective laser sintering (SLS) technology. It discusses the history and development of SLS, the SLS process, materials that can be used, applications, advantages and limitations. Recent developments discussed include using SLS to create electrical devices, 3D print in color, and develop drug delivery devices. Potential future applications highlighted are in the medical, aerospace, automotive and manufacturing industries, with a focus on increased speed, accuracy, size capacity and new materials like metals.
Similar to ADF modeling suite: DFT to MD software for chemistry and materials (20)
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfSelcen Ozturkcan
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
ADF modeling suite: DFT to MD software for chemistry and materials
1.
2. Table of contents
Key benefits .................................................................................... 3
Capabilities ....................................................................................... 5
ADF ...................................................................................................... 6
BAND ................................................................................................... 7
DFTB, MOPAC2012 ........................................................................... 7
ReaxFF .................................................................................................. 9
COSMO-RS ........................................................................................ 9
Fully integrated GUI .....................................................................10
Background.....................................................................................11
Feature list ...................................................................................13
List of authors ..........................................................................19
3. 3
Key benefits
One-stop modeling shop
Excellent software suite for tackling the most challenging problems
in materials science and chemistry. Easy set up and analysis with
GUI.
Fast computational toolbox
Working with hardware vendors, we optimize our codes for desktop
computers and parallel supercomputers. Latest algorithms.
Heavy elements & spectroscopy
High-quality all-electron Slater basis sets for all elements.
Accurate relativistic treatment. Many spectroscopic properties,
from NMR to X-ray.
Understand chemical bonding
Unique insight in chemical bonds with many chemical analysis
tools. Balanced charge decomposition schemes. Various density
analysis tools.
Hassle-free installation, free trial
With parallel binaries for all popular platforms, the entire ADF
suite installs out of the box. Try our powerful modeling tools:
scm.com/trial
Discuss your science with experts
With decades of experience, our expert support team (PhDs in
chemistry & physics) will help you with any queries that may arise.
Calculate charge mobility in organic electronics:
NEGF, transfer integrals, coupled FDE
Key benefits
5. 5
Capabilities
Organic electronics, unique features
SOC-TDDFT: phosphorescence lifetimes for OLEDs
Charge mobility calculations for OFETs,
organic semi-conductors
Accurate spectra of dyes, energy flows in dye-sensitized
solar cells
scm.com/OrganicElectronics
Accurate spectroscopy
From EPR to XANES, we offer a very broad range of spectroscopy.
ADF is particularly recommended by users for its excellent
capabilities for NMR and optical spectra.
scm.com/Spectroscopy
Advanced environment/solvation options
3D-RISM: solvation calculation with averaged solvent structure
QM/QM: frozen-density embedding, QUILD
DRF, SCRF: polarizable environments for MD and QM/MM
DIM/QM: coupled TDDFT + atomistic electrodynamics for
SERS, plasmon-exciton hybridization
scm.com/Solvation
Understand chemical bonds
ADF is used by those who truly want to understand chemical
bonding. Tools like energy decomposition, NBO, ETS-NOCV, NCI,
AIM, bond orders, Hirshfeld give unique insight.
scm.com/ChemicalAnalysis
Structure reactivity
Find TSs with NEB or Transition State Reaction Coordinate
(TSRC). Find shallow minima with fine integration and delocalized
coordinates. Rationally design catalysts with the activation strain
model.
scm.com/StructureAndReactivity
True 1D and 2D systems, compare periodic with cluster
Model polymers and surfaces without artificial repetition in other
dimensions. Compare bulk and cluster by using exact same set up.
Include surface solvation and electric fields. All-electron basis sets
for all elements.
scm.com/PeriodicDFT
Fast approximate DFT for large molecules
Density functional-based tight binding uses pair-wise parameters
for fast calculations, enabling you to study systems up to
thousands of atoms. Molecules, polymers, surfaces, bulk.
scm.com/DFTB
Atomistic modeling of large, reactive systems
ReaxFF was designed to tackle engineering challenges at the
atomistic level. Model the reactive dynamics of complex,
inhomogeneous systems up to 100,000s of atoms.
scm.com/ReaxFF
Solubilities, partition coefficients (log P), pKa
Predict many properties of pure fluids, mixtures and solutions
instantaneously with COSMO-RS. An easily expandable database
of 1892 compounds, allows you to prescreen solvent combinations
with the right properties for drug solubility and contamination
partitioning.
scm.com/COSMO-RS
Robust, parallel, efficient
We work with all major hardware vendors to scale up to 100s
of CPUs, and to exploit GPUs. Efficient algorithms for SCF and
geometry optimization are continuously being implemented.
scm.com/Parallel
Set up, run, and analyze all your modeling jobs effortlessly
Get to work quickly with our step-by-step tutorial and videos!
A fully integrated graphical user interface makes it easy to switch
between different compute engines and visualization tools. A large
database of compounds and import tools makes set up a breeze.
Advanced scripting tools to set up and analyze many jobs all at once.
scm.com/GUI
Capabilities
6. 6
ADF: Amsterdam Density Functional
Molecular research questions? ADF is the answer!
Our flagship program ADF has a 40-year track-record in handling
the most difficult problems in all areas of chemistry and materials
science. Accurate, fast, and robust software to study intricate
bonding and spectroscopy properties from simple to exotic
compounds.
Ever-expanding functionality
With our partners in industry and academia we keep implementing
the latest xc functionals and capabilities to ensure ADF can answer
your research questions also in the future.
Strong points
fast and well-parallelized
spectroscopy
transition metals, heavy atoms
user-friendly set-up support
truly understand chemistry
Selected unique features
spin-orbit coupling TDDFT
charge transfer integrals, Green’s functions
scrutinize chemical bonding interactions
Slaters: correct nuclear cusp (NMR, EPR)
environment: DIM/QM, 3D-RISM, FDE
energy decomposition, fragments
ADF
Relativity: only spin-orbit coupling gets 29
Si NMR spectral peak
shape right. Angew. Chem. Int. Ed. 50, 255 (2011)
7. 7
BAND: Periodic DFT
What can BAND do that your plane wave code cannot?
perfect companion to ADF: cluster periodic with
same settings
treat all electrons
treat surfaces as true 2D, polymers as true 1D
treat relativistic effects properly
include homogeneous electric fields
include continuum solvation (COSMO)
make life easy: build and visualize with GUI
calculate many spectra, orbitals density properties
Selected BAND features
spectra: NMR, EPR (g A tensors), EFG, Q-tensor, EELS
analysis: (P)DOS, band structures, COOP, AIM, ELF, fragments
lattice optimization, phonons
metal dielectric functions: TDCDFT
latest functionals: Grimme D3(BJ) dispersion, Truhlar mGGAs
specialized band gap functionals: GLLB-sc, TB-mBJ, GGA+U
BAND, DFTB, MOPAC
DFTB, MOPAC2012
Study really big systems at the quantum level
Our advanced multi-level schemes in ADF are not suitable for
partitioning your large molecule? Periodic systems with very large
unit cells?
Stewart’s semi-empirical MOPAC2012 and our density-functional
based tight binding (DFTB) modules could bring the quantum
precision you need to study these systems.
Quick insight, pre-screening or pre-optimization
With parameters for almost the entire periodic table, MOPAC2012
is a great tool for pre-optimization and pre-screening of conformers
before you dive in to more accurate DFT calculations. We and our
academic partners are determined to make DFTB parameters for
most nuclei, enabling you to get insight in the dynamic behavior
of various nano-sized systems.
MOPAC2012 H-Bi, Sparkles: lanthanides, molecules, 1D, 2D, 3D,
PM7, PM6, and more.
DFTB SCC, DFTB3, molecular dynamics, molecules, 1D,
2D, 3D, parallelized, properties
“What I really like about ADF? The programs were clearly written
by chemists for dealing with real chemical problems. A great suite
of programs!”
Prof. Roald Hoffmann - Nobel Laureate chemistry
QUOTEQUOTE
9. 9
ReaxFF
Study chemical reactions in really, really large systems
Model 100,000s of atoms with the reactive MD module ReaxFF
Easy building of complex homogeneous mixtures and surface-
liquid interfaces alike with the GUI
Visualize and analyze the changing molecular composition on
the fly
ReaxFF parameters
We collaborate with Prof. van Duin and others to include the
latest optimized force field parameters. Working on automated
procedures to construct your own force fields.
We keep on top of algorithmic developments to increase accuracy
and speed.
Dynamics
Define different temperature regimes, start with non-reactive
iterations. NVT, NVP, NVE. Accelerated dynamics available via
interface. Visualize trajectories.
Application areas
nanoscience
material science
biochemistry
combustion chemistry
polymer chemistry
catalysis
COSMO-RS
Instantaneous prediction of
solubilities
partition coefficients
pKa
values
vapor-liquid, liquid-liquid equilibria (VLE/LLE)
… and much more
activity coefficients, solvation free energies
Henry’s law constants
partial/total vapor pressures
boiling points of solvents and mixtures
excess energies GE
, HE
and TSE
azeotropes, miscibility gaps
COnductor-like Screening MOdel for Realistic Solvents
Thermodynamic properties calculated with quantummechanical
based COSMO-RS have predictive power outside the parameter-
ization set, as opposed to empirical models (UNIFAC).
Extensive database of compounds, easy to expand
Almost 1900 molecule are included in a database. Predict the
solubility or solvent partitioning for your own drug? Simply add
your own substances to our database with a fixed ADF recipe!
ReaxFF / COSMO-RS
“The GUI of ADF is one of the best builders I have ever used, the
possibility to create everything from simple ADF calculations to
complex QM/MM setups to band structure calculations make it
very appealing. Constructing metal complexes has never been so
easy.”
Dr. Michael Patzschke - University of Helsinki
QUOTEQUOTE
10. 10
Fully integrated GUI: Build, Run, Analyze!
Build
import cif, xyz, smiles
large database of structures
slice surfaces, create supercells
switch from molecular to periodic
build complex mixtures with Packmol
Run
Windows, Mac, Linux
cross-platform compatible, remote queues
easy switching from DFT to DFTB or MD and back
Analyze
quick visualization of MOs, densities, properties
(partial) DOS, band structures, many spectra
movies of vibrations, optimization, MD trajectories
Fully integrated GUI
DIM/QM: excited state QM/MM for molecules
on nanoparticles (L. Jensen)
11. 11
Licensing, pricing
Licenses are multi-platform and host-locked or floating. We
can tailor the license to your specific situation and modeling
requirements. Pricing depends on which modules you want, the
type of institution, number of cores and number of years. We offer
regional discounts and teaching-only discounts.
www.scm.com/Sales lists academic prices; you may also request
a quote from there.
Consultancy Contract research
Contact us at info@scm.com if you are interested in consultancy
options or contract research for your custom modeling needs.
Upon request we may also implement specific features.
Background
Relativity increases lead acid battery voltage from 2.4V to 12V!
Phys. Rev. Lett. 106, 018301 (2011)
Background
History
ADF originates from the academic work of Prof. Baerends (VU
Amsterdam) and Prof. Ziegler (University of Calgary). In 1995, the
company Scientific Computing Modelling NV was founded in
Amsterdam, and as of 2013 SCM employs 14 people, mostly highly
trained (PhDs) academics. With 3 successful EU projects we continue
to expand with several job openings and development plans.
Academic network: cutting-edge tools
Staying close to the academic community is paramount to us. It
keeps us on top of the latest developments in order to satisfy the
most pressing modeling demands of today and the future.
Academic developers are happy to see the burdens of debugging,
porting, testing and documenting taken off their hands by our
experienced software developers.
Documentation, support
Extensive documentation and step-by-step tutorials on our web
quickly help you on your way to set up calculations. The GUI has a
useful search function for features and molecules. Expert support
(support@scm.com) and a mailing list are available for all users.
Platform compatibility
The binaries work out of the box on the most popular (Windows,
Mac, Linux) platforms as well as for popular HPC architectures
(Cray, SGI, AIX, Altix, …). We offer help with compiling and
optimizing on non-standard systems on a no-cure, no-pay basis.
“I was very impressed by the quality of the support and their
efficiency”
Romaric David - head HPC Strasbourg University
QUOTEQUOTE
13. 13
Feature list
ADF: molecular DFT
Structure and Reactivity
optimization (ground and excited states)
transition states (TS reaction coordinate, EF, NEB), IRC, LT
(analytical) frequencies, initial Hessian estimates, constraints
and restraints
Cartesian, internal, delocalized coordinates
Model Hamiltonians
relativistic effects (ZORA, spin-orbit coupling)
modern xc: LDA, GGA, (range separated) hybrid-GGA,
meta-GGA, meta-hybrid-GGA
dispersion corrections: D3, D3-BJ, dDsC
potential-only: SAOP, GRAC, LB94, OEP
energy-only: more (hybrid) (meta-)GGAs
solvents, environments: COSMO, QM/MM, DRF, FDE, SCRF,
3D-RISM, QUILD, DIM/QM
electric field, point charges
finite nuclei
Electronic transport
transfer integrals
non-self-consistent Green’s function, wide-band limit
coupled FDE
Spectroscopic properties
IR, (resonance) Raman, MBH, VCD, VROA,
Franck-Condon factors
(vibrationally resolved) UV/Vis spectra, X-ray,
core excitations, state selection
CD, ORD, magnetizabilities, MCD, Verdet constants,
Faraday terms
(hyper-)polarizabilities, dispersion coefficients, lifetime effects
NMR chemical shifts, spin-spin couplings
ESR (EPR): g-tensor, A-tensor, Q-tensor, D-tensor (ZFS)
Nuclear quadrupole interaction (EFG), Mössbauer, NRVS
Analysis
molecule from fragments, symmetry
bond energy analysis, ETS-NOCV
Mulliken, Voronoi, and Hirshfeld charges, bond orders, NBO6,
NCI, SEDD, AIM, ELF, (partial) DOS
Accuracy and Efficiency
High-quality Slater basis sets Z = 1 to 118, all-electron,
frozen core, SZ to QZ4P
parallelized, linear scaling, distance cut-offs, density fit
LISTi, ADIIS, EDIIS, ARH, and spin-flip for flexible and
robust SCF convergence
Feature list
“The ADF program suite has very useful features that make it stand
out in comparison to other codes. Clusters and extended systems
can be directly compared, and switching relativistic effects on and
off gives unique insight.”
Dr. Michael Patzschke - University of Helsinki
QUOTEQUOTE
15. 15
BAND: periodic DFT
bulk crystals, polymers, surfaces
geometry optimization (including lattice), transition state
search, frequencies
XC: LDA, GGA, meta-GGA, dispersion corrections (D3, D3-BJ),
GGA+U, HTBS, GLLB-sc, TB-mBJ
relativistic effects with ZORA and spin-orbit coupling: SCF
and forces
finite nucleus approximation
COSMO solvation model for surfaces, static homogeneous
electric fields
TDDFT: frequency-dependent dielectric functions, EELS, SO
effects, Vignale-Kohn functional
DOS (total, partial, local), Mulliken population analysis, form
factors, AIM, ELF
STM images, smooth band structures, phonon dispersion
curves, Fermi surfaces
effective mass tensors
bond energy analysis (fragment approach)
NMR chemical shifts, shielding tensors
electric field gradient (NQCC)
ESR (EPR): A-tensor, g-tensor
parallel, linear scaling techniques
numerical orbitals and high-quality all-electron Slater orbitals
for all elements, SZ to QZ4P
DFTB
2nd
, 3rd
order self-consistent charges (SCC, DFTB3), dispersion
corrections
minima and TS optimization molecules and periodic
(1D, 2D, 3D) systems
molecular dynamics with Velocity Verlet, Berendsen and
scaling thermostats
phonons, DOS, band structure
MOPAC2012
molecules and periodic systems (1D, 2D, 3D)
minima and TSs, COSMO solvation
Sparkle for lanthanides
MOZYME: linear-scaling SCF for large systems
PM7, PM7-TS, MNDO, AM1, PM3, PM6, PM6-DH+, PM6-H2
ReaxFF
parallelized molecular dynamics and minimizations with
reactive force fields
analyze changing composition (reactants, intermediates,
products) during MD run
Berendsen thermostat; NVT, NPT or NVE ensembles;
constrained dynamics
easy set up of complex mixtures and solid-liquid interfaces in
3D box with Packmol
define different temperature regimes, pressure constraints,
bond constraints
up to 100.000s of atoms
COSMO-RS
predict properties of solutions and liquids with COSMO-RS or
COSMO-SAC
solubilities, partition coefficients (log P), activity coefficients,
solvation free energies, pKa
VLE (LLE) diagrams, boiling points, flash points, composition
lines, miscibility gaps
database of almost 1900 molecules
Feature list
16. 16Feature list
NEXAFS Spectrum of Metal Phthalocyanines with DFT-TS, J. Phys. Chem. A, 116, 2285 (2012)
Quick and easy visualization of orbitals, contour plots, and much more
17. 17
Integrated GUI
set up, run and analyze (complex) jobs for all programs
queue and monitor jobs on different machines
search: panels, documentation, database
draw molecules or import
(extensive database, .xyz, .pdb, .cif, SMILES)
pre-optimization with UFF, MOPAC, or DFTB
easy set up of complex mixtures and solid-liquid interfaces in
3D box with Packmol
seamless switching between all calculation and visualization
modules
3D data fields for orbitals, densities, potentials and more
field visualization via iso surfaces, cut planes or contour plots
visualize DOS, IR, Raman, CD, MCD, VCD, optical spectra, and
more
electronic band structures, phonon dispersion curves with
Brillouin Zone
display (partial) Density-Of-States for ADF, BAND and DFTB
draw orbital interaction diagrams (fragment approach)
show vibrations, optimizations, and MD trajectories
prepare multiple ADF calculations and compare results
graphically and numerically
monitor calculation progress, browse (live) output, for local and
remote jobs
Tools
QM/MM, QUILD: perform multi-layer calculations
PyMD: advanced MD (multi-scale, adaptive, biased)
scripting to prepare and report multiple complex jobs (PyADF)
Feature list
Calculated STM image (LDOS) for PtGe(100)
“The support at SCM is truly top notch”
Dr. Kwan Skinner - Top 10 US chemical company
QUOTEQUOTE
18. 18Feature list
Just a few clicks to set up and run a reactive MD run: water on Al surface
19. 19
The ADF authors and contributors currently include
E.J. Baerends
T. Ziegler
J. Autschbach
D. Bashford
A. Bérces
J.A. Berger
F.M. Bickelhaupt
C. Bo
P.L. de Boeij
P.M. Boerrigter
S. Borini
R. E. Bulo
L. Cavallo
D.P. Chong
L. Deng
R.M. Dickson
A. C. T. van Duin
D.E. Ellis
M. van Faassen
L. Fan
T.H. Fischer
C. Fonseca Guerra
M. Franchini
A. Ghysels
A. Giammona
S.J.A. van Gisbergen
A.W. Götz
J.A. Groeneveld
O.V. Gritsenko
M. Grüning
S. Gusarov
F.E. Harris
T. Heine
P. van den Hoek
C.R. Jacob
H. Jacobsen
L. Jensen
E.S. Kadantsev
J.W. Kaminski
G. van Kessel
R. Klooster
F. Kootstra
A. Kovalenko
M.V. Krykunov
E. van Lenthe
J.N. Louwen
D.A. McCormack
E. S. McGarrity
A. Michalak
M. Mitoraj
J. Neugebauer
V.P. Nicu
L. Noodleman
V.P. Osinga
S. Patchkovskii
M. Pavanello
P.H.T. Philipsen
D. Post
C.C. Pye
W. Ravenek
J.I. Rodríguez
P. Romaniello
P. Ros
P.R.T. Schipper
G. Schreckenbach
J.S. Seldenthuis
M. Seth
D.G. Skachkov
J.G. Snijders
M. Solà
M. Swart
D. Swerhone
G. te Velde
P. Vernooijs
L. Versluis
L. Visscher
O. Visser
F. Wang
T.A. Wesolowski
E.M. van Wezenbeek
G. Wiesenekker
S.K. Wolff
T.K. Woo
A.L. Yakovlev
Authors
Scientific Computing Modelling NV
Vrije Universiteit, Theoretical Chemistry
De Boelelaan 1083
1081 HV Amsterdam
The Netherlands
www.scm.com
info@scm.com
T +31 (0)20 598 76 26
F +31 (0)20 598 76 29
20. DFT to MD Software for Materials and Chemistry
One-stop modeling shop
Fast computational toolbox
Heavy elements spectroscopy
Understand chemical bonding
Hassle-free installation, free trial
Discuss your science with experts
www.scm.com