Clayson C. Spackman has extensive experience in 3D printing soft composites and fiber networks. He received his PhD in Mechanical Engineering from Rensselaer Polytechnic Institute where he developed a 3D printing technology for soft composites using inkjet printing and electrospun fibers. His research focused on investigating material failure mechanisms and developing innovative testing protocols. He has published several peer-reviewed articles and led multiple research projects funded by the NSF and DoD involving 3D printing composites, modeling fiber interactions, and developing educational lab modules.
Generally, the computer systems are made up of silicon-based computer technologies. In DNA computing, it is based on the computing techniques of DNA, biochemistry and molecular biology, instead of traditional silicon-based computer technology. Initially,Adleman computed an experiment which instances the Hamiltonian path problem with DNA test tubes in 1994. Then he computed further research on computation with molecular means in theoretical computer science. DNA computing has vast parallelism and high-density storage to solve many problems. Also, DNA has explored as an excellent material and a fundamental building block for developing large scale nanostructures, constructing individual nanomechanical devices, and performing computations. The input and output information will be in the molecular form which is demonstrated by molecular-scale autonomous programmable computers. This paper deals with the review of future advancements in DNA computing and challenges for researchers in future.
Network approaches have generated substantial interest based on their great potential for integrative omics analysis and are expected to facilitate a new era of precision understanding of complex diseases
From 3D Image to Simulation with Simpleware and COMSOLSimpleware
Simpleware software provides solutions for generating high-quality models from 3D image data (MRI, CT, micro-CT, FIB-SEM...) for direct export to COMSOL software for simulation.
Generally, the computer systems are made up of silicon-based computer technologies. In DNA computing, it is based on the computing techniques of DNA, biochemistry and molecular biology, instead of traditional silicon-based computer technology. Initially,Adleman computed an experiment which instances the Hamiltonian path problem with DNA test tubes in 1994. Then he computed further research on computation with molecular means in theoretical computer science. DNA computing has vast parallelism and high-density storage to solve many problems. Also, DNA has explored as an excellent material and a fundamental building block for developing large scale nanostructures, constructing individual nanomechanical devices, and performing computations. The input and output information will be in the molecular form which is demonstrated by molecular-scale autonomous programmable computers. This paper deals with the review of future advancements in DNA computing and challenges for researchers in future.
Network approaches have generated substantial interest based on their great potential for integrative omics analysis and are expected to facilitate a new era of precision understanding of complex diseases
From 3D Image to Simulation with Simpleware and COMSOLSimpleware
Simpleware software provides solutions for generating high-quality models from 3D image data (MRI, CT, micro-CT, FIB-SEM...) for direct export to COMSOL software for simulation.
July 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
December 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
November 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Visualization and Analysis of Dynamic Networks Alexander Pico
DynNetwork development was taken up initially by Sabina Sara Pfister back in GSoC 2012. She laid out a strong foundation for dynamic network visualization in Cytoscape and my job was to extend the plugin’s functionality to help users analyse time changing networks. The two of us were mentored by Jason Montojo. We had developed a decent tool over the course of two GSoC programs to aid dynamic network analysis and our efforts culminated in DynNetwork getting accepted for an oral presentation at the International Network for Social Network Analysis (INSNA), Sunbelt 2014 which was held in St. Petersburg, FL in February.
Advanced MicroCT for Non-Destructive 3D Multiscale AnalysisInsideScientific
X-ray computed tomography (CT) is becoming an increasingly important tool for the non-destructive characterization and inspection of the three-dimensional microstructure of various materials, products and sample types. The technique creates a three-dimensional representation of a sample/material by reconstructing cross-sectional images or ‘virtual slices’ through a sample.
In this webinar, Robert Williams, PhD, and Mark Riccio will highlight the versatility of the Thermo Scientific™ HeliScan™ microCT, demonstrating the wide breadth of sample types and sizes that the instrument can characterize, such as: polymers, metals, manufactured parts, batteries, rock/porous media, electronics, bone and soft tissue (plants, insects, brain, etc). The HeliScan™ microCT creates valuable solutions by leveraging a helical scanning technique (found in clinical CT scanners) for large volume data acquisition and features a Lab6 X-ray filament for high resolution (400nm) capability.
The ease of use and high throughput of this system makes it ideal for investigations that need to identify and quantify a sample’s 3D internal structure (e.g. voids, cracks, pore networks, coatings, etc.) non-destructively. 4D structural dynamics can be studied by acquiring multiple 3D microCT datasets. Additionally, HeliScan™ microCT is an integral component of a multi-modal macro-scale to atomic-scale workflow involving focused ion beam/scanning electron microscopes and transmission electron (TEM) microscopes.
July 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
December 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
November 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Visualization and Analysis of Dynamic Networks Alexander Pico
DynNetwork development was taken up initially by Sabina Sara Pfister back in GSoC 2012. She laid out a strong foundation for dynamic network visualization in Cytoscape and my job was to extend the plugin’s functionality to help users analyse time changing networks. The two of us were mentored by Jason Montojo. We had developed a decent tool over the course of two GSoC programs to aid dynamic network analysis and our efforts culminated in DynNetwork getting accepted for an oral presentation at the International Network for Social Network Analysis (INSNA), Sunbelt 2014 which was held in St. Petersburg, FL in February.
Advanced MicroCT for Non-Destructive 3D Multiscale AnalysisInsideScientific
X-ray computed tomography (CT) is becoming an increasingly important tool for the non-destructive characterization and inspection of the three-dimensional microstructure of various materials, products and sample types. The technique creates a three-dimensional representation of a sample/material by reconstructing cross-sectional images or ‘virtual slices’ through a sample.
In this webinar, Robert Williams, PhD, and Mark Riccio will highlight the versatility of the Thermo Scientific™ HeliScan™ microCT, demonstrating the wide breadth of sample types and sizes that the instrument can characterize, such as: polymers, metals, manufactured parts, batteries, rock/porous media, electronics, bone and soft tissue (plants, insects, brain, etc). The HeliScan™ microCT creates valuable solutions by leveraging a helical scanning technique (found in clinical CT scanners) for large volume data acquisition and features a Lab6 X-ray filament for high resolution (400nm) capability.
The ease of use and high throughput of this system makes it ideal for investigations that need to identify and quantify a sample’s 3D internal structure (e.g. voids, cracks, pore networks, coatings, etc.) non-destructively. 4D structural dynamics can be studied by acquiring multiple 3D microCT datasets. Additionally, HeliScan™ microCT is an integral component of a multi-modal macro-scale to atomic-scale workflow involving focused ion beam/scanning electron microscopes and transmission electron (TEM) microscopes.
It is a distinct pleasure for me to write in support of my student, Jackie Pang. He studied in my lab for about three years, during which time I witnessed his research achievement and outstanding leadership.
Jackie entered my lab when he was a junior student. At first He had difficulty accepting the strict attendance and assignments. But soon, he learned to manage his time, work in group situations and enjoyed the opportunity to learn from his older peers.
In the past two years, Jackie took a great deal of work in the projects. Even so, he spent most of the rest of time doing research and published several technical reports and papers including one journal paper in both scientific visualization and information visualization.
Jackie is an outstanding student of wide interests. He has won many awards on math, physics and informatics. He also received many honors from many cities, colleges and societies.
Jackie has a lively and enquiring mind. When he comes up with a new idea, he always writes it down and discusses its feasibility with his peers. He also has strong practice ability and done a lot of pioneering work in team building and infrastructure construction. Last year, he developed a website for us to review papers online and created a wiki site for his group to share their experience.
Jackie is also very kind and willing to help his classmates. He always collects materials from the web and sends them to others after putting these materials in order. He is also careful and responsible, and can express clearly.
Since Jackie has long since become the most valuable member of my lab, and a role model for his newer classmates, I recommend him to your fellowship program with absolute confidence.
Thank you for the opportunity of correspondence.
Summary of June 2014 Workshop Report: Building a Materials Accelerator NetworkSusann Ely
Summary of June 2014 Workshop Report: Building a Materials Accelerator Network. Presented by Prof. Dave McDowell, Executive Director, GA Tech Institute for Materials. Presented at the UMC Meeting, MS&T 2015. Oct. 7, 2015
TMS workshop on machine learning in materials science: Intro to deep learning...BrianDeCost
This presentation is intended as a high-level introduction for to deep learning and its applications in materials science. The intended audience is materials scientists and engineers
Disclaimers: the second half of this presentation is intended as a broad overview of deep learning applications in materials science; due to time limitations it is not intended to be comprehensive. As a review of the field, this necessarily includes work that is not my own. If my own name is not included explicitly in the reference at the bottom of a slide, I was not involved in that work.
Any mention of commercial products in this presentation is for information only; it does not imply recommendation or endorsement by NIST.
1. Clayson C. Spackman
Email: clay.spackman@gmail.com • Phone: (208) 286-5984
EDUCATION
Rensselaer Polytechnic Institute, Troy, NY 2016
Doctor of Philosophy - Mechanical Engineering GPA: 3.27/4.00
Dissertation Title: “Direct Writing of Fiber Networks for 3D Printing Soft Composites”
Pepperdine University, Malibu, CA 2012
Bachelor of Science - Physics GPA: 3.54/4.00
Minor-Creative Writing
Pepperdine University, Lausanne, Switzerland (Semester Abroad) Spring 2010
TECHNICAL SKILL SETS
Experimental:
Development of a reliable and scalable 3D printing
technology for soft composite materials
Investigating fundamental material failure
mechanisms using state-of-the-art metrology
units (Alicona, Zeta Instruments, Zeiss SEM)
Designed innovative material testing protocols for
nano-scale fibers, nano-ropes, and soft composites
Inkjet 3D printing using micro-scale piezoelectric
nozzles
High speed imaging (200k+ frames/s)
Calibration and validation of FEM/CZM
models with physical experiments
Micro-scale machining using DT-110 Hybrid
μEDM machine
SEM analysis of fracture surfaces
Electrospinning aligned/co-axial/non-
woven/multi-material nanofibers
Direct-writing of nano-scale fiber structures
Modeling:
Using cohesive zone modelling (CZM) to model
delamination, crack growth, adhesive bond failure
Using parametric studies to impact
manufacturing process variables (e.g. peel rate)
Automated digital image analysis
Multiphysics finite element modeling (FEM) of
electrospinning production systems
Simulation of surface roughness
Creating material failure models (traction-
separation curves)
PEER-REVIEWED PUBLICATIONS
1. Spackman, C., Picha, K., Gross, G., Nowak, J., Smith, P., Zheng, J., Samuel, J., and Mishra, S. “A Novel
Multimaterial Additive Manufacturing Technique for Fabricating Laminated Polymer
Nanocomposite Structures.” J. Micro Nano-Manuf. 3(1), 011008 (Mar 01, 2015) (11 pages)
2. Spackman, C., Frank, C.R., Picha, K., and Samuel J., “3D Printing of Fiber-reinforced Soft Composites:
Process Study and Material Characterization.” Journal of Manufacturing Processes, Vol 23, Aug.
2016, Pages 296–305.
3. Picha, K., Spackman, C., and Samuel J., “Droplet Spreading Characteristics Observed During 3D
Printing of Aligned Fiber-reinforced Soft Composites.” Additive Manufacturing, Vol 12, Part A, Oct.
2016, Pages 121–131.
4. Spackman, C., Ruff, L., Crucetti, J., Chiappone, S., Schadler, L., and Samuel, J. “Research University and
Community College Collaboration Model to Promote Micro Manufacturing Education: Preliminary
Findings.” North American Manufacturing Research Conference: NNMI Mfg. Education & Workforce
Development (June 2016)
5. Spackman, C.C., Nowak F. J., Mills, K.L., and Samuel J., “A Cohesive Zone Model for the Fiber Stamping
Process Encountered During 3D Printing of Fiber-reinforced Soft Composites”, Under review, ASME
Journal of Manufacturing Science and Engineering (Submitted: Dec 2016)
2. RESEARCH EXPERIENCE
Graduate Research Assistant, August 2012 – December 2016
RPI Nano/Micro-scale Manufacturing and Materials Design Laboratory in Troy, NY
Surgeon Training: Synthetic Human Materials by 3D Printing; Funding Agency: U.S. Dept. of Defense
Objective: Design and build a prototype of a new 3D printer capable of printing laminated
composite parts for applications in surgeon training
o Invented new 3D printing technology which combines inkjet printing with electrospun fibers
o Led 7 student team that developed a novel 3D printing process capable of creating composites
o Aided in writing Phase II grant proposal that was selected by DoD over other applicants
3D Printing of Hierarchical Fiber-Reinforced Soft Composites; Funding Agency: NSF
Objective: Investigate the fundamental manufacturing science and process-control problems
unique to the 3D printing of Hierarchical Fiber-Reinforced Soft Composites (HFrSCs)
o Designed experiments to evaluate key manufacturing process steps
o Developed a series of experimental and analytical techniques using optical profilometer, micro-
scale tensile testing, and failure analysis to evaluate novel nanocomposites
o Used Scanning Electron Microscope (SEM) to characterize fracture surfaces of failed specimens
Inkjet 3D Printing/Substrate Interaction Study; Funding Agency: National Science Foundation
Objective: Identify the behavior of liquid droplets on a new surface (nano-fibrous) to aid process
planning for 3D printing of HFrSCs
o Used high-speed imagery to observe droplet-substrate interaction in a parametric study
o Automated digital image analysis techniques using MATLAB program to analyze ~10 TB of data
Finite Element Modeling; Funding Agency: NSF
Objective: To gain a fundamental understanding of the underlying physical phenomenon present
in a composite layup operation; close the loop by using FEA results to design new mech. system
o Built a multimaterial FEM in ABAQUS; conducted parametric studies for key design variables
o Designed and executed a validation study to confirm modeling results
o Using model-aided design, improved efficiency of stamping process for 3D printing HFrSCs
Electric Field Modeling; Funding Agency: U.S. Dept. of Defense
Objective: To design the electric field of a nanofiber collection device to improve its efficiency
o Built a multi-material, multiphysics model using COMSOL to evaluate electrode designs
PEDAGOGICAL EXPERIENCE
Advanced Manufacturing Education; Funding Agency: NSF
Objective: To develop three independent lab modules for graduate/undergrad. students at RPI,
HVCC, and NTU featuring electrospinning, near-field E-jet, and micro-machining
o Led development of conceptual educational framework, content, and assessment tools
o Collected, curated, and analyzed assessment data and fed results into lab module improvements
o Collaborated with a team of 5 interdisciplinary faculty from multiple educational institutions
o Demonstrated abilities to communicate material effectively with several student demographics
RELEVANT SKILLS
FEM & CAD Platforms: COMSOL (Proficient), ABAQUS (Expert), SolidWorks (Proficient)
Statistical/Engineering Analysis: MINITAB (Proficient), MATLAB (Expert)
Programming: C++ (Proficient), G-Code CNC Control (Proficient), LabVIEW (Proficient)
LEADERSHIP ACTIVITIES
Sigma Phi Epsilon, Pepperdine University -Vice President of Recruitment, Mentor of the 10 Year Plan
AmeriCorps - Jumpstart Corps Member Volunteer (Santa Monica, CA)