This document discusses reaction rates and kinetics concepts including:
- Instantaneous reaction rates can be calculated from the slope of concentration-time graphs at specific points.
- Reaction orders and rate laws can be determined experimentally using methods like the initial rate method or integrated rate law method.
- First-order reactions follow the integrated rate law that the natural log of the concentration is linear with time. Second-order and zero-order reactions also have defining rate laws and kinetics equations.
The rate of a reaction, average and instantaneous rate of reaction,order and molecularity of reaction, determination of Oder and molecularity, the integrated rate law of reaction, deferential rate law of reaction, zero order, first order and second order reaction, numerical for practice
The rate of a reaction, average and instantaneous rate of reaction,order and molecularity of reaction, determination of Oder and molecularity, the integrated rate law of reaction, deferential rate law of reaction, zero order, first order and second order reaction, numerical for practice
Design of Methanol Water Distillation Column Rita EL Khoury
Methanol is an essential feed stock for the manufacture of many industrial products such as adhesives and paints and it is widely used as a solvent in many chemical reactions. Crude methanol is obtained from steam reforming of natural gas and then a purification process is needed since it contains smaller and larger degree of impurities.
The purification process consists of two steps: a topping column used to remove the low boiling impurity called the light ends; and the remaining water methanol mixture is transferred to another column called the refining column where it is constantly boiled until separation occurs. Methanol rises to the top while the water accumulates in the bottom.
This document focuses on methanol water separation. A detailed design study for the distillation column is conducted where the separation occurs at atmospheric pressure with a total condenser and a partial reboiler.
Discusses rates of chemical reaction and how they may be altered. Included is the rate law, first, second and zero order reactions as well as the Arrhenius equation.
**More good stuff available at:
www.wsautter.com
and
http://www.youtube.com/results?search_query=wnsautter&aq=f
Reactor and Catalyst Design
0 INTRODUCTION/PURPOSE
1 SCOPE
2 FIELD OF APPLICATION
3 DEFINITIONS
4 CATALYST DESIGN
4.1 Equivalent Pellet Diameter
4.2 Voidage
4.3 Pellet Density
5 REACTOR DESIGN
6 CATALYST SUPPORT
6.1 Choice of Support
TABLES
1 CATALYST SUPPORT SHAPES
2 SECONDARY REFORMER SPREADSHEET
FIGURES
1 GRAPH OF EFFECTIVENESS v THIELE MODULUS
2 VARIATION OF COSTS WITH CATALYST SIZE
3 VARIATION OF COSTS WITH CATALYST BED VOIDAGE
4 VARIATION OF COSTS WITH VESSEL DIAMETER
Design of Methanol Water Distillation Column Rita EL Khoury
Methanol is an essential feed stock for the manufacture of many industrial products such as adhesives and paints and it is widely used as a solvent in many chemical reactions. Crude methanol is obtained from steam reforming of natural gas and then a purification process is needed since it contains smaller and larger degree of impurities.
The purification process consists of two steps: a topping column used to remove the low boiling impurity called the light ends; and the remaining water methanol mixture is transferred to another column called the refining column where it is constantly boiled until separation occurs. Methanol rises to the top while the water accumulates in the bottom.
This document focuses on methanol water separation. A detailed design study for the distillation column is conducted where the separation occurs at atmospheric pressure with a total condenser and a partial reboiler.
Discusses rates of chemical reaction and how they may be altered. Included is the rate law, first, second and zero order reactions as well as the Arrhenius equation.
**More good stuff available at:
www.wsautter.com
and
http://www.youtube.com/results?search_query=wnsautter&aq=f
Reactor and Catalyst Design
0 INTRODUCTION/PURPOSE
1 SCOPE
2 FIELD OF APPLICATION
3 DEFINITIONS
4 CATALYST DESIGN
4.1 Equivalent Pellet Diameter
4.2 Voidage
4.3 Pellet Density
5 REACTOR DESIGN
6 CATALYST SUPPORT
6.1 Choice of Support
TABLES
1 CATALYST SUPPORT SHAPES
2 SECONDARY REFORMER SPREADSHEET
FIGURES
1 GRAPH OF EFFECTIVENESS v THIELE MODULUS
2 VARIATION OF COSTS WITH CATALYST SIZE
3 VARIATION OF COSTS WITH CATALYST BED VOIDAGE
4 VARIATION OF COSTS WITH VESSEL DIAMETER
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
3. A more refined description The average reaction rate gives us information about the speed of the reaction over a certain period of time. But what if we are interested in a more detailed description. How do we calculate the instantaneous reaction rate at any particular time?
4. START END Different Rates During a Reaction Overall average rate Initial Rate Instantaneous Rate (slope of the line At a point)
5. . From your lab experience, how could we follow the course of this reaction? Measure rates? What’s changing? What could we measure? Measuring Rates Consider this reaction: Br 2 ( aq ) + HCOOH ( aq ) 2Br - ( aq ) + 2H + ( aq ) + CO 2 ( g ) time
6. [Br 2 ] Absorption Br 2 ( aq ) + HCOOH ( aq ) 2Br - ( aq ) + 2H + ( aq ) + CO 2 ( g ) time 393 nm light Detector 393 nm Br 2 ( aq )
7. Instantaneous rate = rate for specific tiny instance in time Br 2 ( aq ) + HCOOH ( aq ) 2Br - ( aq ) + 2H + ( aq ) + CO 2 ( g ) Average rate = [Br 2 ] t = - [Br 2 ] final – [Br 2 ] initial t final - t initial slope of tangent slope of tangent slope of tangent
8. rate [Br 2 ] rate = k [Br 2 ] + 0.0 = rate constant = 3.50 x 10 -3 s -1 Y=mX+b Constant = Slope = k How do the RATES change with [Br 2 ] ? Rate = k [Br 2 ] 1 this is called a 1 st order reaction Rate Law The rate law for a reaction tells us how rate varies with concentration of the reactants. Br 2 (aq) + HCOOH(aq) HBr(aq) + CO 2 (g) R A T E k = rate [Br 2 ]
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16. Rate Laws In general, for a A + b B x X with a catalyst C Rate = k [A] m [B] n [C] p The exponents m, n, and p are the reaction order with respect each reactant Overall reaction order= m + n + p These numbers can be 0, 1, 2 or fractions and must be determined by experiment ! They are NOT related to the stoichiometric coefficients a,b,x
18. Determining Reaction Orders Using Initial Rates Compare 2 experiments in which the concentration of one reactant varies and the concentration of the other reactant(s) remains constant. k [O 2 ] 2 m [NO] 2 n k [O 2 ] 1 m [NO] 1 n = = [O 2 ] 2 m [O 2 ] 1 m = 6.40x10 -3 mol/L*s 3.21x10 -3 mol/L*s = ; 2 = 2 m m = 1 Do a similar calculation for the other reactant(s). Run a series of experiments, each of which starts with a different set of reactant concentrations, and from each obtain an initial rate. O 2 ( g ) + 2NO( g ) 2NO 2 ( g ) rate = k [O 2 ] m [NO] n rate 2 rate 1 [O 2 ] 2 [O 2 ] 1 m 1.10x10 -2 mol/L 2.20x10 -2 mol/L m
20. Expected Solution : Another Example Consider this reaction inside a car engine: How can we use this data to determine the rate law and the rate orders with respect to each reactant? rate = k [NO 2 ] m [CO] n Exp. Initial Rate (mol/L*s) Initial [NO 2 ] Initial [CO] 1 2 3 0.0050 0.080 0.0050 0.10 0.10 0.40 0.10 0.10 0.20
21. 16 = 4 m and m = 2 The reaction is 2 nd order in NO 2 . First, choose two experiments in which [CO] remains constant and the [NO 2 ] varies . One Variable at a Time 0.080 0.0050 rate 2 rate 1 [NO 2 ] 2 [NO 2 ] 1 m = k [NO 2 ] m 2 [CO] n 2 k [NO 2 ] m 1 [CO] n 1 = 0.40 0.10 = m Exp. Initial Rate (mol/L*s) Initial [NO 2 ] Initial [CO] 1 2 3 0.0050 0.080 0.0050 0.10 0.10 0.40 0.10 0.10 0.20
22. Now, choose two experiments in which [NO 2 ] remains constant and the [CO] varies. One Variable at a Time The reaction is zero order in CO . rate = k [NO 2 ] 2 [CO] 0 = k [NO 2 ] 2 Overall order Exp. Initial Rate (mol/L*s) Initial [NO 2 ] Initial [CO] 1 2 3 0.0050 0.080 0.0050 0.10 0.10 0.40 0.10 0.10 0.20 k [NO 2 ] m 3 [CO] n 3 k [NO 2 ] m 1 [CO] n 1 [CO] 3 [CO] 1 n = rate 3 rate 1 = 0.0050 0.0050 = 0.20 0.10 n ; 1 = 2 n and n = 0
23. Your Turn rate = k [NO 2 ] 2 What is the value of the constant, k, in this reaction? Exp. Initial Rate (mol/L*s) Initial [NO 2 ] Initial [CO] 1 2 3 0.0050 0.080 0.0050 0.10 0.10 0.40 0.10 0.10 0.20
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25. Overall Reaction Order Units of k (t in seconds) 0 mol/(L*s) (or mol L -1 s -1 ) M/s 2 L/(mol*s) (or L mol -1 s-1) 1/Ms 3 L 2 /(mol 2 *s) (or L 2 mol -2 s -1 ) 1/M 2 s Units: Rate Constant k 1 1/s (or s -1 )
26. Concentration-Time Relations Consider a FIRST ORDER REACTION: A B The rate law is Rate= k[A] RATE= -d[A]/dt = k[A] How can we predict the concentration of reactants at any moment in time? How do you find [A] = f(t) ?
28. Integrating - (d[A]/d t) = k [A], we get [A] / [A] 0 =fraction remaining after time t has elapsed. Called the integrated first-order rate law Integrated Rate Laws
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33. First-Order Reactions The half-life , t ½ , is the time required for the concentration of a reactant to decrease to half of its initial concentration. t ½ = t when [A] = [A] 0 /2 = 1200 s = 20 minutes How do you know decomposition is first order? units of k (s -1 ) ln [A] 0 [A] 0 /2 k = t ½ ln2 k = 0.693 k = What is the half-life of N 2 O 5 if it decomposes with a rate constant of 5.7 x 10 -4 s -1 ? t ½ ln2 k = 0.693 5.7 x 10 -4 s -1 =
34. A plot of [N 2 O 5 ] vs. time for three half-lives
38. Zero-Order Reactions rate = k [A] 0 = k k = = M /s [A] is the concentration of A at any time t [A] 0 is the concentration of A at time t =0 t ½ = t when [A] = [A] 0 /2 [A] = [A] 0 - kt A product rate = - D[A] D t rate [A] 0 D[A] D t = k - t ½ = [A] 0 2 k
39. Consider the following data for the reaction: N 2 O 5 -> 2NO 2 + ½ O 2 Graphical Analysis
40. Summary ln[A] t = -kt + ln[A] 0 1/[A] t = kt + 1/[A] 0 [A] t = -kt + [A] 0
41. At 1000 0 C, cyclobutane (C 4 H 8 ) decomposes in a first-order reaction, with the very high rate constant of 87 s -1 , to two molecules of ethylene (C 2 H 4 ). If the initial C 4 H 8 concentration is 2.00M, what is the concentration after 0.010 s? _____________ M
42. At 1000 0 C, cyclobutane (C 4 H 8 ) decomposes in a first-order reaction, with the very high rate constant of 87 s -1 , to two molecules of ethylene (C 2 H 4 ). (b) What fraction of C 4 H 8 has decomposed in this time?
43. SOLUTION: [C 4 H 8 ] = 0.84 mol/L = 0.58 ln 2.00 [C 4 H 8 ] = -(87s -1 ) (0.010s) ln [C 4 H 8 ] 0 [C 4 H 8 ] t = - k t (a) (b) [C 4 H 8 ] 0 - [C 4 H 8 ] t [C 4 H 8 ] 0 = 2.00M - 0.84M 2.00M
44. PLAN: Cyclopropane is the smallest cyclic hydrocarbon. Because its 60 0 bond angles allow poor orbital overlap, its bonds are weak. As a result, it is thermally unstable and rearranges to propene at 1000 0 C via the following first-order reaction: The rate constant is 9.2s -1 , (a) What is the half-life of the reaction? (b) How long does it take for the concentration of cyclopropane to reach one-quarter of the initial value? One-quarter of the initial value means two half-lives have passed. Use t 1/2 = ln2/k to find the half-life
45. SOLUTION: t 1/2 = 0.693/9.2s -1 = 0.075s (a) 2 t 1/2 = 2(0.075s) = 0.15 s (b)
46. 0 th Order 1 st Order 2 nd Order Plot for straight line Slope, y-intercept Half-life Rate law rate = k rate = k [A] rate = k [A] 2 Units for k mol/(L*s) 1/s L/(mol*s) Int. rate law (straight-line form) [A] t = -k t + [A] 0 ln[A] t = - k t + ln[A] 0 1/[A] t = k t + 1/[A] 0 [A] t vs. t ln[A] t vs. t 1/[A] t vs t -k, [A] 0 -k, ln[A] 0 k, 1/[A] 0 [A] 0 /(2 k) (ln 2)/ k 1/( k [A] 0 ) Overview
47. Summary Activity: N 2 O 5 (g) NO 3 (g) + NO 2 (g) Consider the following graphs and reaction data to predict the concentration of N 2 O 5 at 275 sec. Time (s) [N 2 O 5 ] 0 1.000 25 0.822 50 0.677 75 0.557 100 0.458 125 0.377 150 0.310 175 0.255 200 0.210
48. What is the concentration of N 2 O 5 after 275 sec? ______________ mol/L
Editor's Notes
Update for Tro.
Tier 1.5
Tier 1.5
Tier 1
Tier 1.5
Tier 2 introduction
Tier 2 introduction
Since we already went through an example – Let the students work this one. Tier 2
Tier 1.5
Tier 3
Tier 1
Tier 1, Tier 1.5
Point out that this only works (b) for 1 st order reactions where half-life is not dependent on initial concentration. Tier 1, Tier 1