Advances in Catalyst Modelling and Simulation
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Advances in Catalyst Modelling and Simulation

Recently issued technical report, exclusively for members of TCGR’s Catalytic Advances Program (CAP),
provides insights into computational catalysis…

See report TofC here (as PDF)

As you well know, computers have become indispensable to all aspects of the chemical industry. Software has allowed gains in mechanistic information of chemical processes, facilitating the analysis of the origins of selectivity or the study of more complex reactivity scenarios, such as those related to catalysis as well as property predictions. The immense progress of hardware, theoretical methods, and software over the past 50 years has paved the way for a dramatic increase in application of computational chemistry.

The importance of computational methods cannot be overstated; however they alone cannot (yet) replace experiments because the interesting reactivity problems tend to be more complex, larger in size and with many more mechanistic possibilities. Consequently, the time it takes to gain unambiguous mechanistic information is also increased.

In addressing these vital issues, The Catalyst Group Resources (TCGR) has recently issued a technical report entitled, Advances in Catalyst Modelling and Simulation, commissioned by members of the Catalytic Advances Program (CAP). This report, exclusively for members of CAP, provides insights into computational catalysis for use in addressing industrial challenges.

Computational catalyst modelling leads to progress in many industrial sectors, as it offers a unique insight into properties and behavior of materials and industrial manufacturing processes as well as provides understanding of the underlying physics and chemistry of materials, devices and processes. It can help to design prototypes by enabling pre-screening or faster screening of alternative materials and designs, predicting final product properties and performance, determination if a design concept works without having to build it, and optimization of production process.

Continuous investment in computational catalysis makes the insightful,
industrially-relevant case studies in this CAP report especially timely…

Application of modeling and simulation techniques to catalyst design, optimization and improvement are often called the ab-initio approach to catalyst design. This consists of a set of methods, which are able to characterize the reagents, the catalyst, the reaction, and the reactor it takes place in. The methods can be used to describe:

  • The morphology of the active site;
  • Reagents speciation;
  • How individual molecules interact with the active site;
  • How changes in the active sites influence reactivity;
  • How to convert feed and mechanistic data, extracted from the simulations, into predictive models for improving catalyst and process performance.

Recent studies on impacts of molecular modelling and materials modelling show an increased interest and application of theoretical tools in the industrial practice. These are based upon increased impact indicators, such as number of publications, patents, number of molecules researched by computational chemistry, etc. In fact, BASF, the world’s oldest and largest chemical company with the biggest R&D budget (>$2 billion), is boosting R&D productivity by using computational chemistry to design or even replace laboratory experiments.

The impacts of modelling and simulation have been quantified…

The industrial respondents of a 2016 industry survey addressing the impact of modelling and simulation identified the following typical R&D process improvement benefits due to the application of modeling and simulation techniques: 1) More efficient and targeted experimentation, 2) deeper understanding, 3) broader exploration, and 4) avoiding potentially hazardous experimentation. The impact of materials modeling was measured based on the following descriptors (listed here in the order of relevance):

  • Innovations accomplished; 81% of respondents reported innovation accomplishments as a result of materials modeling.
  • Costs saved; almost 60% of analyzed projects reported cost savings due to the materials modelling project. The absolute cost savings ranged from €100K to €50M with an average of €12M and a median of €5M. Costs saved as a multiple of the investment in materials modelling ranged from 1 to 300 (see Figure 10), with an average of 41 and a median of 5.
  • Jobs created, about 35% of cases reported new jobs for the modelling projects.
  • Increased revenue was reported by 30% of companies; for projects in which the investment in modelling and the total investment and revenue generated were known, an ROI factor (ratio of revenue generated and investment in modelling) ranged from 2 to 1000 with an average of 130 and a median of 5 (when the largest and the smallest ROI values were omitted, the ROI factor yielded an average of 8). A trend for ROI to grow more than linearly with investment in modelling was found.

The analyses show that the resulting advances in materials, designed with an aid of modeling and simulation techniques, as well as products manufactured from these materials have the potential to impact the economy and society in a variety of ways.

TCGR’s timely report addresses real-world, industrially-focused challenges…

Chapter 1, Introduction, discusses how the field must bridge the scales from microscopic (via mesoscopic) to macroscopic of different catalytic phenomena by theoretical description.

Chapter 2, Advances in Catalyst Modeling, presents recent advances in catalyst modelling, including: 1) how to plan experiments to generate kinetic models for new catalysts; 2) modelling methods based on classical physics with focus on those using reactive force fields; 3) discussion of quantum based models, with emphasis on Density Functional Theory (DFT) methods; and 4) structure-activity relationships analyses which are a now an important tool for catalytic performance prediction.

Chapter 3, Advances in Catalyst Simulation, focuses on simulating the catalysts, and introduces advances in Kinetic Monte Carlo and microkinetic modelling. Their most popular variants are presented and their capabilities compared. Then, Finite Elements Methods are briefly presented, followed by the discussion of the recent applications of Computational Fluid Dynamics (CFD). The chapter is concluded by showing how the presented methods can be used in the study of catalysts deactivation and regeneration.

 Advances in Catalyst Modelling and Simulation is based on the recent literature review and interviews with computational chemistry practitioners, working for industry. Don’t be left behind your competitors by lagging in this 4th industrial revolution!

TCGR’s Catalytic Advances Program (CAP) is an information resource for research and development organizations in the chemical, polymer, and petroleum industries. Depending on their membership choice, CAP members may receive all three or just two annual technical reports as well as the weekly newsletter known as CAP Communications. This newsletter provides the latest updates on technical breakthroughs, commercial advancements, noteworthy conference proceedings, and exclusive development opportunities. Membership also includes attendance at a CAP Annual Meeting, with dates, location, and topics selected by the membership.

More information about this and other services of the Catalytic Advances Program (CAP)
can be seen at http://www.catalystgrp.com/php/tcgr_catalyticadvancesprogram.php.
Call +1-215-628-4447 or e-mail John J. Murphy at jmurphy@catalystgrp.com,
and we’ll be happy to discuss these and other interesting membership benefits.

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The Catalyst Group Resources (TCGR), a member of The Catalyst Group, is dedicated to monitoring and analyzing technical and commercial developments in catalysis as they apply to the global refining, petrochemical, fine/specialty chemical, pharmaceutical, polymer/elastomer and environmental industries.