Title of the PhD project: Machine learning exploration of dynamical processes in encapsulated single atom catalysts

Contact person and project supervisor: Christopher Heard Ph. D, heardc@natur.cuni.cz

Websites:
1
)https://chrisheardresearch.wordpress.com/,
2)
http://physchem.cz/research/nanomaterials-modeling/

Research group: Nanomaterials Modeling 

Leader of the research group: Prof. RNDr. Petr Nachtigall, PhD

Department: Physical and Macromolecular Chemistry

Project summary:
In this project you will develop and apply cutting edge computational simulation methods to understand the behaviour of zeolite-encapsulated single atom catalysts (SAC) at the atomistic scale. You will determine catalyst design principles that will inform the next generation of heterogeneous catalytic materials.

Single atom catalysts[1] supported by encapsulation into zeolite pores are highly efficient, cost-effective catalytic systems, used in a rapidly growing number of industrially important processes, from environmental protection to fuel upgrading.[2] However, we are only recently beginning to understand how these catalysts behave on an atomistic scale. The mechanisms of migration, growth and redispersion are so far not well understood. Neither are the effects of external conditions, such as temperature, humidity or age. This gap in understanding provides a great opportunity for ambitious researchers to develop of powerful computational methods to tackle the important issues in SACs. The ultimate goal is a set of design principles to optimise the stability and functionality of SACs in industry.

In our work, we are unravelling the mysteries of SAC-zeolite interactions via a combination of methods, including:

  1. Application of state-of-the-art global structure prediction approaches to predict the preferred locations and configurations of SACs in zeolite pores.[3]
  2. Development of kinetic modelling[4] and machine learning methods to enhance simulation scope and observe dynamic processes in real time. [5]
  3. Laboratory synthesis of SACs analysis via high-resolution election microscopy to test computational predictions for real catalytic materials.

This project will include the development of computational methods, in particular, neural network-based machine learning potentials and kinetic Monte Carlo codes. These methods will be applied towards long-time simulations and statistical analysis of SAC binding, growth and migration processes. The successful candidate will gain experience in programming, simulation methods, maintaining local and international collaborations, and presentation at international conferences. 

Features of a successful candidate:
MSc. or equivalent in Chemistry, Physics or Materials Science, good knowledge of English (required), research background in molecular modelling, computational chemistry or solid-state physics (preferred). Experience with high performance computing and programming in a Linux environment (beneficial). 

References:
[1]
Heterogeneous single-atom catalysis”, A. Wang, J. Li, and T. Zhang, (2018), Nature Reviews Chemistry, 2(6), 65–81.
[2a] Low Temperature NO Storage of Zeolite Supported Pd for Low Temperature Diesel Engine Emission Control”, H.-Y. ChenJ. E. CollierD. LiuL. MantarosieD. Durán-MartínV. NovákR. R. Rajaram and D. Thompsett, (2016), Catalysis Letters, 146, 1706–1711.
[2b] Recent advances in automotive catalysis for NOx emission control by small-pore microporous materials”, A. M. Beale, F. Gao, I. Lezcano-Gonzalez, C. H. F. Peden and J. Szanyi, (2015), Chem. Soc. Rev., 44, 7371–7405.
[3a] Origin of the Unusual Stability of Zeolite-Encapsulated Sub-Nanometer Platinum” D. Hou, L. Grajciar, P. Nachtigall and C. J. Heard, (2020), ACS Catalysis., 10, 11057–11068.
[3b] Fast room temperature lability of aluminosilicate zeolites“, C.J Heard, L. Grajciar, C.M. Rice, S.M. Pugh, P. Nachtigall, S.E. Ashbrook, R.E. Morris, (2019), Nature Communications, 10 (1), 1-7.
[4] “Kinetic regimes in ethylene hydrogenation over transition-metal surfaces” C.J Heard, C. Hu, M. Skoglundh, D. Creaser, H. Grönbeck, (2016), ACS Catalysis, 6(5), 3277-3286  
[5a]
Towards operando computational modeling in heterogeneous catalysis”, L. Grajciar, C. J. Heard, A.A. Bondarenko, M.V. Polynski, J. Meeprasert, E.A. Pidko, P. Nachtigall, (2018), Chemical Society Reviews, 47 (22), 8307-8348.
[5b] 2D oxide nanomaterials to address the energy transition and catalysis”, C.J. Heard, J. Čejka, M. Opanasenko, P. Nachtigall, G. Centi, S. Perathoner, (2018), Advanced Materials, 31 (3), 1801712.

Current research grant of the project leader:
GACR grant 20-26767Y: “Stability of Metal Particles Encapsulated in Zeolites: Multiscale Modelling and Experimental Benchmarking” (two postdocs and two PhD students) 2020-2022. Total budget approx.€ 250.000.


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