Christopher J. Knight

Key research interests include the advancement of molecular simulations and understanding scientific application performance on future computational resources.

Chris is currently team lead for chemistry and materials science in the Computational Science Division (CPS) and the Argonne Leadership Computing Facility (ALCF). Chris helps to develop new cross-cutting collaborations involving others in CPS and CELS, across Argonne, and other institutions to help address some of the most challenging scientific problems through advanced computing and simulation. One focus of Chris’ efforts today is helping teams leverage the Aurora exascale system in support of BES Computational Chemical Sciences and Microelectronics projects.

As a member of the ALCF Catalyst team, Chris works closely with researchers to help them accomplish their scientific goals using leadership computational resources. Chris assists researchers with profiling and debugging their codes, provides general guidance on code parallelization, I/O, load-balancing, workflow design, and data management, and discusses strategies to prepare for future architectures. Important components of this effort include training users on high-performance computing topics and collaborating with researchers to advance their scientific mission.

Chris was lead for Applications Integration on Aurora for the Exascale Computing Project (ECP) coordinating ALCF’s engagement and support of the ECP Application Development and Software Technology teams. This project supported a team of staff and postdocs at Argonne that served as the interface between software developers and vendors and provided critical support developing software for the Aurora exascale system.

Research Interests

• High-performance scientific computing & performance projections
• Statistical Mechanics
• Computer simulations via first principle methods (KS- and OF-DFT)
• Condensed phase simulations: classical and quantum dynamics, multiscale processes, accurate and efficient simulation of chemical reactions
• Chemistry at interfaces: aqueous systems, batteries and supercapacitors, fuel cells, biofuels, smart materials, and nanoporous materials
• Interactions of matter with soft and hard x-rays

Recent Awards

• DOE Secretary’s Honor Award - Exascale Computing Project Team, January 2025.
• Impact Argonne Award for Program Development efforts by building relationships and collaborations across the Laboratory, November 2022.
• Impact Argonne Team Award in support of successful acceptance of the Polaris system, May 2022.
• Impact Argonne Team Award in support of a successful Independent Project Review (IPR) for Aurora, September 2020.
• ANL Pacesetter Award with Vitali Morozov and Scott Parker, June 2017: ​“For extradordinary effort in early testing of the Intel Xeon Phi Knights Landing chip, porting several science applications of interest to LCF to the new platform, and documenting best practices and lessons learned to benefit the entire LCF user community.” ​“Their efforts contributed to an early installation and quick acceptance of Theta.”

Recent Publications

• Valay Agarawal, Rishu Khurana, Cong Liu, Matthew R. Hermes, Christopher Knight, and Laura Gagliardi, ​“Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units” J. Chem. Theory Comput., 21, 7378 (2025).
• Shreya Gupta, Ethan F. Bull-Vulpe, Henry Agnew, Shishir Iyer, Zuanyu Zhu, Ruihan Zhou, Christopher Knight, Francesco Paesani, ​“MBX v1.2: Accelerating Data-Driven Many-Body Molecular Dynamics Simulations” J. Chem. Theory Comput., 21, 1838 (2025).
• Zhao Li, Kaihang Shi, David Dubbeldam, Mark Dewing, Christopher Knight, Alvaro Vazquez Mayagoitia, and Randall Snurr, ​“Efficient Implementation of Monte Carlo Algorithms on Graphical Processing Units for Simulations of Adsorption in Porous Materials” J. Chem. Theory Comput., 20, 10649 (2024).
• Jingyi L. Chen, Jess L. Prelesnik, Buyun Liang, Yangzesheng Sun, Mrugank Bhatt, Christopher Knight, Krishnan Mahesh, and J. Ilja Siepmann, ​“Large-scale molecular dynamics simulations of bubble collapse in water: Effects of system size, water model, and nitrogen”, J. Chem. Phys., 159, 224505 (2023).
• Marc Riera, Christopher Knight, Ethan Bull-Vulpe, Xuanyu Zhu, Henry A. Agnew, Daniel G.A. Smith, Andrew C. Simmonett, and Francesco Paesani, ​“MBX: A many-body energy and force calculator for data-driven many-body simulations”, J. Chem. Phys. 159, 054802 (2023).