Bacchini, F., L. Arzamasskiy, V. Zhdankin, G. R. Werner, M. C. Begelman, and D. A. Uzdensky, "Fully Kinetic Shearing-Box Simulations of Magnetorotational Turbulence in 2D and 3D. I. Pair Plasmas," The Astrophysical Journal (October 2022), IOP Publishing. doi: 10.3847/1538-4357/ac8a94

Zhang, Z., Z. Wei, P. Sautet, and A. N. Alexandrova, "Hydrogen-Induced Restructuring of a Cu(100) Electrode in Electroreduction Conditions," Journal of the American Chemical Society (October 2022), ACS Publications. doi: 10.1021/jacs.2c06188

Chang, W. H. R., "The Dynamics of Drop Breakup in Breaking Waves," Proceedings of the 34th Symposium on Naval Hydrodynamics (October 2022), Washington, DC, The George Washington University

Lee, G., I. Hong, J. Ahn, H. Shin, A. Benali, and Y. Kwon, "Hydrogen Separation with a Graphenylene Monolayer: Diffusion Monte Carlo Study," The Journal of Chemical Physics (October 2022), AIP. doi: 10.1063/5.0116092

Garland, N. A., R. Maulik, Q. Tang, X.-Z. Tang, and P. Balaprakash, "Efficient Data Acquisition and Training of Collisional-Radiative Model Artificial Neural Network Surrogates through Adaptive Parameter Space Sampling," Machine Learning: Science and Technology (October 2022), IOP Publishing. doi: 10.1088/2632-2153/ac93e7

Chitty-Venkata, K. T., M. Emani, V. Vishwanath, and A. K. Somani, "Neural Architecture Search for Transformers: A Survey," IEEE Access (October 2022), IEEE. doi: 10.1109/ACCESS.2022.3212767

Sankaran, S., H. Wang, L. F. Guilhoto, and P. Perdikaris, "On the Impact of Larger Batch Size in the Training of Physics Informed Neural Networks ," The Symbiosis of Deep Learning and Differential Equations II (October 2022), NeurIPS

Deematties, D., S. Rizzi, G. K. Thiruvathukal, and A. Wainselboim, "Towards an Active Foveated Approach to Computer Vision," Computación y Sistemas (October 2022), vol. 26, no. 4, Instituto Politécnico Nacional

Campos, L., D. Jiménez, S. H. Rizzi, and E. Meneses, "An Evaluation of a Ray-Tracing Based Model for Photorealistic Image Rendering of Confined Plasma in Stellarators," Computación y Sistemas (October 2022), vol. 26, no. 4, Instituto Politécnico Nacional

Kaur, S., R. Kanungo, W. Horiuchi, G. Hagen, J. D. Holt, B. S. Hu, T. Miyagi, T. Suzuki, F. Ameil, J. Atkinson, Y. Ayyad, S. Bagchi, D. Cortina-Gil, I. Dillmann, A. Estradé, A. Evdokimov, F. Farinon, H. Geissel, G. Guastalla, R. Janik, R. Knöbel, J. Kurcewicz, Y. A. Litvinov, M. Marta, M. Mostazo, I. Mukha, C. Nociforo, H. J. Ong, T. Otsuka, S. Pietri, A. Prochazka, C. Sceidenberger, B. Sitar, P. Strmen, M. Takechi, J. Tanaka, I. Tanihata, S. Terashima, J. Vargas, H. Weick, and J. S. Winfield, "Proton Distribution Radii of 16–24O: Signatures of New Shell Closures and Neutron Skin," Physical Review Letters (September 2022), APS. doi: 10.1103/PhysRevLett.129.142502

Kononov, A., C.-W. Lee, T. P. dos Santos, B. Robinson, Y. Yao, Y. Yao, X. Andrade, A. D. Baczewski, E. Constantinescu, A. A. Correa, Y. Kanai, N. Modine, and A. Schleife, "Electron Dynamics in Extended Systems within Real-Time Time-Dependent Density-Functional Theory," Computational Approaches for Materials Discovery and Development Perspective (September 2022), Springer Nature. doi: 10.1557/s43579-022-00273-7

Gautham, S. M. B., T. K. Patra, "Deep Learning Potential of Mean Force Between Polymer Grafted Nanoparticles," Soft Matter (September 2022), The Royal Society of Chemistry. doi: 10.1039/d2sm00945e

Mulligan, V. K., "Computational Methods for Peptide Macrocycle Drug Design," Peptide Therapeutics: Fundamentals of Design, Development, and Delivery (September 2022), Springer Nature, pp. 79-161, . doi: 10.1007/978-3-031-04544-8_3

Huang, S., and J. M. Cole, "BatteryDataExtractor: Battery-Aware Text-Mining Software Embedded with BERT Models," Chemical Science (September 2022), Royal Society of Chemistry. doi: 10.1039/d2sc04322j

Fletcher, G. D., C. Bertoni, M. Keceli, and M. J. D'Mello, "Prediction of Correlation Energies Using Variational Subspace Valence Bond," The Journal of Chemical Physics (September 2022), AIP. doi: 10.1063/5.0098146

Wang, T., D. Vartanyan, A. Burrows, and M. S. B. Coleman, "The Essential Character of the Neutrino Mechanism of Core-Collapse Supernova Explosions," Monthly Notices of the Royal Astronomical Society (September 2022), Oxford University Publishing. doi: 10.1093/mnras/stac2691

Wu, S., S. Patel, and M. Ameen, "Investigation of Cycle-to-Cycle Variations in Internal Combustion Engine Using Proper Orthogonal Decomposition," Flow, Turbulence and Combustion (September 2022), Springer Nature. doi: 10.1007/s10494-022-00368-0

Zacharoudiou, I., J. W. S. McCullough, and P. V. Coveney, "Development and Performance of a HemeLB GPU Code for Human-Scale Blood Flow Simulation," Computer Physics Communications (September 2022), Elsevier. doi: 10.1016/j.cpc.2022.108548

Tsant, B. T.-H., D. Vartanyan, and A. Burrows, "Applications of Machine Learning to Predicting Core-Collapse Supernova Explosion Outcomes," The Astrophysical Journal Letters (September 2022), IOP Publishing. doi: 10.3847/2041-8213/ac8f4b

Li, Z., R. Chard, Y. Babuji, B. Galewsky, T. J. Skluzacek, K. Nagaitsev, A. Woodard, B. Blaiszik, J. Bryan, D. S. Katz, I. Foster, and K. Chard, "funcX: Federated Function as a Service for Science," IEEE Transactions on Parallel and Distributed Systems (September 2022), IEEE. doi: 10.1109/TPDS.2022.3208767