JANUARY

Andreoli, L., J. Carlson, A. Lovato, S. Pastore, N. Rocco, and R. B. Wiringa. “Electron Scattering on A=3 Nuclei from Quantum Monte Carlo Based Approaches,” Physical Review C (January 2022), APS. doi: 10.1103/physrevc.105.014002

Ashwin Renganathan, S., R. Maulik, S. Letizia, and G. Valerio Iungo. “Data-Driven Wind Turbine Wake Modeling via Probabilistic Machine Learning,” Neural Computing and Applications (January 2022), Springer Nature. doi: 10.1007/s00521-021-06799-6

Bayerl, B., C. M., Andolina ,S. Dwaraknath, and W. A. Saidi. “Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations,” Digital Discovery (January 2022), no. 1, Royal Society of Chemistry, pp. 61-69. doi: 10.1039/d1dd00005e

Berres, A. S., B. C. Bass, M. B. Adams, E. Garrison, and J. R. New. “A Data-Driven Approach to Nation-Scale Building Energy Modeling,” 2021 IEEE International Conference on Big Data (Big Data) (January 2022), Orlando, FL, IEEE. doi: 10.1109/BigData52589.2021.9671786

Bosilca, G., A. Bouteiller, T. Herault, V. Le Févre, Y. Robert, and J. Dongarra. “Comparing Distributed Termination Detection Algorithms for Modern HPC Platforms,” International Journal of Networking and Computing (January 2022), vol. 12, no. 1, International Journal of Networking and Computing. doi: 10.15803/ijnc.12.1_26

Chidyagwaia, S. G., M. Vardhana, M. Kapland, R. Chamberlain, P. Barker, and A. Randles. “Characterization of Hemodynamics in Anomalous Aortic Origin of Coronary Arteries Using Patient-Specific Modeling,” Journal of Biomechanics (January 2022), Elsevier. doi: 10.1016/j.jbiomech.2021.110919

Clyde, A., S. Galanie, D.W. Kneller, H. Ma, Y Babuji, B Blaiszik, A. Brace, T. Brettin, K. Chard, R. Chard, L. Coates, I. Foster, D. Hauner, V. Kertesz, N. Kumar, H. Lee, Z. Li, A. Merzky, J.G. Schmidt, L. Tan, M. Titov, A. Trifan, M. Turilli, H. Van Dam, S.C. Chennubhotla, S. Jha, A. Kovalevsky, A. Ramanathan, M.S. Head, and R. Stevens. “High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor,” Journal of Chemical Information and Modeling (January 2022), ACS. doi: 10.1021/acs.jcim.1c00851

Drobchik, A. N., V. V. Nikitin, M. I. Fokin, G. A. Dugarov, A. L. Shevchenko, A. L. Deriy, A. Y. Manikov, K. E. Kuper, and A.A. Duchtov. “Environmental Cell for In Situ X-ray Synchrotron Micro-CT Imaging with Simultaneous Acoustic Measurements,” Journal of Synchrotron Radiation (January 2022), International Union of Crystallography. doi: 10.1107/s1600577521013308

Feldman, C., B. Michalowicz, E. Siegmann, T. Curtis, A. Calder, and R. Harrison. “Experiences with Porting the FLASH Code to Ookami, an HPE Apollo 80 A64FX Platform,” HPCAsia 2022 Workshop: International Conference on High Performance Computing in Asia-Pacific Region Workshops (January 2022), ACM. doi: 10.1145/3503470.3503478

Khan, A., E. A. Huerta, and H. Zheng. “Interpretable AI Forecasting for Numerical Relativity Waveforms of Quasicircular, Spinning, Nonprocessing Binary Black Hole Mergers,” Physical Review D (January 2022), APS. doi: 10.1103/PhysRevD.105.024024

Liu, Z., H. Sharma, J.-S. Park, P. Kenesei, A. Miceli, J. Almer, R. Kettimuthu,and I. Foster. “BraggNN: Fast X-ray Bragg Peak Analysis Using Deep Learning,” IUCrJ (January 2022), vol. 9, no. 1, International Union of Crystallography, pp. 104-113. doi: 10.1107/S2052252521011258

Malbrunot-Ettenauer, S., S. Kaufmann, S. Bacca, C. Barbieri, J. Billowes, M. L. Bissell, K. Blaum, B. Cheal, T. Duguet, R. F. Garcia Ruiz, W. Gins, C. Gorges, G. Hagen, H. Heylen, J. D. Holt, G. R. Jansen, A. Kanellakopoulos, M. Kortelainen, T. Miyagi, P. Navrátil, W. Nazarewicz, R. Neugart, G. Neyens, W. Nörtershäuser, S. J. Novario, T. Papenbrock, T. Ratajczyk, P.-G. Reinhard, L. V. Rodríguez, R. Sánchez, S. Sailer, A. Schwenk, J. Simonis, V. Somà, S. R. Stroberg, L. Wehner, C. Wraith, L. Xie, Z. Y. Xu, X. F. Yang, and D. T. Yordanov. “Nuclear Charge Radii of the Nickel Isotopes ^58−68,70Ni,” Physical Review Letters (January 2022), APS. doi: 10.1103/PhysRevLett.128.022502

Manna, S., T. D. Loeffler, R. Batra, S. Banik, H. Chan, B. Varughese, K. Sasikumar, M. Sternberg, T. Peterka, M. J. Cherukara, S. K. Gray, B. G. Sumpter, and S. K. R. S. Sankaranarayanan. “Learning in Continuous Action Space for Developing High Dimensional Potential Energy Models,” Nature Communications (January 2022), Springer Nature. doi: 10.1038/s41467-021-27849-6

Posner, J., L. Reitz, and C. Fohry. “Task-Level Resilience: Checkpointing vs. Supervision,” International Journal of Networking and Computing (January 2022), vol. 12, no. 1, International Journal of Networking and Computing, pp. 47-72. doi: 10.15803/ijnc.12.1_47

Saidi, W. A. “Optimizing the Catalytic Activity of Pd-Based Multinary Alloys toward Oxygen Reduction Reaction,” The Journal of Physical Chemistry Letters (January 2022), vol. 13, ACS Publications. doi: 10.1021/acs.jpclett.1c04128

Schwartz, J., Z. W. Di, Y. Jiang, A. J. Fielitz, D.-H. Ha, S. D. Perera, I. El Baggari, R. D. Robinson, J. A. Fessler, C. Ophus, S. Rozeveld, and R. Hovden. “Imaging Atomic-Scale Chemistry from Fused Multi-Modal Electron Microscopy,” npj Computational Materials (January 2022), Springer Nature. doi: 10.1038/s41524-021-00692-5

Sudharsan, S., B. Ganapathysubramanian, and A. Sharma. “A Vorticity-Based Criterion to Characterise Leading Edge Dynamic Stall Onset,” Journal of Fluid Mechanics (January 2022), Cambridge University Press. doi: 10.1017/jfm.2021.1149

Vorabbi, M., M. Gennari, P. Finelli, C. Giusti, P. Navrátil, and R. Machleidt. “Elastic Proton Scattering Off Nonzero Spin Nuclei,” Physical Review C (January 2022), APS. doi: 10.1103/PhysRevC.105.014621

Xie, Z., S. Raskar, and M. Emani. “Throughput-Oriented and Accuracy-Aware DNN Training with BFloat16 on GPU,” 4th IEEE International Parallel and Distributed Processing Symposium Workshop on Scalable Deep Learning over Parallel and Distributed Infrastructure (January 2022), Lyons, France, IEEE. doi: 10.1109/IPDPSW55747.2022.00176

Xu, H., A. Berres, S. Yoginath, K. Kurte, R. Peleti, J. R. New, and J. Sanyal. “Towards Adaptive Decision Support: A Perspective from Intelligent and Annotated Visual Analytics for Exploring Big Urban Mobility Data,” ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication (January 2022), U.S. Department of Energy. doi: 10.2172/1843572

Ye, Z., C. Zhang, and G. Galli. “Photoelectron Spectra of Water and Simple Aqueous Solutions at Extreme Conditions,” Faraday Discussions (January 2022), Royal Society of Chemistry. doi: 10.1039/D2FD00003B

FEBRUARY

Appelquist, T., R. C. Brower, K. K. Cushman, G. T. Fleming, A. Gasbarro, A. Hasenfratz, J. Ingoldby, X. Y. Jin, E. T. Neil, J. C. Osborn, C. Rebbi, E. Rinaldi, D. Schaich, P. Vranas, E. Weinberg, and O. Witzel. “Goldstone Boson Scattering with a Light Composite Scalar,” Physical Review D (February 2022), APS. doi: 10.1103/physrevd.105.034505

Burrows, A., and M. Coleman. “The Character of Three-Dimensional Core-Collapse Simulation Results,” The 16th International Symposium on Nuclei in the Cosmos (February 2022), Chengdu, China, EPJ Web Conferences. doi: 10.1051/epjconf 202226007001

Chaturvedi, P., A. Khan, M. Tian, E. A. Huerta, and H. Zheng. “Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale,” Frontiers in Artificial Intelligence (February 2022), Frontiers Media SA. doi: 10.3389/frai.2022.828672

Elhatisari, S., T. A. Lähde, D. Lee, U.-G. Meißner, and T. Vonk . “Alpha-Alpha Scattering in the Multiverse,” Journal of High Energy Physics (February 2022), Springer Nature. doi: 10.1007/JHEP02

Frontiere, N., K. Heitmann, E. Rangel, P. Larsen, A. Pope, I. Sultan, T. Uram, S. Habib, S. Rizzi, J. Insley, and The HACC Collaboration. “Farpoint: A High-Resolution Cosmology Simulation at the Gigaparsec Scale,” The Astrophysical Journal (February 2022), IOP Publishing. doi: 10.3847/1538-4365/ac43b9

Guo, J., Ward, L., Babuji, Y., Hoyt, N., Williamson, M., Foster, I., Jackson, N., Benmore, C. and Sivarman, G. “A Composition-Transferable Machine Learning Potential for LiCl-KCl Molten Salts Validated by HEXRD,” ChemRxiv (February 2022), Cambridge University Press. doi: 10.26434/chemrxiv-2022-8w9ft

Huang, B., C. González-Zacarías, S. S. Güitrón, A. Aslam, S. G. Biedron, K. Bronw, and T. Bolin. “Artificial Intelligence-Assisted Design and Virtual Diagnostic for the Initial Condition of a Storage-Ring-Based Quantum Information System,” IEEE Access (February 2022), IEEE. doi: 10.1109/ACCESS.2022.3147727

Impagnatiello, M., M. Bolla, K. Keskinen, G. Giannakopoulos, C. E. Frouzakis, Y. M. Wright, and K. Boulochos. “Systematic Assessment of Data-Driven Approaches for Wall Heat Transfer Modelling for LES in IC Engines Using DNS Data,” International Journal of Heat and Mass Transfer (February 2022), vol. 183, no. B, Elsevier. doi: 10.1016/j.ijheatmasstransfer.2021.122109

Kortelainen, M., Z. Sun, G. Hagen, W. Nazarewicz, T. Papenbrock, and P.-G. Reinhard. “Universal Trend of Charge Radii of Even-Even Ca–Zn Nuclei,” Physical Review C (February 2022), APS. doi: 10.1103/PhysRevC.105.L021303

Larsson, J., V. Kumar, N. Oberoi, M. Di Renzo, and S. Pirozzoli. “Large-Eddy Simulations of Idealized Shock/Boundary-Layer Interactions with Crossflow,” AIAA Journal (February 2022), AIAA. doi: 10.2514/1.J061060

Shepard, C., and Y. Kanai. “Nonlinear Electronic Excitation in Water under Proton Irradiation: A First Principles Study,” Physical Chemistry Chemical Physics (February 2022), Royal Society of Chemistry. doi: 10.1039/D1CP05313B

Thompson, A. P., H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in ‘t Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. “LAMMPS - A Flexible Simulation Tool for Particle-Based Materials Modeling at the Atomic, Meso, and Continuum Scales,” Computer Physics Communications (February 2022), Elsevier. doi: 10.1016/j.cpc.2021.108171

Tiihonen, J., P. R. C. Kent, and J. T. Krogel. “Surrogate Hessian Accelerated Structural Optimization for Stochastic Electronic Structure Theories,” The Journal of Chemical Physics (February 2022), AIP. doi: 10.1063/5.0079046

Wan, S., B. Agastya, D. Wright, I. Wall, A. Graves, D. Green, and P. Coveney. “Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors Inhibitors,” ChemRxiv (February 2022), Cambridge University Press. doi: 10.26434/chemrxiv-2022-hrxqs

White, C. J., A. Burrows, M. S. B. Coleman, and D. Vartanyan. “On the Origin of Pulsar and Magnetar Magnetic Fields,” The Astrophysical Journal (February 2022), IOP Publishing. doi: 10.3847/1538-4357/ac4507

MARCH

Bhati, A. P., and P. V. Coveney. “Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols,” Journal of Chemical Theory and Computation (March 2022), ACS. doi: 10.1021/acs.jctc.1c01288

Bicer, T., X. Yu, D.J. Ching, and R. Chard. “High-Performance Ptychographic Reconstruction with Federated Facilities,” SMC 2021: Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation (March 2022), Springer Nature. doi: 10.1007/978-3-030-96498-6_10

Bonaiti, F., S. Bacca, and G. Hagen. “Ab Initio Coupled-Cluster Calculations of Ground and Dipole Excited States in ⁸He,” Physical Review C (March 2022), APS. doi: 10.1103/PhysRevC.105.034313

Guttenfelder, W., D. J. Battaglia, E. Belova, N. Bertelli, M. D. Boyer, C. S. Chang, A. Diallo, V. N. Duarte, F. Ebrahimi, E. D. Emdee, N. Ferraro, E. Fredrickson, N. N. Gorelenkov, W. Heidbrink, Z. Ilhan, S. M. Kaye, E.-H. Kim, A. Kleiner, F. Laggner, M. Lampert, J. B. Lestz, C. Liu, D. Liu, T. Looby, N. Mandell, R. Maingi, J. R. Myra, S. Munaretto, M. Podestà, T. Rafiq, R. Raman, M. Reinke, Y. Ren, J. Ruiz Ruiz, F. Scotti, S. Shiraiwa, V. Soukhanovskii, P. Vail, Z. R. Wang, W. Wehner, A. E. White, R. B. White, B. J. Q. Woods, J. Yang, S. J. Zweben, S. Banerjee, R. Barchfeld, R. E. Bell, J. W. Berkery, A. Bhattacharjee, A. Bierwage, G. P. Canal, X. Chen, C. Clauser, N. Crocker, C. Domier, T. Evans, M. Francisquez, K. Gan, S. Gerhardt, R. J. Goldston, T. Gray, A. Hakim, G. Hammett, S. Jardin, R. Kaita, B. Koel, E. Kolemen, S.-H. Ku, S. Kubota, B. P. LeBlanc, F. Levinton, J. D. Lore, N. Luhmann, R. Lunsford, R. Maqueda, J. E. Menard, J. H. Nichols, M. Ono, J.-K. Park, F. Poli, T. Rhodes, J. Riquezes, D. Russell, S. A. Sabbagh, E. Schuster, D. R. Smith, D. Stotler, B. Stratton, K. Tritz, W. Wang, and B. Wirth. “NSTX-U Theory, Modeling and Analysis Results,” Nuclear Fusion (March 2022), IOP Publishing. doi: 10.1088/1741-4326/ac5448

Huang, B., M. Govoni, and G. Galli. “Simulating the Electronic Structure of Spin Defects on Quantum Computers,” PRX Quantum (March 2022), APS. doi: 10.1103/prxquantum.3.010339

Li, B., C. Feng, C. Siebenschuh, R. Zhang, E. Spyrou, V. Krishnan, B. F. Hobbs, and J. Zhang. “Sizing Ramping Reserve Using Probabilistic Solar Forecasts: A Data-Driven Method,” Applied Energy (March 2022), Elsevier. doi: 10.1016/j.apenergy.2022.118812

Linker, T., K.-I. Nomura, A. Aditya, S. Fukshima, R. K. Kalia, A. Krishnamoorthy, A. Nakano, P. Rajak, K. Shimmura, F. Shimojo, and P. Vashishta. “Exploring Far-from-Equilibrium Ultrafast Polarization Control in Ferroelectric Oxides with Excited-State Neural Network Quantum Molecular Dynamics,” Science Advances (March 2022), AAAS. doi: 10.1126/sciadv.abk2625

Lu, Y., R., Maulik, T. Gao, F. Dietrich, I. G. Kevrekidis, and J. Duan. “Learning the Temporal Evolution of Multivariate Densities via Normalizing Flows,” Chaos: An Interdisciplinary Journal of Nonlinear Science (March 2022), AIP Publishing. doi: 10.1063/5.0065093

Ohayon, B., R. F. Garcia Ruiz, Z. H. Sun, G. Hagen, T. Papenbrock, and B. K. Sahoo. “Nuclear Charge Radii of Na Isotopes: Interplay of Atomic and Nuclear Theory,” Physical Review C (March 2022), APS. doi: 10.1103/PhysRevC.105.L031305

Pauloski, J. G., L. Huang, W. Xu, K. Chard, I. T. Foster, and Z. Zhang. “Deep Neural Network Training with Distributed K-FAC,” IEEE Transactions on Parallel and Distributed Systems (March 2022), IEEE. doi: 10.1109/TPDS.2022.3161187

Pefkou, D. A., D. C. Hackett, and P. E. Shanahan. “Gluon Gravitational Structure of Hadrons of Different Spin,” Physical Review D (March 2022), APS. doi: 10.1103/physrevd.105.054509

Preinm, A. F., M. Ge, A. N. Ramos-Valle, D. Wang, and S. E. Giangrande. “Towards a Unified Setup to Simulate Mid-Latitude and Tropical Mesoscale Convective Systems at Kilometer-Scales,” ESS Open Archive (March 2022), ESS Open Archive. doi: 10.1002/essoar.10510881.1

Yang. L, R. Hu, A. Kraus, P. Balaprakash, and A. Obabko. “Data-Driven Modeling of Coarse Mesh Turbulence for Reactor Transient Analysis Using Convolutional Recurrent Neural Networks,” Nuclear Engineering and Design (March 2022), Elsevier. doi: 10.1016/j.nucengdes.2022.111716

Zhu, M., and J. M. Cole. “PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format,” Journal of Chemical Information and Modeling (March 2022), ACS. doi: 10.1021/acs.jcim.1c01198

APRIL

Bale, A. A., S. M. B. Gautham, and T. K. Patra. “Sequence-Defined Pareto Frontier of a Copolymer Structure,” Journal of Polymer Science (April 2022), John Wiley and Sons. doi: 10.1002/pol.20220088

Bollweg, D., O. Kaczmarek, F. Karsch, S. Mukherjee, P. Petreczky, C. Schmidt, and P. Scior. “Taylor Expansions and Padé Approximants For Cumulants of Conserved Charge Fluctuations at Nonvanishing Chemical Potentials,” Physical Review D (April 2022), APS. doi: 10.1103/physrevd.105.074511

Cho, Y., S. Kang, B. C. Wood, and E. S. Cho. “Heteroatom-Doped Graphenes as Actively Interacting 2D Encapsulation Media for Mg-Based Hydrogen Storage,” ACS Applied Materials and Interfaces (April 2022), ACS. doi: 10.1021/acsami.1c23837

Dumi, A., S. Upadhyay, L. Bernasconi, H. Shin, A. Benali, and K. D. Jordan. “The Binding of Atomic Hydrogen on Graphene from Density Functional Theory and Diffusion Monte Carlo Calculations,” The Journal of Chemical Physics (April 2022), AIP. doi: 10.1063/5.0085982

Huang, J., L. Duan, and M. M. Choudhari. “Direct Numerical Simulation of Hypersonic Turbulent Boundary Layers: Effect of Spatial Evolution and Reynolds Number,” Journal of Fluid Mechanics (April 2022), vol. 937, Cambridge University Press. doi: 10.1017/jfm.2022.80

Kahraman, A. B., and J. Larsson. “Adaptive Determination of the Optimal Exchange Location in Wall-Modeled Large-Eddy Simulation,” AIAA Journal (April 2022), AIAA. doi: 10.2514/1.J061347

King, G. B., S. Pastore, M. Piarulli, and R. Schiavilla. “Partial Muon Capture Rates in A=3 and A=6 Nuclei with Chiral Effective Field Theory,” Physical Review C (April 2022), APS. doi: 10.1103/PhysRevC.105.L042501

Liu, X., X. Wang, S. Gao, V.Chang, R. Tom, M.Yu, L. Ghiringhelli, and N. Marom. “Finding Predictive Models for Singlet Fission by Machine Learning,” npj Computational Materials (April 2022), Springer Nature. doi: 10.1038/s41524-022-00758-y

Lungo, G. V., R. Maulik, S. A. Renganathan, and S. Letizia. “Machine-Learning Identification of the Variability of Mean Velocity and Turbulence Intensity for Wakes Generated by Onshore Wind Turbines: Cluster Analysis of Wind Lidar Measurements,” Journal of Renewable and Sustainable Energy (April 2022), vol. 14, no. 2, AIP. doi: 10.1063/5.0070094

Ostalowski, K., and J. Tan. “Direct Simulation of Blood Flow with Heterogeneous Cell Suspensions in a Patient-Specific Capillary Network,” Physics of Fluids (April 2022), AIP. doi: 10.1063/5.0088342

Pirayeshshirazinezhad, R., S. G. Biedron, J. A. Diaz-Cruz, S. Sosa Güitrón, and M. Martinez-Ramon. “Designing Monte Carlo Simulation and an Optimal Machine Learning to Optimize and Model Space Missions,” IEEE Access (April 2022), IEEE. doi: 10.1109/access.2022.3170438

Saidi, W.A. “Emergence of Local Scaling Relations in Absorption Energies on High-Entropy Alloy,” npj Computational Materials (April 2022), Springer Nature. doi: 10.1038/s41524-022-00766-y

Trott, C. R., D. Lebrun-Grandie, D. Arndt, J. Ciesko, V. Dang, N. Ellingwood, R. Gayatri, E. Harvey, D. Hollman, D. Ibanez, N. Liber, J. Madsen, J. Miles, D. Poliakoff, A. Powell, S. Rajamanickam, M. Simberg, D. Sunderland, B. Turcksin, and J. Wilke. “Kokkos 3: Programming Model Extensions for the Exascale Era,” IEEE Transactions on Parallel and Distributed Systems (April 2022), vol. 33, no. 4, IEEE, pp. 805-817. doi: 10.1109/TPDS.2021.3097283

MAY

Atkinson, M. C., P. Navrátil, G. Hupin, K. Kravvaris, and S. Quaglioni. “Ab Initio Calculation of the β Decay from ¹¹Be to a ¹⁰Be + p Resonance,” Physical Review C (May 2022), APS. doi: 10.1103/PhysRevC.105.054316

Bethel, E. W., B. Loring, U. Ayachit, D. Camp, E. P. N. Duque, N. Ferrier, J. Insley, J. Gu, J. Kress, P. O’Leary, D. Pugmire, S. Rizzi, D. Thompson, G. H. Weber, B. Whitlock, M. Wolf, and K. Wu. “The SENSEI Generic In Situ Interface: Tool and Processing Portability at Scale,” In Situ Visualization for Computational Science (May 2022), Springer Nature, pp. 281-306. doi: 10.1007/978-3-030-81627-8_13

Bethel, E. W., B. Loring, U. Ayachit, E. P. N. Duque, N. Ferrier, J. Insley, J. Gu, J. Kress, P. O’Leary, D. Pugmire, S. Rizzi, D. Thompson, W. Usher, G. H. Weber, B. Whitlock, M. Wolf, and K. Wu. “Proximity Portability and in Transit, M-to-N Data Partitioning and Movement in SENSEI,” In Situ Visualization for Computational Science (May 2022), Springer Nature, pp. 439-460. doi: 10.1007/978-3-030-81627-8_20

Cossairt, A., M. Buehlmann, E. Kovacs, X. Liu, S. Habib, and K. Heitmann. “Cosmo-Paleontology: Statistics of Fossil Groups in a Gravity-Only Simulation,” The Open Journal of Astrophysics (May 2022), Maynooth Academic Publishing. doi: 10.21105/astro.2203.08768

Gamelin, B. L., J. Feinstein, J. Wang, J. Bessac, E. Yan, and V. R. Kotamarthi. “Projected U.S. Drought Extremes through the Twenty-First Century with Vapor Pressure Deficit,” Scientific Reports (May 2022), Springer Nature. doi: 10.1038/s41598-022-12516-7

Gensini, V., A. M. Haberlie, and W. S. Ashley. “Convection-Permitting Simulations of Historical and Possible Future Climate over the Contiguous United States,” Climate Dynamics (May 2022), Springer Nature. doi: 10.1007/s00382-022-06306-0

Gerasimeniuk, N.V., M. N. Chernodub, V. A. Goy, D. L. Boyda, S. D. Liubimov, A. V. Molochkov. “Applying Machine Learning Methods to Prediction Problems of Lattice Observables,” SciPost Physics Proceedings (May 2022), SciPost Foundation. doi: 10.21468/scipostphysproc.6.020

Huang, S., and J. M. Cole. “BatteryBERT: A Pretrained Language Model for Battery Database Enhancement,” Journal of Chemical Information and Modeling (May 2022), ACS Publications. doi: 10.1021/acs.jcim.2c00035

Jain, S. S., and P. Moin. “A Kinetic Energy- and Entropy-Preserving Scheme for Compressible Two-Phase Flows,” Journal of Computational Physics (May 2022), Elsevier. doi: 10.1016/j.jcp.2022.111307

Maulik, R., V. Rao, J. Wang, G. Mengaldo, E. Constantinescu, B. Lusch, P. Balaprakash, I. Foster, and R. Kotamarthi. “Efficient High-Dimensional Variational Data Assimilation with Machine-Learned Reduced-Order Models,” Geoscientific Model Development (May 2022), European Geosciences Union. doi: 10.5194/gmd-15-3433-2022

Miller, D., V. A. Gensini, and B. S. Barrett. “Madden-Julian Oscillation Influences United States Springtime Tornado and Hail Frequency,” npj Climate and Atmospheric Sciences (May 2022), Springer Nature. doi: 10.1038/s41612-022-00263-5

Peterka, T., Y. Nashed, I. Grindeanu, V. Mahadevan, R. Yeh, and D. Lenz. “Multivariate Functional Approximation of Scientific Data,” In Situ Visualization for Computational Science (May 2022), Springer Nature, pp. 375-397. doi: 10.1007/978-3-030-81627-8_17

Sivaraman, G., G. Csanyi, A. Vazquez-Mayagoitia, I. T. Foster, S. K. Wilke, R. Weber, and C. J. Benmore. “A Combined Machine Learning and High-Energy X-ray Diffraction Approach to Understanding Liquid and Amorphous Metal Oxides,” Journal of the Physical Society of Japan (May 2022), The Physical Society of Japan. doi: 10.7566/JPSJ.91.091009

Usher, W., H. Park, M. Lee, P. Navrátil, D. Fussell, and V. Pascucci. “A Simulation-Oblivious Data Transport Model for Flexible In Transit Visualization,” In Situ Visualization for Computational Science (May 2022), Springer Nature, pp. 399-419. doi: 10.1007/978-3-030-81627-8_18

Verma, G., S. Finviya, A. M. Malik, M. Emani, and B. Chapman. “Towards Neural Architecture-Aware Exploration of Compiler Optimizations in a Deep Learning {Graph} Compiler,” CF ‘22: Proceedings of the 19th ACM International Conference on Computing Frontiers (May 2022), Turin, Italy, Association for Computing Machinery. doi: 10.1145/3528416.3530251

Wade, A., A. Bhati, S. Wan, and P. Coveney. “Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility,” Journal of Chemical Theory and Computation (May 2022), ACS Publications. doi: 10.1021/acs.jctc.2c00114

Wan, S., A. Bhati, D. Wright, I. Wall, A. Graves, D. Green, and P. Coveney. “Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors Inhibitors,” Journal of Chemical Information and Modeling (May 2022), ACS Publications. doi: 10.1021/acs.jcim.2c00255

Wang, J., P. Xue, W. Pringle, Z. Yang, and Y. Qian. “Impacts of Lake Surface Temperature on the Summer Climate Over the Great Lakes Region,” JGR Atmospheres (May 2022), John Wiley and Sons. doi: 10.1029/2021jd036231

Yildiz, O., M. Dreher and T. Peterka. “Decaf: Decoupled Dataflows for In Situ Workflows,” In Situ Visualization for Computational Science (May 2022), Springer Nature, pp. 137-158. doi: 10.1007/978-3-030-81627-8_7

Zhao, J., and J. M. Cole. “A Database of Refractive Indices and Dielectric Constants Auto-generated Using ChemDataExtractor,” Scientific Data (May 2022), Springer Nature. doi: 10.1038/s41597-022-01295-5

JUNE

Anderson, J., Y. Liu, and J. Mellor-Crummey. “Preparing for Performance Analysis at Exascale,” ICS ’22: Proceedings of the 36th ACM International Conference on Supercomputing (June 2022), Association for Computing Machinery. doi: 10.1145/3524059.3532397

Caprio, M. A., P. J. Fasano, and P. Maris. “Robust Ab Initio Prediction of Nuclear Electric Quadrupole Observables by Scaling to the Charge Radius,” Physical Review C (June 2022), APS. doi: 10.1103/PhysRevC.105.L061302

Chitty-Venkata, K. T., M. Emani, V. Vishwanath, and A. K. Somani. “Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures,” HPDC ‘22: Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing (June 2022), Minneapolis, MN, Association for Computing Machinery. doi: 10.1145/3502181.3531463

Debackere, S. N. B., H. Hoekstra, J. Schaye, K. Heitmann, and S. Habib. “Why Are We Still Using 3D Masses for Cluster Cosmology?” Monthly Notices of the Royal Astronomical Society (June 2022), Oxford University Publishing. doi: 10.1093/mnras/stac1687

Glick-Magid, A., C. Forssén, D. Gazda, D. Gazit, P. Gysbers, and P. Navrátil. “Nuclear Ab Initio Calculations of ⁶He β-decay for beyond the Standard Model Studies,” Physical Review B (June 2022), Elsevier. doi: 10.1016/j.physletb.2022.137259

Haberlie, A. M., W. S. Ashley, C. M. Battisto, and V. A. Gensini. “Thunderstorm Activity Under Intermediate and Extreme Climate Change Scenarios,” Geophysical Research Letters (June 2022), vol. 49, no. 14, John Wiley and Sons. doi: 10.1029 2022gl098779

Hagen, G., S. J. Novario, Z. H. Sun, T. Papenbrock, G. R. Jansen, J. G. Lietz, T. Duguet, and A. Tichai. “Angular-Momentum Projection in Coupled-Cluster Theory: Structure of ³⁴Mg,” Physical Review C (June 2022), APS. doi: 10.1103/PhysRevC.105.064311

Hotton, A. L., J. Ozik, C. Kaligotla, N. Collier, A. Stevens, A. S. Khanna, M. M. MacDonell, C. Wang, D. J. LePoire, Y.-S. Chang, I. J. Martiniz-Moyano, B. Mucenic, H. A. Pollack, J. A. Schneider, and C. Macal. “Impact of Changes in Protective Behaviors and Out-of-Household Activities by Age on COVID-19 Transmission and Hospitalization in Chicago, Illinois,” Annals of Epidemiology (June 2022), Elsevier. doi: 10.1016/j.annepidem.2022.06.005

Isaacs, E. B., H. Shin, A. Annaberdiyev, C. Wolverton, L. Mitas, A. Benali, and O. Heinonen. “Assessing the Accuracy of Compound Formation Energies with Quantum Monte Carlo,” Physical Review B (June 2022), APS. doi: 10.1103/PhysRevB.105.224110

Kanhaiya. K, H. Heinz. “Adsorption and Diffusion of Oxygen on Pure and Partially Oxidized Metal Surfaces in Ultrahigh Resolution,” Nano Letters (June 2022), ACS Publications, pp. 5392–5400. doi: 10.1021/acs.nanolett.2c00490

Kim, K., A. Dive, A. Grieder, N. Adelstein, S. Kang, L. F. Wan, and B. C. Wood. “Flexible Machine-Learning Interatomic Potential for Simulating Structural Disordering Behavior of Li₇La₃Zr₂O₁₂ Solid Electrolytes,” The Journal of Chemical Physics (June 2022), AIP. doi: 10.1063/5.0090341

Kumar, P., S. Kabra, and J. M. Cole. “Auto-generating Databases of Yield Strength and Grain Size Using ChemDataExtractor,” Scientific Data (June 2022), Springer Nature. doi: 10.1038/s41597-022-01301-w

Lin, Y.-R., M. Franke, S. Parhizkar, M. Raths, V. W. Yu., T.-L. Lee, S. Soubatch, V. Blum, F. S. Tautz, C. Kump, and F. C. Bocquet. “Boron Nitride on SiC(0001),” Physical Review Materials (June 2022), APS. doi: 10.1103/PhysRevMaterials.6.064002

Liu, J., B. Nicolae, D. Li, J. M. Wozniak, T. Bicer, Z. Liu, and I. Foster. “Large Scale Caching and Streaming of Training Data for Online Deep Learning,” FlexScience ’22: Proceedings of the 12th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures (June 2022), Association for Computing Machinery, pp. 19-26. doi: 10.1145/3526058.3535453

Lu, B.-N., N. Li, S. Elhatisari, Y.-Z. Ma, D. Lee, and U.-G. Meißner. “Perturbative Quantum Monte Carlo Method for Nuclear Physics,” Physical Review Letters (June 2022), APS. doi: 10.1103/PhysRevLett.128.242501

Sarkar, A., and D. Lee. “Self-Learning Emulators and Eigenvector Continuation,” Physical Review Research (June 2022), APS. doi: 10.1103/PhysRevResearch.4.023214

Skluzacek, T., M. Chen, E. Hsu, K. Chard, and I. Foster. “Models and Metrics for Mining Meaningful Metadata,” Computational Science – ICCS 2022 (June 2022), Springer Nature, pp. 417-430. doi: 10.1007/978-3-031-08751-6_30

Srinivasan, S., R. Batra, D. Luo, T. Loeffler, S. Manna, H. Chan, L. Yang, W. Yang, J. Wen, P. Darancet, and S. K. R. S. Sankaranarayanan. “Machine Learning the Metastable Phase Diagram of Covalently Bonded Carbon,” Nature Communications (June 2022), Springer Nature. doi: 10.1038/s41467-022-30820-8

Stein, G., J. Blaum, P. Harrington, T. Medan, and Z. Lukić. “Mining for Strong Gravitational Lenses with Self-Supervised Learning,” The Astrophysical Journal (June 2022), IOP Publishing. doi: 10.3847/1538-4357/ac6d63

Wan, S., A. P. Bhati, D. W. Wright, A. D. Wade, G. Tresadern, H. van Vlijmen, and P. V. Coveney. “The Performance of Ensemble-Based Free Energy Protocols in Computing Binding Affinities to ROS1 Kinase,” Scientific Reports (June 2022), Springer Nature. doi: 10.1038/s41598-022-13319-6

Yang, T. T., and W. Saidi. “Reconciling the Volcano Trend with the Butler–Volmer Model for the Hydrogen Evolution Reaction,” The Journal of Physical Chemistry Letters (June 2022), ACS. doi: 10.1021/acs.jpclett.2c01411

Yao, Y., H. Chan, S. Sankaranarayanan, P. Balaprakash, R. J. Harder, and M. J. Cherukara. “AutoPhaseNN: Unsupervised Physics-Aware Deep Learning of 3D Nanoscale Bragg Coherent Diffraction Imaging,” npj Computational Materials (June 2022), Springer Nature. doi: 10.1038/s41524-022-00803-w

JULY

Albergo, M. S., D. Boyda, D. C. Cranmer, C. Hackett, G. Kanwar, S. Racaniére, D. J. Rezende, F. Romero-López, P. E. Shanahan, and J. M. Urban. “Flow-Based Sampling in the Lattice Schwinger Model at Criticality,” Physical Review D (July 2022), APS. doi: 10.1103/physrevd.106.014514

Guo, J., L. Ward, Y. Babuji, N. Hoyt, M. Williamson, I. Foster, N. Jackson, C. Benmore, and G. Sivaraman. “Composition-Transferable Machine Learning Potential for LiCl-KCl Molten Salts Validated by High-Energy X-ray Diffraction,” Physical Review B (July 2022), APS. doi: 10.1103/PhysRevB.106.014209

Hosseini, R., F. Simini, and V. Vishwanath. “Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications,” Fifth Conference on Machine Learning and Systems (July 2022), Santa Clara, CA, MLSys. doi: 10.48550/arXiv.2207.09955

Ivan, L., and W. Kaufmann. “Direct Numerical Simulation of Turbulent Flow Using Hyperbolic Moment Methods,” ICCFD11 Proceedings (July 2022), Maui, HI, International Conference on Computational Fluid Dynamics.

Kaufmann, W., and J. G. McDonald. “Large-Scale Investigation of 3D Discontinuous-Galerkin-Hancock Method for Hyperbolic Balance Laws with Stiff Local Sources,” ICCFD11 Proceedings (July 2022), Maui, HI, International Conference on Computational Fluid Dynamics.

Krishnamoorthy, A., K. Nomura, N. Baradwaj, K. Shimamura, R. Ma, S. Fukushima, F. Shimojo, R. K. Kalia, A. Nakano, and P. Vashishta. “Hydrogen Bonding in Liquid Ammonia,” The Journal of Physical Chemistry Letters (July 2022), ACS. doi: 10.1021/acs.jpclett.2c01608

Kumar, V., and J. Larsson. “Modular Method for Estimation of Velocity and Temperature Profiles in High-Speed Boundary Layers,” AIAA Journal (July 2022), AIAA. doi: 10.2514/1.J061735

Marchildon, M., B. Allard, L. Ivan, and J. G. McDonald. “A Polydisperse Gaussian-Moment Method for Extended Statistical Modelling of Multiphase Flows,” ICCFD11 Proceedings (July 2022), Maui, HI, International Conference on Computational Fluid Dynamics.

Sankaranarayanan, S., B. Varughese, S. Manna, T. Loeffler, R. Batra, and M. Cherukara. “Transfer and Active Learning of High Dimensional Neural Network Potentials for Transition Metal Clusters and Bulk,” Research Square (July 2022), Research Square. doi: 10.21203/rs.3.rs-1769974/v1

Shilpika, S., B. Lusch, M. Emani, F. Simini, V. Vishwanath, M. E. Papka, and K.-L. Ma. “Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems,” 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (July 2022), Taormina, Italy, IEEE. doi: 10.1109/CCGrid54584.2022.00081

Zheng, H., V. Vishwanath, Q. Koziol, H. Tang, J. Ravi, J. Mainzer, and S. Byna. “HDF5 Cache VOL: Efficient and Scalable Parallel I/O through Caching Data on Node-Local Storage,” 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (July 2022), Taormina, Italy, IEEE. doi: 10.1109/CCGrid54584.2022.00015

AUGUST

Annaberdiyev, A., C. A. Melton, G. Wang, and L. Mitas. “Electronic Structure of α−RuCl₃ by Fixed-Node and Fixed-Phase Diffusion Monte Carlo Methods,” Physical Review B (August 2022), APS. doi: 10.1103/PhysRevB.106.075127

Bass, B., J. Larsen, B. Edwards, C. Mathis, and J. New. “Multi-Variable Parametric Analysis of Prototype Building Energy Performance Using Current and Future Weather Scenarios for Data-Driven Market Transformation Support,” Oak Ridge National Laboratory (August 2022), U.S. Department of Energy.

Bhardwaj, G., J. O’Connor, S. Rettie, Y.-H. Huang, T. A. Ramelot, V. K. Mulligan, G. G. Alpkilic, J. Palmer, A. K. Bera, M. J. Bick, M. Di Piazza, X. Li, P. Hosseinzadeh, T. W. Craven, R. Tejero, A. Lauko, R. Choi, C. Glynn, L. Dong, R. Griffin, W. C. van Voorhis, J. Rodriguez, L. Stewart, G. T. Montelione, D. Craik, and D. Baker. “Accurate De Novo Design of Membrane-Traversing Macrocycles,” Cell (August 2022), Cell Press. doi: 10.1016/j.cell.2022.07.019

Chakraborty, TC, J. Wang, Y. Qian, W. Pringle, Z. Yang, and P. Xue. “Urban versus Lake Impacts on Heat Stress and Its Disparities in a Shoreline City,” Research Square (August 2022), Research Square. doi: 10.21203/rs.3.rs-1818535/v1

Chen, Y., E. Lee, P. Gil, P. Ma, C. Amanchukwu and J. de Pablo. “Molecular Engineering of Fluoroether Electrolytes for Lithium Metal Batteries,” ChemRxiv (August 2022), Cambridge University Press. doi: 10.26434/chemrxiv-2022-1v9v6-v2

Egele, R., R. Maulik, K. Raghavan, B. Lusch, I. Guyon, and P. Balaprakash. “AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification,” 2022 26th International Conference on Pattern Recognition (August 2022), Montreal, QC, Canada, IEEE. doi: 10.1109/ICPR56361.2022.9956231

Futita, K., N. Sakamoto, T. Fujiwara, T. Tsukamoto, and J. Nonaka. “A Visual Analytics Method for Time-Series Log Data Using Multiple Dimensionality Reduction,” Journal of Advanced Simulation in Science and Engineering (August 2022), vol. 9, no. 2, Japan Society for Simulation Technology, pp. 206-219. doi: 10.15748/jasse.9.206

Hu, B., W. Jiang, T. Miyagi, Z. Sun, A. Ekström, C. Forssén, G. Hagen, J. D. Holt, T. Papenbrock, S. R. Stroberg, and I. Vernon. “Ab Initio Predictions Link the Neutron Skin of ²⁰⁸Pb to Nuclear Forces,” Nature Physics (August 2022), Springer Nature. doi: 10.1038/s41567-022-01715-8

Jain, S. S. “Accurate Conservative Phase-Field Method for Simulation of Two-Phase Flows,” Journal of Computational Physics (August 2022), Elsevier. doi: 10.1016/j.jcp.2022.111529

Lauricella, G., J. Zhou, Q. Luan, I. Papautsky, and Z. Peng. “Computational Study of Inertial Migration of Prolate Particles in a Straight Rectangular Channel,” Physics of Fluids (August 2022), AIP Publishing. doi: 10.1063/5.0100963

Linker, T., S. Fukushima, R. K. Kalia, A. Krishnamoorthy, A. Nakano, K. Nomura, K. Shimamura, F. Shimojo, and P. Vashishta. “Towards Computational Polar-Topotronics: Multiscale Neural-Network Quantum Molecular Dynamics Simulations of Polar Vortex States in SrTiO₃/PbTiO₃ Nanowires,” Frontiers in Nanotechnology (August 2022), Frontiers Media SA. doi: 10.3389/fnano.2022.884149

Mulligan, V. K., and P. Hosseinzadeh. “Computational Design of Peptide-Based Binders to Therapeutic Targets,” Approaching the Next Inflection in Peptide Therapeutics: Attaining Cell Permeability and Oral Bioavailability (August 2022), ACS, pp. 55-102. doi: 10.1021/bk-2022-1417.ch003

Newberry, F., C. Wetterer-Nelson, J. A. Evans, A. Doostan, and K. E. Jansen. “Software Tools to Enable Immersive Simulation,” Engineering with Computers (August 2022), Springer Nature. doi: 10.1007/s00366-022-01714-6

Robinson, D., C. Avestruz, and N. Y. Gnedin. “Can Cooling and Heating Functions Be Modeled with Homogeneous Radiation Fields?” The Astrophysical Journal (August 2022), IOP Publishing. doi: 10.3847/1538-4357/ac85e1

Schwartz, J., C. Harris, J. Pietryga, H. Zheng, P. Kumar, A. Visheratina, N. A. Kotov, B. Major, P. Avery, P. Ercius, U. Ayachit, B. Geveci, D. A. Muller, A. Genova, Y. Jiang, M. Hanwell, and R. Hovden. “Real-Time 3D Analysis during Electron Tomography Using tomviz,” Nature Communications (August 2022), Springer Nature. doi: 10.1038/s41467-022-32046-0

Sherrell, D. A., A. Lavens, M. Wilamowski, Y. Kim, R. Chard, K. Lazarski, G. Rosenbaum, R. Vescovi, J. L. Johnson, C. Akins, C. Chang, K. Michalska, G. Babnigg, I. Foster, and A. Joachimiak. “Fixed-Target Serial Crystallography at the Structural Biology Center,” Journal of Synchrotron Radiation (August 2022), International Union of Crystallography. doi: doi.org/10.1107/S1600577522007895

Trifan, A., D. Gorgun, M. Salim, Z. Li, A. Brace, M. Zvyagin, H. Ma, A. Clyde, D. Clark, D. J. Hardy, T. Burnley, L. Huang, J. McCalpin, M. Emani, H. Yoo, J. Yin, A. Tsaris, V. Subbiah, T. Raza, J. Liu, N. Trebesch, G. Wells, V. Mysore, T. Gibbs, J. Phillips, S. C. Chennubhotla, I. Foster, R. Stevens, A. Anandkumar, V. Vishwanath, J. E. Stone, E. Tajkhorshid, S. A. Harris, and A. Ramanathan. “Intelligent Resolution: Integrating Cryo-EM with AI-Driven Multi-Resolution Simulations to Observe the Severe Acute Respiratory Syndrome Coronavirus-2 Replication-Transcription Machinery in Action,” The International Journal of High Performance Computing Applications (August 2022), SAGE Publications. doi: 10.1177/10943420221113513

Wang, G., B. Kincaid, H. Zhou, A. Annaberdiyev, M. C. Bennett, J. T. Krogel, and L. Mitas. “A New Generation of Effective Core Potentials from Correlated and Spin-Orbit Calculations: Selected Heavy Elements,” The Journal of Chemical Physics (August 2022), AIP. doi: 10.1063/5.0087300

Wang, X., S. Gao, M. Zhao, and N. Marom. “Benchmarking Time-Dependent Density Functional Theory for Singlet Excited States of Thermally Activated Delayed Fluorescence Chromophores,” Physical Review Research (August 2022), APS. doi: 10.1103/physrevresearch.4.033147

Wu, X., V. Taylor, and Z. Lan. “Performance and Power Modeling and Prediction Using MuMMI and 10 Machine Learning Methods,” Concurrency and Computation: Practice and Experience (August 2022) John Wiley and Sons. doi: 10.1002/cpe.7254

Yu, V. W., and M. Govoni. “GPU Acceleration of Large-Scale Full-Frequency GW Calculations,” Journal of Chemical Theory and Computation (August 2022), ACS. doi: 10.1021/acs.jctc.2c00241

SEPTEMBER

Coleman, M. S. B., and A. Burrows. “Kicks and Induced Spins of Neutron Stars at Birth,” Monthly Notices of the Royal Astronomical Society (September 2022), Oxford University Publishing. doi: 10.1093/mnras/stac2573

Dorier, M., R. Egele, P. Balaprakash, J. Koo, S. Madireddy, S. Ramesh, A. D. Malony, and R. Ross. “HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization,” 2022 IEEE International Conference on Cluster Computing (CLUSTER) (September 2022), IEEE, pp. 381-393. doi: 10.1109/CLUSTER51413.2022.00049

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

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

Hobbs, B. F., J. Zhang, H. F. Hamann, C. Siebenschuh, R. Zhang, B. Li, I. Krad, V. Krishnan, E. Spyrou, Y. Wang, Q. Xu, and S. Zhang. “Using Probabilistic Solar Power Forecasts to Inform Flexible Ramp Product Procurement for the California ISO,” Solar Energy Advances (September 2022), Elsevier. doi: 10.1016/j.seja.2022.100024

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

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, 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

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

McCray, A. R. C., Y. Li, R. Basnet, K. Pandey, J. Hu, D. P. Phelan, X. Ma, A. K. Petford-Long, and C. Phatak. “Thermal Hysteresis and Ordering Behavior of Magnetic Skyrmion Lattices,” Nano Letters (September 2022), ACS Publications. doi: 10.1021/acs.nanolett.2c02275

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

Sobczyk, J. E., S. Bacca, G. Hagen, and T. Papenbrock. “Spectral Function for ⁴He Using the Chebyshev Expansion in Coupled-Cluster Theory,” Physical Review C (September 2022), APS. doi: 10.1103/PhysRevC.106.034310

Tews, I., Z. Davoudi, A. Ekström, J. D. Holt, K. Becker, R. Briceño, D. J. Dean, W. Detmold, C. Drischler, T. Duguet, E. Epelbaum, A. Gasparyan, J. Gegelia, J. R. Green, H. W. Grießhammer, A. D. Hanlon, M. Heinz, H. Hergert, M. Hoferichter, M. Illa, D. Kekejian, A. Kievsky, S. König, H. Krebs, K. D. Launey, D. Lee, P. Navrátil, A. Nicholson, A. Parreño, D. R. Phillips, M. Płoszajczak, X.-L. Ren, T. R. Richardson, C. Robin, G. H. Sargsyan, M. J. Savage, M. R. Schindler, P. E. Shanahan, R. P. Springer, A. Tichai, U. van Kolck, M. L. Wagman, A. Walker-Loud, C.-J. Yang, and X. Zhang. “Nuclear Forces for Precision Nuclear Physics: A Collection of Perspectives,” Few-Body Systems (September 2022), Springer Nature. doi: 10.1007/s00601-022-01749-x

Tsai, P.- H., and P. Fischer. “Parametric Model-Order-Reduction Development for Unsteady Convection,” Frontiers in Physics (September 2022), vol. 10, Frontiers Media SA. doi: 10.3389/fphy.2022.903169

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

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

Yang, H., M. Govoni, A. Kundu, and G. Galli. “Computational Protocol to Evaluate Electron–Phonon Interactions within Density Matrix Perturbation Theory,” Journal of Chemical Theory and Computation (September 2022), ACS. doi: 10.1021/acs.jctc.2c00579

Yang, T. T., A. Wang, S. D. House, J. Yang, J.-K. Lee, and W. A. Saidi. “Computationally Guided Design to Accelerate Discovery of Doped β-Mo₂C Catalysts toward Hydrogen Evolution Reaction,” ACS Catalysis (September 2022), ACS Publications. doi: 10.1021/acscatal.2c03184

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

OCTOBER

Abbot, R., M. S. Albergo, D. Boyda, K. Cranmer, D. C. Hackett, G. Kanwar, S. Racaniere, D. J. Rezende, F. Romero-Lopez, P. E. Shanahan, B. Tian, and J. M. Urban. “Gauge-Equivariant Flow Models for Sampling in Lattice Field Theories with Pseudofermions,” Physical Review D (October 2022), APS. doi: 10.1103/physrevd.106.074506

Ali, A., H. Sharma, R. Kettimuthu, P. Kenesei, D. Trujillo, A. Miceli, I. Foster, R. Coffee, J. Thayer, and Z. Liu. “fairDMS: Rapid Model Training by Data and Model Reuse,” 2022 IEEE International Conference on Cluster Computing (CLUSTER) (October 2022), Heidelberg, Germany, IEEE. doi: 10.1109/CLUSTER51413.2022.00050

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

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.

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.

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

Davies, C. T. H., C. Detar, A. X. El-Khadra, S. Gottlieb, D. Hatton, A. S. Kronfeld, S. Lahert, G. P. Lepage, C. McNeile, E. T. Neil, C. T. Peterson, G. S. Ray, R. S. Van de Water, and A. Vaquero. “Windows on the Hadronic Vacuum Polarization Contribution to the Muon Anomalous Magnetic Moment,” Physical Review D (October 2022), vol. 106, no. 7, APS. doi: 10.1103/physrevd.106.074509

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.

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

Giannakopoulos, G. K., K. Keskinen, J. Koch, C. E. Frouzakis, Y. M. Wright, and K. Boulouchos. “Characterizing the Evolution of Boundary Layers in IC Engines by Combined Direct Numerical and Large-Eddy Simulations,” Flow, Turbulence and Combustion (October 2022), Springer Nature. doi: 10.1007/s10494-022-00383-1

Hobbs, B. F., V. Krishnan, J. Zhang, H. F. Hamann, C. Siebenschuh, R. Zhang, B. Li, L. He, P. Edwards, H. Sky, I. Krad, E. Spyrou, X. Fang, Y. Wang, Q. Xu, and S. Zhang. “How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements,” IEEE Open Access Journal of Power and Energy (October 2022), IEEE. doi: 10.1109/OAJPE.2022.3217909

Kim, H., S. Kang, J. Y. Lee, T. W. Heo, B. C. Wood, J.-H. Shim, Y. W. Cho, D. H. Kim, J.-Y. Suh, and Y.-S. Lee. “A New Perspective on the Initial Hydrogenation of TiFe_0.9M_0.1 (M = V, Cr, Fe, Co, Ni) Alloys Gained from Surface Oxide Analyses and Nucleation Energetics,” Applied Surface Science (October 2022), Elsevier. doi: 10.1016/j.apsusc.2022.155443

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

Li, B., Y. Fan, M. Dearing, Z. Lan, P. Rich, W. Allcock, and M. Papka. “MRSch: Multi-Resource Scheduling for HPC,” 2022 IEEE International Conference on Cluster Computing (CLUSTER) (October 2022), IEEE. doi: 10.1109/cluster51413.2022.00020

Petro, J. M., H. Rong, C. Michaud, N. Layad, Z. Liu, and R. Coffee. “Enabling Real-Time Adaptation of Machine Learning Models at X-ray Free Electron Laser Facilities with High-Speed Training Optimized Computational Hardware,” Frontiers in Physics (October 2022), Frontiers Media SA. doi: 10.3389/fphy.2022.958120

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.

Shah, A. H., Z. Zhang, Z. Huang, S. Wang, G. Zhong, C. Wan, A. N. Alenandrova, Y. Huang, and X. Duan. “The Role of Alkali Metal Cations and Platinum-Surface Hydroxyl in the Alkaline Hydrogen Evolution Reaction,” Nature Catalysis (October 2022), Springer Nature. doi: 10.1038/s41929-022-00851-x

Sierepeklis, O., and J. M. Cole. “A Thermoelectric Materials Database Auto-Generated from the Scientific Literature Using ChemDataExtractor,” Scientific Data (October 2022), Springer Nature. doi: 10.1038/s41597-022-01752-1

Vescovi, R., R. Chard, N. D. Saint, B. Blaiszik, J. Pruyne, T. Bicer, A. Lavens, Z. Liu, M. E. Papka, S. Narayanan, N. Schwarz, K. Chard, and I. T. Foster. “Linking Scientific Instruments and Computation: Patterns, Technologies, and Experiences,” Patterns (October 2022), Cell Press. doi: 10.1016/j.patter.2022.100606

Wilkins, M., Y. Guo, R. Thakur, P. Dinda, and N. Hardavellas. “ACCLAiM: Advancing the Practicality of MPI Collective Communication Autotuning Using Machine Learning,” 2022 IEEE International Conference on Cluster Computing (CLUSTER) (October 2022), Heidelberg, Germany, IEEE. doi: 10.1109/CLUSTER51413.2022.00030

Yang, L., S. C. Tiwari, S. Fukushima, F. Shimojo, R. K. Kalia, A. Nakano, P. Vashishta, and P. S. Branicio. “Photoexcitation-Induced Nonthermal Ultrafast Loss of Long-Range Order in GeTe,” The Journal of Physical Chemistry Letters (October 2022), ACS. doi: 10.1021/acs.jpclett.2c02448

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

NOVEMBER

Andrusenko, I., C. L. Hall, E. Mugnaioli, J. Potticary, S. R. Hall, W. Schmidt, S. Gao, K. Zhao, N. Marom, and M. Gemmi. “True Molecular Conformation and Structure Determination by Three-Dimensional Electron Diffraction of PAY By-Products Potentially Useful for Electronic Applications,” IUCrJ (November 2022), International Union of Crystallography, pp. 131-142. doi: 10.1107/s205225252201154x

Doan, H. A., C. Li, L. Ward, M. Zhou, L. A. Curtiss, and R. S. Assary. “Accelerating the Evaluation of Crucial Descriptors for Catalyst Screening via Message Passing Neural Network,” Digital Discovery (November 2022), Royal Society of Chemistry. doi: 10.1039/D2DD00088A

Dodd-o, J., A. M. Acevedo-Jake, A.-R. Azizogli, V. K. Mulligan, and V. A. Kumar. “How to Design Peptides,” Chemokine-Glycosaminoglycan Interactions: Methods and Protocols (November 2022), Springer Nature, pp. 187-216. doi: 10.1007/978-1-0716-2835-5_15

Fedorov, D., M. Otten, B. Kang, A. Benali, S. Habib, S. Gray, and Y. Alexeev. “Quantum Resource Estimation for Quantum Chemistry Algorithms,” 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (November 2022), Broomfield, CO, IEEE. doi: 10.1109/QCE53715.2022.00144

Hager, R., S. Ku, A. Y. Sharma, C. S. Chang, R. M. Churchill, and A. Scheinberg. “Electromagnetic Total-f Algorithm for Gyrokinetic Particle-in-Cell Simulations of Boundary Plasma in XGC,” Physics of Plasmas (November 2022), AIP. doi: 10.1063/5.0097855

Hargrove, P. H., and D. Bonachea. “GASNet-EX RMA Communication Performance on Recent Supercomputing Systems,” 5th Annual Parallel Applications Workshop, Alternatives to MPI+X (November 2022), IEEE. doi: 10.25344/S40C7D

Hosseini, R., F. Simini, A. Clyde, and A. Ramanathan. “Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks,” Thirty-Sixth Conference on Neural Information Processing Systems (November 2022), New Orleans, LA, Neural Information Processing Systems Foundation. doi: 10.48550/arXiv.2211.02720

Huck, K., X. Wu, A. Dubey, A. Georgiadou, J. A. Harris, T. Klosterman, M. Trappett, and K. Weide. “Performance Debugging and Tuning of Flash-X with Data Analysis Tools,” SC2022 Workshop on Programming and Performance Visualization Tools (ProTools22) (November 2022), Dallas, TX, IEEE.

Kincaid, B., G. Wang, H. Zhou, and L. Mitas. “Correlation Consistent Effective Core Potentials for Late 3D Transition Metals Adapted for Plane Wave Calculations,” The Journal of Chemical Physics (November 2022), AIP. doi: 10.1063/5.0109098

Kurihana, T., J. Franke, I. Foster, Z. Wang, and E. Moyer. “Insight into Cloud Processes from Unsupervised Classification with a Rotationally Invariant Autoencoder,” Thirty-Sixth Conference on Neural Information Processing Systems (November 2022), New Orleans, LA, Neural Information Processing Systems Foundation. doi: 10.48550/arXiv.2211.00860

Kurihana, T., E. J. Moyer, and I. T. Foster. “AICCA: AI-Driven Cloud Classification Atlas,” Remote Sensing (November 2022), MDPI. doi: 10.3390/rs14225690

Lin, P.-H., C. Liao, W. Chen, T. Vanderbruggen, M. Emani, and H. Xu. “Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study,” 2022 Fourth International Conference on Transdisciplinary AI (November 2022), Laguna Hills, CA, IEEE. doi: 10.1109/TransAI54797.2022.00029

Lykov, D., R. Schutski, A. Gaida, V. Vinokur, and Y. Alexeev. “Tensor Network Quantum Simulator with Step-Dependent Parallelization,” 2022 IEEE International Conference on Quantum Computing and Engineering (QCE) (November 2022), IEEE. doi: 10.1109/QCE53715.2022.00081

Munarriz, J., Z. Zhang, P. Sautet, and A. N. Alexandrova. “Graphite-Supported Ptn Cluster Electrocatalysts: Major Change of Active Sites as a Function of the Applied Potential,” ACS Catalysis (November 2022), ACS Publications. doi: 10.1021/acscatal.2c04643

Ravi, N., P. Chaturvedi, E. A. Huerta, L. Zhengchun, R. Chard, A. Scourtas, K. J. Schmidt, K. Chard, B. Blaiszik, and I. Foster. “FAIR Principles for AI Models with a Practical Application for Accelerated High Energy Diffraction Microscopy,” Scientific Data (November 2022), Springer Nature. doi: 10.1038/s41597-022-01712-9

Roja, E., D. Pérez, and E. Meneses. “Exploring the Effects of Silent Data Corruption in Distributed Deep Learning Training,” 2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (November 2022), IEEE, pp. 21-30. doi: 10.1109/SBAC-PAD55451.2022.00013

Schmitt, J., G. B. King, R. G. T. Zegers, Y. Ayyad, D. Bazin, B. A. Brown, A. Carls, J. Chen, A. Davis, M. DeNudt, J. Droste, B. Gao, C. Hultquist, H. Iwasaki, S. Noji, S. Pastore, J. Pereira, M. Piarulli, H. Sakai, A. Stolz, R. Titus, R. B. Wiringa, and J. C. Zamora. “Probing Spin-Isospin Excitations in Proton-Rich Nuclei via the ¹¹C(p,n)¹¹N Reaction,” Physical Review C (November 2022), APS. doi: 10.1103/physrevc.106.054323

Weiss, R., A. Lovato, and R. B. Wiringa. “Isospin-Symmetry Implications for Nuclear Two-Body Distributions and Short-Range Correlations,” Physical Review C (November 2022), APS. doi: 10.1103/PhysRevC.106.054319

Zyvagin, M., A. Brace, K. Hippie, Y. Deng, B. Zhang, C. O. Bohorquez, A. Clyde, B. Kale, D. Perez-Rivera, H. Ma, C. M. Mann, M. Irvin, J. G. Pauloski, L. Ward, V. Hayot-Sasson, M. Emani, S. Foreman, Z. Xie, D. Lin, M. Shukla, W. Nie, J. Romero, C. Dallago, A. Vahdat, C. Xiao, T. Gibbs, I. Foster, J. J. Davis, M. E. Papka, T. Brettin, R. Stevens, A. Anandkumar, V. Vishwanath, and A. Ramanathan. “GenSLMs: Genome-Scale Language Models Reveal SARS-CoV-2 Evolutionary Dynamics,” SC22: The International Conference for High Performance Computing, Networking, Storage, and Analysis (November 2022), Dallas, TX, IEEE. doi: 10.1101 2022.10.10.511571

DECEMBER

Bass, B., J. New, and Z. Wade. “Future Typical Meteorological Year (fTMY) Weather Data and Climate Change Impacts to Maricopa County, Arizona,” BuildSys ’22: Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (December 2022), Association for Computing Machinery, pp. 504-507. doi: 10.1145/3563357.3567408

Blöndal, K., K. Sargsyan, D. H. Bross, B. Ruscic, and C. F. Goldsmith. “Configuration Space Integration for Adsorbate Partition Functions: The Effect of Anharmonicity on the Thermophysical Properties of CO–Pt(111) and CH₃OH–Cu(111),” ACS Catalysis (December 2022), ACS. doi: 10.1021/acscatal.2c04246

Hoy, J., and I. Bermejo-Moreno. “Fluid-Structural Coupling of an Impinging Shock-Turbulent Boundary Layer Interaction at Mach 3 over a Flexible Panel,” Flow (December 2022), Cambridge University Press. doi: 10.1017/flo.2022.28

Jain, S. S., and A. Mani. “A Computational Model for Transport of Immiscible Scalars in Two-Phase Flows,” Journal of Computational Physics (December 2022), Elsevier. doi: 10.1016/j.jcp.2022.111843

Jain, S. S., M. C. Adler, J. R. West, A. Mani, P. Moin, and S. K. Lele. “Assessment of Diffuse-Interface Methods for Compressible Multiphase Fluid Flows and Elastic-Plastic Deformation in Solids,” Journal of Computational Physics (December 2022), Elsevier. doi: 10.1016/j.jcp.2022.111866

Kraus, M., L. Naoufal, L. Zhengchun, and R. Coffee. “EdgeAI: Machine Learning via Direct Attached Accelerator for Streaming Data Processing at High Shot Rate X-Ray Free-Electron Lasers,” Frontiers in Physics (December 2022), Frontiers Media SA. doi: 10.3389/fphy.2022.957509

Linker, T., K. Nomura, S. Fukushima, R. K. Kalia, A. Krishnamoorthy, A. Nakano, K. Shimamura, F. Shimojo, and P. Vashishta. “Squishing Skyrmions: Symmetry-Guided Dynamic Transformation of Polar Topologies under Compression,” The Journal of Physical Chemistry Letters (December 2022), ACS. doi: 10.1021/acs.jpclett.2c03029

Linot, A. J., J. W. Burby, Q. Tang, P. Balaprakash, M. D. Graham, and R. Maulik. “Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems,” Journal of Computational Physics (December 2022), Elsevier. doi: 10.1016/j.jcp.2022.111838

Maris, P., R. Roth, E. Epelbaum, R. J. Furnstahl, J. Golak, K. Hebeler, T. Hüther, H. Kamada, H. Krebs, H. Le, U.-G. Meißner, J. A. Melendez, A. Nogga, P. Reinert, R. Skibiński, J. P. Vary, H. Witała, and T. Wolfgruber. “Nuclear Properties with Semilocal Momentum-Space Regularized Chiral Interactions beyond N²LO,” Physical Review C (December 2022), APS. doi: 10.1103/PhysRevC.106.064002

Marrinan, T., J. Tan, J. A. Insley, A. Kanayinkal, and M. E. Papka. “Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images,” ISVC 2022: Advances in Visual Computing (December 2022), Springer Nature. doi: 10.1007/978-3-031-20713-6_9

Moran, K. R., K. Heitmann, E. Lawrence, S. Habib, D. Bingham, A. Upadhye, J. Kwan, D. Higdon, and R. Payne. “The Mira-Titan Universe – IV. High Precision Power Spectrum Emulation,” Monthly Notices of the Royal Astronomical Society (December 2022), Oxford University Publishing. doi: 10.1093/mnras/stac3452

Nealey, I., N. Ferrier, J. A. Insley, V. A. Mateevitsi, S. Rizzi, and J. Schulze. “Sort-Last In-Transit Data Visualization with SENSEI, Catalyst, and Unreal Engine,” 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV) (December 2022), Oklahoma City, OK, IEEE. doi: 10.1109/LDAV57265.2022.9966391

Norman, M., I. Lyngaas, A. Bagusetty, and M. Berrill. “Portable C++ Code That Can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL),” International Journal of Parallel Programming (December 2022), Springer Nature. doi: 10.1007/s10766-022-00739-0

Ortiz, J. A., J. A. Insley, J. Knowles, V. A. Mateevitsi, M. E. Papka, and S. Rizzi. “Massive Data Visualization Techniques for Use in Virtual Reality Devices,” 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV) (December 2022), Oklahoma City, OK, IEEE. doi: 10.1109/LDAV57265.2022.9966400

Rostamijavanani, A., S. Li, and Y. Yang. “Physics-Constrained Deep Learning of Nonlinear Normal Modes of Spatiotemporal Fluid Flow Dynamics,” Physics of Fluids (December 2022), AIP Publishing. doi: 10.1063/5.0124455

Sun, Z. H., C. A. Bell, G. Hagen, and T. Papenbrock. “How to Renormalize Coupled Cluster Theory,” Physical Review C (December 2022), APS. doi: 10.1103/PhysRevC.106.L061302

Tishchenko, N., N. Ferrier, J. A. Insley, V. A. Mateevitsi, M. E. Papka, S. Rizzi, and J. Tan. “Toward Bi-directional In Situ Visualization and Analysis of Blood Flow Simulations with Dynamic Deforming Walls,” 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV) (December 2022), Oklahoma City, OK, IEEE. doi: 10.1109/LDAV57265.2022.9966389

Torelli, R., Y. Pei, Y. Zhang, and S. Som. “End-to-End Modeling of Fuel Injection via Static Coupling of Internal Flow and Ensuing Spray,” Communications Engineering (December 2022), Springer Nature. doi: 10.1038/s44172-022-00038-z

Weiss, R., P. Soriano, A. Lovato, J. Menendez, and R. B. Wiringa. “Neutrinoless Double-β Decay: Combining Quantum Monte Carlo and the Nuclear Shell Model with the Generalized Contact Formalism,” Physical Review C (December 2022), APS. doi: 10.1103/physrevc.106.065501

Wu, Q., J. Bessac, W. Huang, J. Wang, and R. Kotamarthi. “A Conditional Approach for Joint Estimation of Wind Speed and Direction Under Future Climates,” Advances in Statistical Climatology, Meteorology and Oceanography (December 2022), Copernicus Publications. doi: 10.5194/ascmo-8-205-2022

Wu, Q., J. A. Insley, V. A. Mateevitsi, S. Rizzi, and K.-L. Ma. “Distributed Volumetric Neural Representation for In Situ Visualization and Analysis,” 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV) (December 2022), Oklahoma City, OK, IEEE. doi: 10.1109/LDAV57265.2022.9966405

Wu, S., H. Li, and A. Ma. “Exact Reaction Coordinates for Flap Opening in HIV-1 Protease,” Proceedings of the National Academy of Sciences (December 2022), NAS. doi: 10.1073/pnas.2214906119

Wu, S., S. S. Patel, and M. M. Ameen. “Investigating the Origins of Cyclic Variability in Internal Combustion Engines Using Wall-Resolved Large Eddy Simulations,” Journal of Engineering for Gas Turbines and Power (December 2022), The American Society of Mechanical Engineers. doi: 10.1115/1.4056095