Explore how software is shaping the future of science' |  | Empowering Discovery Through Software Innovation | Explore cutting-edge tools and frameworks advancing quantum chemistry and molecular science | The future of chemical physics is being written in code. Researchers are leveraging open-source libraries, scalable computing frameworks, and collaborative platforms to tackle complex challenges and accelerate discovery.
This curated selection of articles from The Journal of Chemical Physics (JCP) highlights innovations that embody flexibility, scalability, and sustainability. From HORTON's decade-long evolution and BigChem's massively parallel workflows, to GBasis for Gaussian basis computations and Sire for molecular simulation interoperability, these tools redefine computational possibilities. | | Publish Your Paper With JCP | Share your research on software development or computational methods and help shape the future of chemical physics. | | | | | | | Explore solutions for multireference quantum methods with Forte, configuration interaction with PyCI, and quantum dynamics simulations using mpsqd. Learn how PLUMED Tutorials foster collaborative learning and how MRSimulator simplifies solid-state nuclear magnetic resonance spectral analysis.
The developments discussed in these papers illustrate how software is transforming chemical physics—empowering scientists to push boundaries and reveal new insights. |
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MRSimulator: A cross-platform, object-oriented software package for rapid solid-state NMR spectral simulation and analysis Deepansh J. Srivastava, Matthew Giammar, Maxwell C. Venetos, Lexi McCarthy-Carney, et al. READ MORE > | | | Grid: A Python library for molecular integration, interpolation, differentiation, and more Alireza Tehrani, Xiaotian Derrick Yang, Marco Martínez-González, Leila Pujal, et al. READ MORE > | | | Massively scalable workflows for quantum chemistry: BigChem and ChemCloud Colton B. Hicks, Todd J. Martinez READ MORE > | | | The tale of HORTON: Lessons learned in a decade of scientific software development Matthew Chan, Toon Verstraelen, Alireza Tehrani, Michelle Richer, et al. READ MORE > | | | GBasis: A Python library for evaluating functions, functionals, and integrals expressed with Gaussian basis functions Taewon David Kim, Leila Pujal, Michelle Richer, Maximilian van Zyl, et al. READ MORE > | | | PyCI: A Python-scriptable library for arbitrary determinant CI Michelle Richer, Gabriela Sánchez-Díaz, Marco Martínez-González, Valerii Chuiko, et al. READ MORE > | | | Forte: A suite of advanced multireference quantum chemistry methods Francesco A. Evangelista, Chenyang Li, Prakash Verma, Kevin P. Hannon, et al. READ MORE > | | | mpsqd: A matrix product state based Python package to simulate closed and open system quantum dynamics Weizhong Guan, Peng Bao, Jiawei Peng, Zhenggang Lan, et al. READ MORE > | | | PLUMED Tutorials: A collaborative, community-driven learning ecosystem Gareth A. Tribello, Massimiliano Bonomi, Giovanni Bussi, Carlo Camilloni, et al. READ MORE > | | | Sire: An interoperability engine for prototyping algorithms and exchanging information between molecular simulation programs Christopher J. Woods, Lester O. Hedges, Adrian J. Mulholland, Maturos Malaisree, et al. READ MORE > | | | |
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FURTHER SOFTWARE AND CHEMICAL PHYSICS RESEARCH |
Explore more fascinating studies from other journals in our portfolio. | APL COMPUTATIONAL PHYSICS |
Enhancing PySCF-based quantum chemistry simulations with modern hardware, algorithms, and Python tools Zhichen Pu, Qiming Sun READ MORE > | | | |
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Deep learning-based prediction of high explosive induced fluid dynamics Francis G. VanGessel, Mitul Pandya READ MORE > | | | |
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Aqueous solution chemistry in silico and the role of data-driven approaches Debarshi Banerjee, Khatereh Azizi, Colin K. Egan, Edward Danquah Donkor, et al. READ MORE > | | | |
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