Community Accessible Datastore of High-Throughput Calculations: Experiences from the Materials Project. - Dan Gunter; Shreyas Cholia; Anubhav Jain 001; Michael Kocher; Kristin A. Persson; Lavanya Ramakrishnan; Shyue Ping Ong; Gerbrand Ceder (SC Companion, 2012)

A Community Contribution Framework for Sharing Materials Data with Materials Project. - Patrick Huck; Anubhav Jain 001; Dan Gunter; Donald Winston; Kristin A. Persson (e-Science, 2015)

FireWorks: a dynamic workflow system designed for high-throughput applications. - Anubhav Jain 001; Shyue Ping Ong; Wei Chen 043; Bharat Medasani; Xiaohui Qu; Michael Kocher; Miriam Brafman; Guido Petretto; Gian-Marco Rignanese; Geoffroy Hautier; Daniel K. Gunter; Kristin A. Persson (Concurr. Comput. Pract. Exp., 2015)

PyDII: A python framework for computing equilibrium intrinsic point defect concentrations and extrinsic solute site preferences in intermetallic compounds. - Hong Ding; Bharat Medasani; Wei Chen 043; Kristin A. Persson; Maciej Haranczyk; Mark Asta (Comput. Phys. Commun., 2015)

User applications driven by the community contribution framework MPContribs in the Materials Project. - Patrick Huck; Dan Gunter; Shreyas Cholia; Donald Winston; Alpha T. N'Diaye; Kristin A. Persson (Concurr. Comput. Pract. Exp., 2016)

Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature. - Leigh Weston; Vahe Tshitoyan; John Dagdelen; Olga Kononova; Amalie Trewartha; Kristin A. Persson; Gerbrand Ceder; Anubhav Jain 001 (J. Chem. Inf. Model., 2019)

Unsupervised word embeddings capture latent knowledge from materials science literature. - Vahe Tshitoyan; John Dagdelen; Leigh Weston; Alexander Dunn; Ziqin Rong; Olga Kononova; Kristin A. Persson; Gerbrand Ceder; Anubhav Jain 001 (Nat., 2019)

COVIDScholar: An automated COVID-19 research aggregation and analysis platform. - Amalie Trewartha; John Dagdelen; Haoyan Huo; Kevin Cruse; Zheren Wang; Tanjin He; Akshay Subramanian; Yuxing Fei; Benjamin Justus; Kristin A. Persson; Gerbrand Ceder (CoRR, 2020)

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride. - Oxana Andriuc; Martin Siron; Joseph H. Montoya; Matthew K. Horton; Kristin A. Persson (J. Chem. Inf. Model., 2021)

Promises and perils of computational materials databases. - Matthew K. Horton; Shyam Dwaraknath; Kristin A. Persson (Nat. Comput. Sci., 2021)

Structured information extraction from complex scientific text with fine-tuned large language models. - Alexander Dunn; John Dagdelen; Nicholas Walker; Sanghoon Lee; Andrew S. Rosen; Gerbrand Ceder; Kristin A. Persson; Anubhav Jain 001 (CoRR, 2022)

Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science. - Amalie Trewartha; Nicholas Walker; Haoyan Huo; Sanghoon Lee; Kevin Cruse; John Dagdelen; Alexander Dunn; Kristin A. Persson; Gerbrand Ceder; Anubhav Jain 001 (Patterns, 2022)

Extracting Structured Seed-Mediated Gold Nanorod Growth Procedures from Literature with GPT-3. - Nicholas Walker; John Dagdelen; Kevin Cruse; Sanghoon Lee; Samuel Gleason; Alexander Dunn; Gerbrand Ceder; A. Paul Alivisatos; Kristin A. Persson; Anubhav Jain 001 (CoRR, 2023)

Matbench Discovery - An evaluation framework for machine learning crystal stability prediction. - Janosh Riebesell; Rhys E. A. Goodall; Anubhav Jain 001; Philipp Benner; Kristin A. Persson; Alpha A. Lee (CoRR, 2023)

Chemical reaction networks and opportunities for machine learning. - Mingjian Wen; Evan Walter Clark Spotte-Smith; Samuel M. Blau; Matthew J. McDermott; Aditi S. Krishnapriyan; Kristin A. Persson (Nat. Comput. Sci., 2023)

SolvationAnalysis: A Python toolkit for understanding liquid solvation structure in classical molecular dynamics simulations. - Orion Archer Cohen; Hugo MacDermott-Opeskin; Lauren Lee; Tingzheng Hou; Kara D. Fong; Ryan Kingsbury; Jingyang Wang; Kristin A. Persson (J. Open Source Softw., 2023)

A method to computationally screen for tunable properties of crystalline alloys. - Rachel Woods-Robinson; Matthew K. Horton; Kristin A. Persson (Patterns, 2023)

Towards MatCore: A Unified Metadata Standard for Materials Science. - Jane Greenberg; Pámela Bóveda-Aguirre; John Allison; Pietro Asinari; Maria Chan; Anand Chandrasekaran; Elif Ertekin; Emmanouel Garoufallou; Giulia Galli; Paolo Giannozzi; Feliciano Giustino; Gerhard Goldbeck; et al. (MTSR, 2024)

Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning. - Bowen Deng; Yunyeong Choi; Peichen Zhong; Janosh Riebesell; Shashwat Anand; Zhuohan Li; KyuJung Jun; Kristin A. Persson; Gerbrand Ceder (CoRR, 2024)

Deconvolution and Analysis of the 1H NMR Spectra of Crude Reaction Mixtures. - Maxwell C. Venetos; Masha Elkin; Connor Delaney; John F. Hartwig; Kristin A. Persson (J. Chem. Inf. Model., 2024)

pylattica: a package for prototyping lattice models in chemistry and materials science. - Max C. Gallant; Kristin A. Persson (J. Open Source Softw., 2024)

Jobflow: Computational Workflows Made Simple. - Andrew S. Rosen; Max C. Gallant; Janine George; Janosh Riebesell; Hrushikesh Sahasrabuddhe; Jimmy-Xuan Shen; Mingjian Wen; Matthew L. Evans; Guido Petretto; David Waroquiers; Gian-Marco Rignanese; Kristin A. Persson; et al. (J. Open Source Softw., 2024)

RNMC: kinetic Monte Carlo implementations for complex reaction networks. - Laura Zichi; Daniel Barter; Eric Sivonxay; Evan Walter Clark Spotte-Smith; Rohith Srinivaas Mohanakrishnan; Emory M. Chan; Kristin A. Persson; Samuel M. Blau (J. Open Source Softw., 2024)

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions. - Rishabh D. Guha; Santiago Vargas; Evan Walter Clark Spotte-Smith; Alexander Rizzolo Epstein; Maxwell C. Venetos; Ryan Kingsbury; Mingjian Wen; Samuel M. Blau; Kristin A. Persson (J. Chem. Inf. Model., 2025)

Large Language Models Are Innate Crystal Structure Generators. - Jingru Gan; Peichen Zhong; Yuanqi Du; Yanqiao Zhu 001; Chenru Duan; Haorui Wang; Carla P. Gomes; Kristin A. Persson; Daniel Schwalbe-Koda; Wei Wang 010 (CoRR, 2025)

Cross-functional transferability in universal machine learning interatomic potentials. - Xu Huang; Bowen Deng; Peichen Zhong; Aaron D. Kaplan; Kristin A. Persson; Gerbrand Ceder (CoRR, 2025)

System of Agentic AI for the Discovery of Metal-Organic Frameworks. - Théo Jaffrelot Inizan; Sherry Yang 001; Aaron D. Kaplan; Yen-hsu Lin; Jian Yin 030; Saber Mirzaei; Mona Abdelgaid; Ali H. Alawadhi; KwangHwan Cho; Zhiling Zheng; Ekin Dogus Cubuk; Christian Borgs; et al. (CoRR, 2025)

MP-ALOE: An r2SCAN dataset for universal machine learning interatomic potentials. - Matthew C. Kuner; Aaron D. Kaplan; Kristin A. Persson; Mark Asta; Daryl C. Chrzan (CoRR, 2025)