BetaCitation Atlas

RESEARCH PAPER · Matter · 2021

Autonomous experimentation systems for materials development: A community perspective

Eric A. Stach, Brian DeCost, Aaron Gilad Kusne, Jason R. Hattrick-Simpers, Keith A. Brown, Kristofer G. Reyes, Joshua Schrier, Simon J. L. Billinge, Tonio Buonassisi, Ian T Foster, Carla Pedro Gomes, John M. Gregoire, Apurva Mehta, Joseph H. Montoya, Elsa Olivetti, Chiwoo Park, Eli Rotenberg, Semion K. Saikin, Sylvia Smullin, Valentin Stanev, Benji Maruyama

Read original paper ↗

See where this research leads.

397 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Autonomous experimentation systems for materials development: A community perspectiveOriginalBayesian optimization of nanoporous materials112Sequential adaptive design for jump regression estimation11Towards Predictive Synthesis of Inorganic Materials Using Network Science5NGenE 2021: Electrochemistry Is Everywhere18Knowledge extraction in catalysis utilizing design of experiments and machine learning29A Conceptual Theory of Model-Science Interface: Where AI Outputs Become Experimental Inputs0Algorithmic Screening Frontiers: How Model Priors Reshape Searchable Materials Space0Bayesian optimization with known experimental and design constraints for chemistry applications89Benchmarking active learning strategies for materials optimization and discovery48Machine learning enabling high-throughput and remote operations at large-scale user facilities16Machine learning for design principles for single atom catalysts towards electrochemical reactions116Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective46The Compression–Fidelity Trade-Off in Materials Embedding Architectures0The resolution- vs. -accuracy dilemma in machine learning modeling of electronic excitation spectra16The Treatment of Absence and Null Results in Materials Machine Learning Literature: A Review Study0Toward an Autonomous Workflow for Single Crystal Neutron Diffraction1Why Invariance Becomes a Liability: Failure Modes of Rotationally Invariant GNNs for Anisotropic Elastic Constants0From Platform to Knowledge Graph: Evolution of Laboratory Automation108Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning32Toward autonomous materials research: Recent progress and future challenges61Active meta-learning for predicting and selecting perovskite crystallization experiments24The materials tetrahedron has a “digital twin”34High-throughput workflows in the service of (photo)electrocatalysis research14Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping10Quantum Materials Manufacturing5Data-Driven Design and Autonomous Experimentation in Soft and Biological Materials Engineering42Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries72Autonomous Nanocrystal Doping by Self‐Driving Fluidic Micro‐Processors20Agents for sequential learning using multiple-fidelity data38Recent advances and applications of deep learning methods in materials science1161The case for data science in experimental chemistry: examples and recommendations83On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning55Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up35MODEL, GUESS, CHECK: Wordle as a primer on active learning for materials research15Sidekick: A Low-Cost Open-Source 3D-printed liquid dispensing robot34Reaching critical MASS: Crowdsourcing designs for the next generation of materials acceleration platforms29An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics45Towards Automated Design of Corrosion Resistant Alloy Coatings with an Autonomous Scanning Droplet Cell18A Framework for Closed-Loop Optimization of an Automated Mechanical Serial-Sectioning System via Run-to-Run Control as Applied to a Robo-Met.3D3A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys33Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models7Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models5Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery552An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms1Accelerated optochemical engineering solutions to CO2 photocatalysis for a sustainable future72Human- and machine-centred designs of molecules and materials for sustainability and decarbonization137An object-oriented framework to enable workflow evolution across materials acceleration platforms20Autonomous (AI-driven) materials science23Biologic formulation in a self-driving biomaterials lab19Computation-informed optimization of Ni(PyC)2 functionalization for noble gas separations12Deep learning for electron and scanning probe microscopy: From materials design to atomic fabrication36The LEGOLAS Kit: A low-cost robot science kit for education with symbolic regression for hypothesis discovery and validation19Brokering between tenants for an international materials acceleration platform5Scanning probes as a materials automation platform with extremely miniaturized samples8Robotic Powder Grinding with a Soft Jig for Laboratory Automation in Material Science19A perspective on Bayesian methods applied to materials discovery and design47Networks and interfaces as catalysts for polymer materials innovation10A Framework for the Optimal Selection of High-Throughput Data Collection Workflows by Autonomous Experimentation Systems6Artificial intelligence for materials research at extremes20Delivering real-time multi-modal materials analysis with enterprise beamlines5Materials for extreme environments314Structural element shaping on a plate in the manufacture of a hybrid product from aluminum alloy using WAAM technology4Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation118High-Throughput Electrochemistry to Study Materials Degradation in Extreme Environments11A catalyst acceleration platform toward realizing the energy transition2What is a minimal working example for a self-driving laboratory?49Forecasting of in situ electron energy loss spectroscopy18Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces15Advanced supramolecular design for direct ink writing of soft materials86An open-source environmental chamber for materials-stability testing using an optical proxy13Bayesian optimisation for efficient material discovery: a mini review49By how much can closed-loop frameworks accelerate computational materials discovery?21Computational and Data-Driven Materials Engineering: High-Throughput Computational Screening Platforms, Workflows, and Discovery Outcomes0Domain-specific chatbots for science using embeddings29Driving school for self-driving labs17Equipping data-driven experiment planning for Self-driving Laboratories with semantic memory: case studies of transfer learning in chemical reaction optimization33Human-in-The-Loop for Bayesian Autonomous Materials Phase Mapping0Integrating autonomy into automated research platforms32Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations41Multimodal, Physics-Informed Machine Learning for Accelerated Materials Design and Discovery0Orchestrating nimble experiments across interconnected labs37Realizing the cooking recipe of materials synthesis through large language models14Screening for electrically conductive defects in thin functional films using electrochemiluminescence1Simulation Priors in Machine Learning Materials Models: Hidden Physics Assumptions0The materials experiment knowledge graph25The rise of automated curiosity-driven discoveries in chemistry20Towards a modular architecture for science factories31Towards Pareto optimal high entropy hydrides via data-driven materials discovery43What is missing in autonomous discovery: open challenges for the community44Re-envisioning the design of nanomedicines: harnessing automation and artificial intelligence43Emerging Trends in Machine Learning: A Polymer Perspective187Globus automation services: Research process automation across the space–time continuum38Perspective: Machine learning in experimental solid mechanics68Mathematical nuances of Gaussian process-driven autonomous experimentation13Next-generation intelligent laboratories for materials design and manufacturing25Role of AI in experimental materials science42Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems112Autonomous and online detection of dry areas on a boiling surface using deep learning and infrared thermometry20Automated phase segmentation and quantification of high-resolution TEM image for alloy design8Self-driving laboratories: A paradigm shift in nanomedicine development84Combinatorial synthesis for AI-driven materials discovery114AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning215Accelerated Design of Architected Materials with Multifidelity Bayesian Optimization6Autonomous experimental systems in materials science22Stoichiometric growth of SrTiO3 films via Bayesian optimization with adaptive prior mean9A critical examination of robustness and generalizability of machine learning prediction of materials properties146ET-AL: Entropy-targeted active learning for bias mitigation in materials data30Scalable multi-agent lab framework for lab optimization33Materials Informatics Tools in the Context of Bio-Inspired Material Mechanics17Statistical and machine learning-based durability-testing strategies for energy storage26Physics-Informed Bayesian learning of electrohydrodynamic polymer jet printing dynamics24Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops24Machine learning for materials science: Barriers to broader adoption31Autonomous x-ray scattering26Tuning Bayesian optimization for materials synthesis: simulating two- and three-dimensional cases10Data Processing and Machine Learning0Future Vision0Olympus, enhanced: benchmarking mixed-parameter and multi-objective optimization in chemistry and materials science8Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use37Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use6Materials research in artificial intelligence era0Transforming characterization data into information in the case of perovskite solar cells8Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission26Using 3D printing as a research tool for materials discovery12The Power of Automation in Polymer Chemistry: Precision Synthesis of Multiblock Copolymers with Block Sequence Control24CRESt – Copilot for Real-world Experimental Scientist6Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review157A hybrid metaheuristic and computer vision approach to closed-loop calibration of fused deposition modeling 3D printers16Autonomous experiments using active learning and AI61Photocatalytic CO2 reduction834A Modern Twist on an Old Measurement: Using Laboratory Automation and Data Science to Determine the Solubility Product of Lead Iodide2Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques35Innovative Strategies for Integrating Technology into Agricultural Programmes at Technical and Vocational Colleges1Unleashing the Power of Artificial Intelligence in Materials Design179Autonomous Exploration of an Unexpected Electrode Material for Lithium Batteries11Review of Low-cost Self-driving Laboratories: The "Frugal Twin" Concept3Leveraging Interpretable Features and Clustering Agreements for Assistive Materials Discovery1In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science99Revolutionizing drug formulation development: The increasing impact of machine learning128Robotic Powder Grinding with Audio-Visual Feedback for Laboratory Automation in Materials Science4Closed-loop superconducting materials discovery34CRESt – Copilot for Real-world Experimental Scientist4CRESt – Copilot for Real-world Experimental Scientist2Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning28Exploiting redundancy in large materials datasets for efficient machine learning with less data118Exploring Benchmarks for Self-Driving Labs using Color Matching4CRESt – Copilot for Real-world Experimental Scientist9Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap7Accelerated chemical science with AI86Diversifying self-assembled phases in block copolymer thin films via blending8

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

397 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. Bayesian optimization of nanoporous materials

    Molecular Systems Design & Engineering · 2021-01-01

    Aryan Deshwal, Cory M. Simon, Janardhan Rao Doppa

    Read original paper ↗ ·

  2. Sequential adaptive design for jump regression estimation

    IISE Transactions · 2021-12-03

    Chiwoo Park, Peihua Qiu, Jennifer Carpena‐Núñez, Rahul S. Rao, Michael A. Susner, Benji Maruyama

    Read original paper ↗ ·

  3. Towards Predictive Synthesis of Inorganic Materials Using Network Science

    Frontiers in Chemistry · 2021-12-21

    Alex Aziz, Javier Carrasco

    Read original paper ↗ ·

  4. NGenE 2021: Electrochemistry Is Everywhere

    ACS Energy Letters · 2021-12-22

    Jordi Cabana, Thomas Aláan, George W. Crabtree, Marta C. Hatzell, Karthish Manthiram, Daniel A. Steingart, Iryna V. Zenyuk, Feng Jiao, Aleksandra Vojvodić, Jenny Y. Yang, Nitash P. Balsara, Kristin Aslaug Persson, Donald J. Siegel, Christy L. Haynes, Janine Mauzeroll, Mei Shen, B. Jill Venton, Nina Balke, Joaquín Rodríguez‐López, Debra R. Rolison, Reza Shahbazian‐Yassar, Venkat N. Srinivasan, Santanu Chaudhuri, Adrien Couet, Jason R. Hattrick-Simpers

    Read original paper ↗ ·

  5. Knowledge extraction in catalysis utilizing design of experiments and machine learning

    Current Opinion in Chemical Engineering · 2021-12-29

    Blake MacQueen, Rasika Jayarathna, Jochen A. Lauterbach

    Read original paper ↗ ·

  6. A Conceptual Theory of Model-Science Interface: Where AI Outputs Become Experimental Inputs

    Journal of Artificial Intelligence for Materials Science · 2022-01-01

    Wei Chen, Li Zhang

    Read original paper ↗ ·

  7. Algorithmic Screening Frontiers: How Model Priors Reshape Searchable Materials Space

    Journal of Computational and Data-Driven Materials Engineering · 2022-01-01

    Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich

    Read original paper ↗ ·

  8. Bayesian optimization with known experimental and design constraints for chemistry applications

    Digital Discovery · 2022-01-01

    Riley J. Hickman, Matteo Aldeghi, Florian Häse, Alán Aspuru‐Guzik

    Read original paper ↗ ·

  9. Benchmarking active learning strategies for materials optimization and discovery

    Oxford Open Materials Science · 2022-01-01

    Alex Wang, Haotong Liang, Austin McDannald, Ichiro Takeuchi, Aaron Gilad Kusne

    Read original paper ↗ ·

  10. Machine learning enabling high-throughput and remote operations at large-scale user facilities

    Digital Discovery · 2022-01-01

    Tatiana Konstantinova, Phillip M. Maffettone, Bruce Ravel, Stuart I. Campbell, Andi Barbour, Daniel Olds

    Read original paper ↗ ·

  11. Machine learning for design principles for single atom catalysts towards electrochemical reactions

    Journal of Materials Chemistry A · 2022-01-01

    Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, Patrick Ryan Galligan, Hoilun Wong, Zhenjing Liu, Hongwei Liu, Yuting Cai, William A. Goddard, Zhengtang Luo

    Read original paper ↗ ·

  12. Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective

    Catalysis Science & Technology · 2022-01-01

    Annette Trunschke

    Read original paper ↗ ·

  13. The Compression–Fidelity Trade-Off in Materials Embedding Architectures

    Journal of Computational and Data-Driven Materials Engineering · 2022-01-01

    Claire Dupont, Julien Martin

    Read original paper ↗ ·

  14. The resolution- vs. -accuracy dilemma in machine learning modeling of electronic excitation spectra

    Digital Discovery · 2022-01-01

    Prakriti Kayastha, Sabyasachi Chakraborty, Raghunathan Ramakrishnan

    Read original paper ↗ ·

  15. The Treatment of Absence and Null Results in Materials Machine Learning Literature: A Review Study

    Journal of Artificial Intelligence for Materials Science · 2022-01-01

    Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich

    Read original paper ↗ ·

  16. Toward an Autonomous Workflow for Single Crystal Neutron Diffraction

    Communications in computer and information science · 2022-01-01

    Junqi Yin, Guannan Zhang, Huibo B. Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang

    Read original paper ↗ ·

  17. Why Invariance Becomes a Liability: Failure Modes of Rotationally Invariant GNNs for Anisotropic Elastic Constants

    Journal of Computational and Data-Driven Materials Engineering · 2022-01-01

    Michael Turner, Sophia Nguyen, David Clark, Emma Wilson

    Read original paper ↗ ·

  18. From Platform to Knowledge Graph: Evolution of Laboratory Automation

    JACS Au · 2022-01-10

    Jiaru Bai, Liwei Cao, Sebastian Mosbach, Jethro Akroyd, Alexei A. Lapkin, Markus Kraft

    Read original paper ↗ ·

  19. Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning

    Chemistry of Materials · 2022-01-12

    Zhi Li, Philip W. Nega, Mansoor Ani Najeeb, Chaochao Dun, Mat­thias Zeller, Jeffrey J. Urban, Wissam Abdo Saidi, Joshua Schrier, Alexander J. Norquist, Emory M. Chan

    Read original paper ↗ ·

  20. Toward autonomous materials research: Recent progress and future challenges

    Applied Physics Reviews · 2022-01-13

    Joseph H. Montoya, Muratahan Aykol, Abraham Anapolsky, Chirranjeevi Balaji Gopal, Patrick K. Herring, Jens S. Hummelshøj, Linda Hung, Ha-Kyung Kwon, Daniel Schweigert, Shijing Sun, Santosh K. Suram, Steven B. Torrisi, Amalie Trewartha, Brian D. Storey

    Read original paper ↗ ·

  21. Active meta-learning for predicting and selecting perovskite crystallization experiments

    The Journal of Chemical Physics · 2022-01-23

    Venkateswaran Shekar, Gareth Nicholas, Mansoor Ani Najeeb, Margaret Zeile, Vincent Yu, Xiaorong Wang, Dylan Slack, Zhi Li, Philip W. Nega, Emory M. Chan, Alexander J. Norquist, Joshua Schrier, Sorelle A. Friedler

    Read original paper ↗ ·

  22. The materials tetrahedron has a “digital twin”

    MRS Bulletin · 2022-02-01

    Michael E. Deagen, L. Catherine Brinson, Richard A. Vaia, Linda S. Schadler

    Read original paper ↗ ·

  23. High-throughput workflows in the service of (photo)electrocatalysis research

    Trends in Chemistry · 2022-02-05

    Attila Kormányos, Ken J. Jenewein, Serhiy Cherevko

    Read original paper ↗ ·

  24. Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

    Frontiers in Physics · 2022-02-16

    Aaron Gilad Kusne, Austin McDannald, Brian DeCost, Corey Oses, Cormac Toher, Stefano Curtarolo A, Apurva Mehta, Ichiro Takeuchi

    Read original paper ↗ ·

  25. Quantum Materials Manufacturing

    Advanced Materials · 2022-02-23

    Nicholas R. Glavin, Pulickel Madhavapanicker Ajayan, Swastik Kar

    Read original paper ↗ ·

  26. Data-Driven Design and Autonomous Experimentation in Soft and Biological Materials Engineering

    Annual Review of Chemical and Biomolecular Engineering · 2022-03-02

    Andrew L. Ferguson, Keith A. Brown

    Read original paper ↗ ·

  27. Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

    Advanced Materials · 2022-03-12

    Maxim A Ziatdinov, Yongtao Liu, Anna N. Morozovska, Eugene А. Eliseev, Xiaohang Zhang, Ichiro Takeuchi, Sergei V. Kalinin

    Read original paper ↗ ·

  28. Autonomous Nanocrystal Doping by Self‐Driving Fluidic Micro‐Processors

    Advanced Intelligent Systems · 2022-03-13

    Fazel Bateni, Robert W. Epps, Kameel Antami, Rokas Dargis, Jeffery A. Bennett, Kristofer G. Reyes, Milad Abolhasani

    Read original paper ↗ ·

  29. Agents for sequential learning using multiple-fidelity data

    Scientific Reports · 2022-03-18

    Aini Palizhati, Steven B. Torrisi, Muratahan Aykol, Santosh K. Suram, Jens S. Hummelshøj, Joseph H. Montoya

    Read original paper ↗ ·

  30. Recent advances and applications of deep learning methods in materials science

    npj Computational Materials · 2022-04-05

    Kamal Kumar Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth A. Holm, Shyue Ping Ong, Chris M. Wolverton

    Read original paper ↗ ·

  31. The case for data science in experimental chemistry: examples and recommendations

    Nature Reviews Chemistry · 2022-04-21

    Junko Yano, Kelly J. Gaffney, John M. Gregoire, Linda Hung, A. Ourmazd, Joshua Schrier, James A. Sethian, Francesca Maria Toma

    Read original paper ↗ ·

  32. On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning

    Applied Physics Reviews · 2022-04-29

    Austin McDannald, Matthias Frontzek, Andrei T. Savici, Mathieu Doucet, Efrain E. Rodriguez, Kate Meuse, Jessica Opsahl‐Ong, Daniel V. Samarov, Ichiro Takeuchi, William Ratcliff, Aaron Gilad Kusne

    Read original paper ↗ ·

  33. Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up

    Matter · 2022-05-01

    Rishi E. Kumar, Armi Tiihonen, Shijing Sun, David P. Fenning, Zhe Liu, Tonio Buonassisi

    Read original paper ↗ ·

  34. MODEL, GUESS, CHECK: Wordle as a primer on active learning for materials research

    npj Computational Materials · 2022-05-02

    Keith A. Brown

    Read original paper ↗ ·

  35. Sidekick: A Low-Cost Open-Source 3D-printed liquid dispensing robot

    HardwareX · 2022-05-26

    Rodolfo Keesey, Robert J. LeSuer, Joshua Schrier

    Read original paper ↗ ·

  36. Reaching critical MASS: Crowdsourcing designs for the next generation of materials acceleration platforms

    Matter · 2022-06-08

    Martin T. Seifrid, Jason R. Hattrick-Simpers, Alán Aspuru‐Guzik, Tom Kalil, Steven W. Cranford

    Read original paper ↗ ·

  37. An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics

    Microscopy and Microanalysis · 2022-06-10

    Matthew J. Olszta, Derek Hopkins, Kevin R. Fiedler, Marjolein T. Oostrom, Sarah M. Akers, Steven R. Spurgeon

    Read original paper ↗ ·

  38. Towards Automated Design of Corrosion Resistant Alloy Coatings with an Autonomous Scanning Droplet Cell

    JOM · 2022-06-21

    Brian DeCost, Howie Joress, Suchismita Sarker, Apurva Mehta, Jason R. Hattrick-Simpers

    Read original paper ↗ ·

  39. A Framework for Closed-Loop Optimization of an Automated Mechanical Serial-Sectioning System via Run-to-Run Control as Applied to a Robo-Met.3D

    JOM · 2022-06-22

    Damian Gallegos-Patterson, Kendric R. Ortiz, Claus Danielson, Jonathan D Madison, Andrew T. Polonsky

    Read original paper ↗ ·

  40. A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys

    Scientific Reports · 2022-07-08

    Kyungtae Lee, Mukil V. Ayyasamy, Yangfeng Ji, Prasanna V. Balachandran

    Read original paper ↗ ·

  41. Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models

    ChemRxiv · 2022-07-19

    Venkateswaran Shekar, Vincent Yu, Benjamin J. Garcia, David Benjamin Gordon, Gemma E. Moran, David M. Blei, Loı̈c M. Roch, Alberto García-Durán, Mansoor Ani Najeeb, Margaret Zeile, Philip W. Nega, Zhi Li, Mina A. Kim, Emory M. Chan, Alexander J. Norquist, Sorelle A. Friedler, Joshua Schrier

    Read original paper ↗ ·

  42. Serendipity based recommender system for perovskites material discovery: balancing exploration and exploitation across multiple models

    ChemRxiv · 2022-07-20

    Venkateswaran Shekar, Vincent Yu, Benjamin J. Garcia, David Benjamin Gordon, Gemma E. Moran, David M. Blei, Loı̈c M. Roch, Alberto García-Durán, Mansoor Ani Najeeb, Margaret Zeile, Philip W. Nega, Zhi Li, Mina A. Kim, Emory M. Chan, Alexander J. Norquist, Sorelle A. Friedler, Joshua Schrier

    Read original paper ↗ ·

  43. Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

    Chemical Reviews · 2022-07-21

    Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler, Rachel A. Caruso

    Read original paper ↗ ·

  44. An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms

    ChemRxiv · 2022-07-27

    Chang Jie Leong, Andre K. Y. Low, Jose Recatala‐Gomez, Pablo Quijano Velasco, Eléonore Vissol-Gaudin, Jin Da Tan, Balamurugan Ramalingam, Riko I Made, Shreyas Dinesh Pethe, Saumya Sebastian, Yee-Fun Lim, Zi Hui Jonathan Khoo, Yang Bai, Jayce Jian Wei Cheng, Kedar Hippalgaonkar

    Read original paper ↗ ·

  45. Accelerated optochemical engineering solutions to CO2 photocatalysis for a sustainable future

    Matter · 2022-08-23

    Geoffrey Alan Ozin

    Read original paper ↗ ·

  46. Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

    Nature Reviews Materials · 2022-08-24

    Jiayu Peng, Daniel Schwalbe‐Koda, Karthik Akkiraju, Tian Xie, Livia Giordano, Yang Yu, C. John Eom, Jaclyn R. Lunger, Daniel J. Zheng, Reshma R. Rao, Sokseiha Muy, Jeffrey C. Grossman, Karsten Reuter, Rafael Gómez‐Bombarelli, Yang Shao‐Horn

    Read original paper ↗ ·

  47. An object-oriented framework to enable workflow evolution across materials acceleration platforms

    Matter · 2022-08-31

    Chang Jie Leong, Andre K. Y. Low, Jose Recatala‐Gomez, Pablo Quijano Velasco, Eléonore Vissol-Gaudin, Jin Da Tan, Balamurugan Ramalingam, Riko I Made, Shreyas Dinesh Pethe, Saumya Sebastian, Yee‐Fun Lim, Zi Hui Jonathan Khoo, Yang Bai, Jayce Jian Wei Cheng, Kedar Hippalgaonkar

    Read original paper ↗ ·

  48. Autonomous (AI-driven) materials science

    Applied Physics Reviews · 2022-09-01

    Martin L. Green, Benji Maruyama, Joshua Schrier

    Read original paper ↗ ·

  49. Biologic formulation in a self-driving biomaterials lab

    Cell Reports Physical Science · 2022-09-01

    Matthew Tamasi, Adam J. Gormley

    Read original paper ↗ ·

  50. Computation-informed optimization of Ni(PyC)2 functionalization for noble gas separations

    Cell Reports Physical Science · 2022-09-01

    Nickolas Gantzler, Min‐Bum Kim, Alexander J. Robinson, Maxwell W. Terban, Sanjit Ghose, Robert E. Dinnebier, Arthur H. P. York, Davide Tiana, Cory M. Simon, Praveen K. Thallapally

    Read original paper ↗ ·
More citing papers →
Citation Atlas · A map of research, not a ranking.