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RESEARCH PAPER · Chemical Science · 2021

Golem: an algorithm for robust experiment and process optimization

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

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

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Golem: an algorithm for robust experiment and process optimizationOriginalAccelerating organic solar cell material's discovery: high-throughput screening and big data129Bayesian optimization of nanoporous materials112Bayesian optimization of nanoporous materials8The BAREFOOT Optimization Framework5Bayesian optimization with adaptive surrogate models for automated experimental design138Machine learning–accelerated design and synthesis of polyelemental heterostructures126Bayesian optimization with known experimental and design constraints for chemistry applications89Toward autonomous materials research: Recent progress and future challenges61Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up35Autonomous Chemical Experiments: Challenges and Perspectives on Establishing a Self-Driving Lab294Enabling Technologies in Carbohydrate Chemistry: Automated Glycan Assembly, Flow Chemistry and Data Science28Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF31Open-Source Chromatographic Data Analysis for Reaction Optimization and Screening34How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science14Machine Learning for the Optimization of Chemical Reaction Conditions6A Review of the Applications of Artificial Intelligence in the Process Analysis and Optimization of Chemical Products8Race to the bottom: Bayesian optimisation for chemical problems76On Accelerating Substrate Optimization Using Computational Gibbs Energy Barriers: A Numerical Consideration Utilizing a Computational Data Set2JARVIS-Leaderboard: a large scale benchmark of materials design methods65ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories103From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design190Self-Driving Laboratories for Chemistry and Materials Science674Artificial intelligence and machine learning at various stages and scales of process systems engineering36OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler12COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets16A Review of Evolving Challenges in Transmission Expansion Planning Problems18Atlas: a brain for self-driving laboratories50Delegated Experimentation: Decision Authority Transfer in Closed-Loop Materials Engineering0Multi-objective reaction optimization under uncertainties using expected quantile improvement7Optimizing Phosphine Ligands for Ruthenium Catalysts in Asymmetric Hydrogenation of β-Keto Esters: The Role of Water in Activity and Selectivity2A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research5El Agente: An autonomous agent for quantum chemistry54BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty3Robust optimization of microalgae cultivation using a dual-uncertainty quantified random forest-based EGO framework0The Problem of Scientific Consensus in AI-Driven Materials Science—Conceptual Approaches: A Review Study0Artificial Intelligence Enhanced Taguchi–RSM Framework for Intelligent and Sustainable Optimization2SPACESHIP: Autonomous Mapping of Hardware-Dependent Synthesizable Space in Solution-Phase Gold Nanomaterials0Advances in automated microfluidic platforms with inline metrology and machine learning for the design, synthesis, and optimization of core–shell microstructures1

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  1. Accelerating organic solar cell material's discovery: high-throughput screening and big data

    Energy & Environmental Science · 2021-01-01

    Xabier Rodríguez‐Martínez, Enrique Pascual‐San‐José, Mariano Campoy‐Quiles

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  2. Bayesian optimization of nanoporous materials

    Molecular Systems Design & Engineering · 2021-01-01

    Aryan Deshwal, Cory M. Simon, Janardhan Rao Doppa

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  3. Bayesian optimization of nanoporous materials

    Unknown journal · 2021-07-12

    Aryan Deshwal, Cory M. Simon, Janardhan Rao Doppa

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  4. The BAREFOOT Optimization Framework

    Integrating materials and manufacturing innovation · 2021-11-10

    Richard Couperthwaite, Danial Khatamsaz, Abhilash Molkeri, Jaylen James, Ankit Srivastava, Douglas Allaire, Raymundo Arróyave

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  5. Bayesian optimization with adaptive surrogate models for automated experimental design

    npj Computational Materials · 2021-12-03

    Bowen Lei, Tanner Kirk, Anirban Bhattacharya, Debdeep Pati, Xiaoning Qian, Raymundo Arróyave, Bani K. Mallick

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  6. Machine learning–accelerated design and synthesis of polyelemental heterostructures

    Science Advances · 2021-12-22

    Carolin B. Wahl, Muratahan Aykol, Jordan H. Swisher, Joseph H. Montoya, Santosh K. Suram, Chad Alexander Mirkin

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  7. 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

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  8. 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

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  9. 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

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  10. Autonomous Chemical Experiments: Challenges and Perspectives on Establishing a Self-Driving Lab

    Accounts of Chemical Research · 2022-08-10

    Martin T. Seifrid, Robert Pollice, Andrés Aguilar‐Granda, Zamyla Morgan Chan, Kazuhiro Hotta, Cher Tian Ser, Jenya Vestfrid, Tony Wu, Alán Aspuru‐Guzik

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  11. Enabling Technologies in Carbohydrate Chemistry: Automated Glycan Assembly, Flow Chemistry and Data Science

    ChemBioChem · 2022-11-16

    Mei‐Huei Lin, Jakob B. Wolf, Eric T. Sletten, Dario Cambié, José Danglad‐Flores, Peter H. Seeberger

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  12. Using genetic algorithms to systematically improve the synthesis conditions of Al-PMOF

    Communications Chemistry · 2022-12-10

    Nency P. Domingues, Seyed Mohamad Moosavi, Leopold Talirz, Kevin Maik Jablonka, Christopher P. Ireland, Fatmah Mish Ebrahim, Berend Smit

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  13. Open-Source Chromatographic Data Analysis for Reaction Optimization and Screening

    ACS Central Science · 2023-02-09

    Christian P. Haas, Maximilian Lübbesmeyer, Edward H. Jin, Matthew A. McDonald, Brent A. Koscher, Nicolas Guimond, Laura Di Rocco, Henning Kayser, Samuel Leweke, Sebastian Niedenführ, Rachel Nicholls, Emily Greeves, David M. Barber, Julius Hillenbrand, Giulio Volpin, Klavs F. Jensen

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  14. How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science

    CHIMIA International Journal for Chemistry · 2023-02-22

    Daniel Pacheco Gutiérrez, Linnea M. Folkmann, Hermann Tribukait, Loı̈c M. Roch

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  15. Machine Learning for the Optimization of Chemical Reaction Conditions

    Unknown journal · 2023-08-31

    A. Filipa Almeida, Tiago Rodrigues

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  16. A Review of the Applications of Artificial Intelligence in the Process Analysis and Optimization of Chemical Products

    Pharmaceutical Fronts · 2023-12-01

    Runqiu Shen, Weike Su

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  17. Race to the bottom: Bayesian optimisation for chemical problems

    Digital Discovery · 2024-01-01

    Yifan Wu, Aron Walsh, Alex M. Ganose

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  18. On Accelerating Substrate Optimization Using Computational Gibbs Energy Barriers: A Numerical Consideration Utilizing a Computational Data Set

    ACS Omega · 2024-01-29

    Hiroaki Okada, Satoshi Maeda

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  19. JARVIS-Leaderboard: a large scale benchmark of materials design methods

    npj Computational Materials · 2024-05-07

    Kamal Kumar Choudhary, Daniel Wines, Kangming Li, Kevin F. Garrity, Vishu Gupta, Aldo Humberto Romero, Jaron T. Krogel, Kayahan Saritas, Addis Fuhr, Panchapakesan Ganesh, Paul R. C. Kent, Keqiang Yan, Yuchao Lin, Shuiwang Ji, Ben J. Blaiszik, Patrick Reiser, Pascal Friederich, Ankit Agrawal, Pratyush Tiwary, Eric R. Beyerle, Peter Minch, Trevor David Rhone, Ichiro Takeuchi, Robert B. Wexler, Arun Mannodi‐Kanakkithodi, Elif Ertekin, Avanish Mishra, Nithin Mathew, Mitchell A. Wood, Andrew Rohskopf, Jason R. Hattrick-Simpers, Shih‐Han Wang, Luke E. K. Achenie, Hongliang Xin, Maureen E. Williams, Adam J. Biacchi, Francesca Tavazza

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  20. ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories

    Matter · 2024-05-14

    Malcolm Sim, Mohammad Ghazi Vakili, Felix Strieth‐Kalthoff, Han Hao, Riley J. Hickman, Santiago Miret, Sergio Pablo‐García, Alán Aspuru‐Guzik

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  21. From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design

    ACS Catalysis · 2024-07-24

    Jorge Benavides-Hernández, Franck Dumeignil

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  22. Self-Driving Laboratories for Chemistry and Materials Science

    Chemical Reviews · 2024-08-13

    Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo‐García, Ella Miray Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth‐Kalthoff, Martin T. Seifrid, Alán Aspuru‐Guzik

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  23. Artificial intelligence and machine learning at various stages and scales of process systems engineering

    The Canadian Journal of Chemical Engineering · 2024-11-06

    Karthik Srinivasan, Anjana Puliyanda, Devavrat Thosar, Abhijit Bhakte, Kuldeep Singh, Prince Addo, Rajagopalan Srinivasan, Vinay Prasad

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  24. OCTOPUS: operation control system for task optimization and job parallelization via a user-optimal scheduler

    Nature Communications · 2024-11-08

    Hyuk Jun Yoo, Kwan‐Young Lee, Dong-Hun Kim, Sang Soo Han

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  25. COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets

    Cell Reports Physical Science · 2024-12-20

    Zhen Zhu Cao, Laura Falivene, Albert Poater, Bholanath Maity, Ziyung Zhang, Gentoku Takasao, Sadeed Bin Sayed, Andrea Petta, Giovanni Talarico, Romina Oliva, Luigi Cavallo

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  26. A Review of Evolving Challenges in Transmission Expansion Planning Problems

    IEEE Access · 2025-01-01

    Shengming Cao, Waqquas Bukhsh

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  27. Atlas: a brain for self-driving laboratories

    Digital Discovery · 2025-01-01

    Riley J. Hickman, Malcolm Sim, Sergio Pablo‐García, Gary Tom, Ivan Woolhouse, Han Hao, Zeqing Bao, Pauric Bannigan, Christine J. Allen, Matteo Aldeghi, Alán Aspuru‐Guzik

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  28. Delegated Experimentation: Decision Authority Transfer in Closed-Loop Materials Engineering

    Journal of Computational and Data-Driven Materials Engineering · 2025-01-01

    Natalia Petrova, Elena Stoyanova, Ivan Dimitrov

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  29. Multi-objective reaction optimization under uncertainties using expected quantile improvement

    Computers & Chemical Engineering · 2025-01-09

    Jiyizhe Zhang, Daria Semochkina, Naoto Sugisawa, David C. Woods, Alexei A. Lapkin

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  30. Optimizing Phosphine Ligands for Ruthenium Catalysts in Asymmetric Hydrogenation of β-Keto Esters: The Role of Water in Activity and Selectivity

    Molecular Catalysis · 2025-02-04

    Chasheng He, Guihua Luo, Hongliang Duan, Yuanyuan Xie, Guijun Zhang, An Su, Weike Su

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  31. A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research

    Applied Sciences · 2025-05-07

    Lukas Nolte, Sven Tomforde

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  32. El Agente: An autonomous agent for quantum chemistry

    Matter · 2025-07-01

    Yushi Zou, Austin Cheng, Abdulrahman Aldossary, Jiaru Bai, Shi Xuan Leong, Jorge A. Campos-Gonzalez-Angulo, Changhyeok Choi, Cher Tian Ser, Gary Tom, Andrew Wang, Zijian Zhang, Ilya Yakavets, Hao Han, Chris Crebolder, Varinia Bernales, Alán Aspuru‐Guzik

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  33. BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty

    Computers & Chemical Engineering · 2025-09-25

    Akshay Kudva, Joel A. Paulson

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  34. Robust optimization of microalgae cultivation using a dual-uncertainty quantified random forest-based EGO framework

    Reaction Chemistry & Engineering · 2026-01-01

    Mingqi Jiang, Y ZHAO, Zhuo Wang, Xupeng Cao, Fucheng Pan

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  35. The Problem of Scientific Consensus in AI-Driven Materials Science—Conceptual Approaches: A Review Study

    Journal of Artificial Intelligence for Materials Science · 2026-01-01

    Andrei Popescu, Mihai Ionescu, Elena Stan, Sorin Dumitrescu, Irina Pavel

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  36. Artificial Intelligence Enhanced Taguchi–RSM Framework for Intelligent and Sustainable Optimization

    Advances in computational intelligence and robotics book series · 2026-03-26

    Shalom Akhai, Mahapara Abbass

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  37. SPACESHIP: Autonomous Mapping of Hardware-Dependent Synthesizable Space in Solution-Phase Gold Nanomaterials

    Journal of the American Chemical Society · 2026-04-29

    Nayeon Kim, Hyuk Jun Yoo, Daeho Kim, Heeseung Lee, Chang Seop Hong, Sang Soo Han

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  38. Advances in automated microfluidic platforms with inline metrology and machine learning for the design, synthesis, and optimization of core–shell microstructures

    Materials Today Chemistry · 2026-08-21

    Vijila Chellappan, Keyu Chen, Brindha Ramasubramanian, Jiaming You, Sourav Mitra, G. Vinitha, Maciej Koperski

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