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Self-driving laboratories in Korea: a new era of autonomous discovery
Jiho Hwang, Seongmin Kim, Sooyoun Lim, Juhwan Kim, Seungwoo Lee, Seonghyeon Min, Jisoo Song, Jeongwook Lim, Seonghun Hong, Jin-Ha Hwang, Youn-Suk Choi, Dong-Hwa Seo, Sang Soo Han, KangGeon Kim, Su-Hyun Yoo, Jungho Shin, Jang Wook Choi, Jaewook Nam, Jungwon Park, Jaeyune Ryu and Yousung Jung
Digital Discovery, 2026, 5, 1968
DOI: 10.1039/D6DD00024J

Autonomous robotic experimentation system for powder X-ray diffraction
Yuto Yotsumoto, Yusaku Nakajima, Ryusei Takamoto, Yasuo Takeichi and Kanta Ono
Digital Discovery, 2024, 3, 2523
DOI: 10.1039/D4DD00190G

Variable pathlength cell for internal data validation in computer vision
Xiangyu Liu, Namita Sharma, Aldrik H. Velders and Vittorio Saggiomo
Digital Discovery, 2025, 4, 3238
DOI: 10.1039/D5DD00245A

Robotically automated 3D printing and testing of thermoplastic material specimens
Miguel Hernández-del-Valle, Christina Schenk, Lucía Echevarría-Pastrana, Burcu Ozdemir, Enrique Dios-Lázaro, Jorge Ilarraza-Zuazo, De-Yi Wang and Maciej Haranczyk
Digital Discovery, 2023, 2, 1969
DOI: 10.1039/D3DD00141E

Toward self-driving laboratory 2.0 for chemistry and materials discovery
Heeseung Lee, Hyuk Jun Yoo, Hye Su Jang, Byeongho Park, Yang Jeong Park and Sang Soo Han
Mater. Horiz., 2026, 13, 4712
DOI: 10.1039/D5MH01984B

ChemGymRL: A customizable interactive framework for reinforcement learning for digital chemistry
Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Mark Baula, Nouha Chatti, Amanuel Dawit, Xinkai Li, Nicholas Paquin, Mitchell Shahen, Zihan Yang, Colin Bellinger, Mark Crowley and Isaac Tamblyn
Digital Discovery, 2024, 3, 742
DOI: 10.1039/D3DD00183K

Democratizing self-driving labs: advances in low-cost 3D printing for laboratory automation
Sayan Doloi, Maloy Das, Yujia Li, Zen Han Cho, Xingchi Xiao, John V. Hanna, Matthew Osvaldo and Leonard Ng Wei Tat
Digital Discovery, 2025, 4, 1685
DOI: 10.1039/D4DD00411F

Bayesian optimisation for efficient material discovery: a mini review
Yimeng Jin and Priyank V. Kumar
Nanoscale, 2023, 15, 10975
DOI: 10.1039/D2NR07147A

AMPERE-2: an open-hardware, robotic platform for automated electrodeposition and electrochemical validation
Nis Fisker-Bødker, Daniel Persaud, Yang Bai, Mark Kozdras, Tejs Vegge, Jason Hattrick-Simpers and Jin Hyun Chang
Digital Discovery, 2025, 4, 2491
DOI: 10.1039/D5DD00180C

Driving school for self-driving labs
Kelsey L. Snapp and Keith A. Brown
Digital Discovery, 2023, 2, 1620
DOI: 10.1039/D3DD00150D

The decade of artificial intelligence in chemistry and materials
Alán Aspuru-Guzik
Digital Discovery, 2023, 2, 10
DOI: 10.1039/D3DD90001K

A revolutionary paradigm in chemistry and materials science research: self-driving laboratories
Jiaxuan Qiu, Liwen Zhu, Zhe Feng, Zhongzhong Luo and Longlu Wang
Chem. Commun., 2025, 61, 10026
DOI: 10.1039/D5CC01959A

Active learning high coverage sets of complementary reaction conditions
Sofia L. Sivilotti, David M. Friday and Nicholas E. Jackson
Digital Discovery, 2025, 4, 846
DOI: 10.1039/D4DD00365A

InSpecLearn4SDL: interpretable spectral features predict conductivity in self-driving doped conjugated polymer labs
Ankush Kumar Mishra, Jacob P. Mauthe, Nicholas Luke, Aram Amassian and Baskar Ganapathysubramanian
Digital Discovery, 2026, 5, 1925
DOI: 10.1039/D5DD00479A

Integrating autonomy into automated research platforms
Richard B. Canty, Brent A. Koscher, Matthew A. McDonald and Klavs F. Jensen
Digital Discovery, 2023, 2, 1259
DOI: 10.1039/D3DD00135K

Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept
Stanley Lo, Sterling G. Baird, Joshua Schrier, Ben Blaiszik, Nessa Carson, Ian Foster, Andrés Aguilar-Granda, Sergei V. Kalinin, Benji Maruyama, Maria Politi, Helen Tran, Taylor D. Sparks and Alán Aspuru-Guzik
Digital Discovery, 2024, 3, 842
DOI: 10.1039/D3DD00223C

SALSA: a low-cost self-driving lab modular add-on for salt solubility assessment for battery electrolytes
Tianyi Zhang, Hongyi Lin, Yuhan Chen and Venkatasubramanian Viswanathan
Digital Discovery, 2026, 5, 1881
DOI: 10.1039/D5DD00516G

Leveraging large language model and social network service for automation in scanning probe microscopy
Zhuo Diao, Hayato Yamashita and Masayuki Abe
Meas. Sci. Technol., 2025, 36, 047001
DOI: 10.1088/1361-6501/adbf3a

Beyond Combinatorial Materials Science: The 100 Prisoners Problem
J. Elliott Fowler, Matthew A. Kottwitz, Nat Trask and Rémi Dingreville
Integr Mater Manuf Innov, 2024, 13, 83
DOI: 10.1007/s40192-023-00330-6

Self-driving laboratories to autonomously navigate the protein fitness landscape
Jacob T. Rapp, Bennett J. Bremer and Philip A. Romero
Nat Chem Eng, 2024, 1, 97
DOI: 10.1038/s44286-023-00002-4

Role of AI in experimental materials science
Milad Abolhasani and Keith A. Brown
MRS Bulletin, 2023, 48, 134
DOI: 10.1557/s43577-023-00482-y

Real-time experiment-theory closed-loop interaction for autonomous materials science
Haotong Liang, Chuangye Wang, Heshan Yu, Dylan Kirsch, Rohit Pant, Austin McDannald, A. Gilad Kusne, Ji-Cheng Zhao and Ichiro Takeuchi
Sci. Adv., 2025, 11
DOI: 10.1126/sciadv.adu7426

Virtual laboratories: transforming research with AI
Arto Klami, Theo Damoulas, Ola Engkvist, Patrick Rinke and Samuel Kaski
DCE, 2024, 5
DOI: 10.1017/dce.2024.15

In-Line Molar Mass Determination in Semidilute Polymer Solutions
Johann L. Rapp, Eric P. Weeda, Ryan Sayko, Nick Legaux, Foad Vashahi, Sergei S. Sheiko, Andrey V. Dobrynin and Frank A. Leibfarth
Macromolecules, 2026, 59, 4039
DOI: 10.1021/acs.macromol.5c03393

Accelerated Emergence of Self-Driving Laboratories for Accelerating Materials Discovery
Amanda K. Brown, Abhishek Soni, Daniel Lin and Curtis P. Berlinguette
ACS Cent. Sci., 2026, 12, 300
DOI: 10.1021/acscentsci.5c01624

Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning
Johann L. Rapp, Dylan M. Anstine, Filipp Gusev, Filipp Nikitin, Kelly H. Yun, Meredith A. Borden, Vittal Bhat, Olexandr Isayev and Frank A. Leibfarth
Angewandte Chemie, 2025, 137
DOI: 10.1002/ange.202513147

AI‐Driven Advances in Sustainable Materials for Green Energy: From Innovation to Lifecycle Management
Yuehui Xian, Cheng Li, Yangyang Xu, Yumei Zhou and Dezhen Xue
SusMat, 2025, 5
DOI: 10.1002/sus2.70030

Experimental mechanician for plate lattice metamaterial discovery
Songtao Hu, Haoran Li, Wenhui Lu, Tian Xie, Xijia Ding, Xiantong Zhang, Xi Shi, Zhike Peng and Xiaobao Cao
Nat Commun, 2026, 17
DOI: 10.1038/s41467-026-70675-x

Collecting diverse near-optimal samples via nested Thompson sampling
Ryosuke Shibukawa, Shoichi Matsuda, Kazuha Nakamura, Ryo Tamura and Koji Tsuda
npj Comput Mater, 2026, 12
DOI: 10.1038/s41524-026-02067-0

Using 3D printing as a research tool for materials discovery
Ronald A. Smaldone, Keith A. Brown, Grace X. Gu and Chenfeng Ke
Device, 2023, 1, 100014
DOI: 10.1016/j.device.2023.100014

Self-Driving Laboratories for Chemistry and Materials Science
Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo-García, Ella M. Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth-Kalthoff, Martin Seifrid and Alán Aspuru-Guzik
Chem. Rev., 2024, 124, 9633
DOI: 10.1021/acs.chemrev.4c00055

Bioinspired materials for underwater adhesion with pathways to switchability
Chanhong Lee, Huiqi Shi, Jiyoung Jung, Bowen Zheng, Kan Wang, Ravi Tutika, Rong Long, Bruce P. Lee, Grace X. Gu and Michael D. Bartlett
Cell Reports Physical Science, 2023, 4, 101597
DOI: 10.1016/j.xcrp.2023.101597

Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning
Johann L. Rapp, Dylan M. Anstine, Filipp Gusev, Filipp Nikitin, Kelly H. Yun, Meredith A. Borden, Vittal Bhat, Olexandr Isayev and Frank A. Leibfarth
Angew Chem Int Ed, 2025, 64
DOI: 10.1002/anie.202513147

Autonomous Chemical Experiments: Challenges and Perspectives on Establishing a Self-Driving Lab
Martin Seifrid, Robert Pollice, Andrés Aguilar-Granda, Zamyla Morgan Chan, Kazuhiro Hotta, Cher Tian Ser, Jenya Vestfrid, Tony C. Wu and Alán Aspuru-Guzik
Acc. Chem. Res., 2022, 55, 2454
DOI: 10.1021/acs.accounts.2c00220

Self‐Driving Lab for Solid‐Phase Extraction Process Optimization and Application to Nucleic Acid Purification
Sebastian Putz, Jonathan Döttling, Tim Ballweg, Andre Tschöpe, Vitaly Biniyaminov and Matthias Franzreb
Advanced Intelligent Systems, 2025, 7
DOI: 10.1002/aisy.202400564

AP‐Lab: An AI‐Driven Autonomous Pilot‐Scale Platform Bridging Materials Discovery and Industrial Manufacturing
Zhan‐Long Wang, Zhifen Ma, Wenxing Song, Guolai Jiang, Boshi Jiang, Mingyang Jiang, Weiliang Shu, Bing Wang, Zhiyuan Wan, Shengyong Geng, Zhen Zhao, Wenhua Zhou and Xue‐Feng Yu
Advanced Science, 2026, 13
DOI: 10.1002/advs.74293

Automated membrane characterization: In-situ monitoring of the permeate and retentate solutions using a 3D printed permeate probe device
Jonathan Aubuchon Ouimet, Faraj Al-Badani, Xinhong Liu, Laurianne Lair, Zachary W. Muetzel, Alexander W. Dowling and William A. Phillip
Journal of Membrane Science Letters, 2024, 4, 100087
DOI: 10.1016/j.memlet.2024.100087

Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals
Jinge Xu, Christopher H. J. Moran, Arup Ghorai, Fazel Bateni, Jeffrey A. Bennett, Nikolai Mukhin, Koray Latif, Andrew Cahn, Pragyan Jha, Fernando Delgado Licona, Sina Sadeghi, Lior Politi and Milad Abolhasani
Nat Commun, 2025, 16
DOI: 10.1038/s41467-025-63209-4

Autonomous ‘self-driving’ laboratories: a review of technology and policy implications
Alexander V. Tobias and Adam Wahab
R. Soc. Open Sci., 2025, 12
DOI: 10.1098/rsos.250646

Bayesian Optimization in Polymer Modeling: From Coarse‐Graining Foundations to Autonomous Inverse Design
Zakiya Shireen
Macro Theory & Simulations, 2026, 35
DOI: 10.1002/mats.202500081

Perspectives for self-driving labs in synthetic biology
Hector G Martin, Tijana Radivojevic, Jeremy Zucker, Kristofer Bouchard, Jess Sustarich, Sean Peisert, Dan Arnold, Nathan Hillson, Gyorgy Babnigg, Jose M Marti, Christopher J Mungall, Gregg T Beckham, Lucas Waldburger, James Carothers, ShivShankar Sundaram, Deb Agarwal, Blake A Simmons, Tyler Backman, Deepanwita Banerjee, Deepti Tanjore, Lavanya Ramakrishnan and Anup Singh
Current Opinion in Biotechnology, 2023, 79, 102881
DOI: 10.1016/j.copbio.2022.102881

Machine Learning for Reactive Structural Adhesive Design: A Framework for Chemistry, Formulation, and Optimization
Florian Rothenhäusler and Holger Ruckdaeschel
Adhesives, 2026, 2, 5
DOI: 10.3390/adhesives2010005

An automated system for electrodeposition of polymer thin films and their wetting analysis
Harley Quinn, Gregory A. Robben, Zhaoyi Zheng, Jin Yan, Yuanzhi Li, Zhaoji Yang, Maria Politi, Nadya Peek, Lilo Pozzo, Jörg G. Werner and Keith A. Brown
Review of Scientific Instruments, 2026, 97
DOI: 10.1063/5.0309809

Introducing a four-fold way to conceptualize artificial agency
Maud van Lier
Synthese, 2023, 201
DOI: 10.1007/s11229-023-04083-9

Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab
Sebastian Putz, Niklas Teetz, Michael Abt, Pascal Jerono, Thomas Meurer and Matthias Franzreb
Biotech & Bioengineering, 2025, 122, 3018
DOI: 10.1002/bit.70038