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RESEARCH PAPER · Nature Chemical Engineering · 2025

Flow-driven data intensification to accelerate autonomous inorganic materials discovery

Fernando Delgado‐Licona, Abdulrahman Alsaiari, Hannah Dickerson, Philip Klem, Arup Ghorai, Richard B. Canty, Jeffrey A. Bennett, Pragyan Jha, Nikolai Mukhin, Junbin Li, Enrique A. López-Guajardo, Sina Sadeghi, Fazel Bateni, Milad Abolhasani

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

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42 direct citing works

Flow-driven data intensification to accelerate autonomous inorganic materials discoveryOriginalAI-Driven Autonomous Platforms for Nanomaterial Discovery and Optimization: Bridging Simulation, Synthesis, and In Situ Characterization2Temporal Governance Gaps: Oversight Latency in Accelerated Materials Discovery Systems0The Future of Materials Science with AI: Self-Driving Laboratories and Closed-Loop Discovery0Learning the flow from the get-go0Programmable Light-Driven Color Tuning of Perovskite Quantum Dots4Accelerating multimetallic catalyst discovery with robotics and agentic AI8Toward AI ecosystems for electrolyte and interface engineering in solid-state batteries23Aqueous Continuous Flow Synthesis of Cadmium Chalcogenide Quantum Dots: Opportunities and Challenges2Interpreting X-ray Diffraction Patterns of Metal–Organic Frameworks via Generative Artificial Intelligence7A modular platform for in-flow synthesis and characterization of upconverting nanoparticles0AI-driven design and applications of quantum dots9A scientist's guide to AI-driven molecular discovery3Machine-Learning-Guided Discovery and Statistical Analysis of Multielemental Reverse Water–Gas Shift Catalysts1Mechanism-embedded deep learning platform enabling accurate structure–property prediction for complex systems0From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science0Autonomous microfluidic experimentation for exploring reaction inference and synthesizing double perovskite nanoplatelets4Microfluidics: A Scalable Solution to Data Challenges in Chemical AI0A chromatographic process design and optimization multi-agent platform powered by large language models: A case application on extract of Ginkgo biloba leaf0Open-source robotic chip-to-plate interface for high-throughput microfluidic generation of materials libraries0Autonomous control of quantum-confined CsPbBr3 nanoplatelets0Autonomous laboratories for sustainable nanomaterials discovery0The past, present and future of self-driving laboratories5Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework0Towards self-driving laboratories in the biopharmaceutical industry0Improving Close-Contact Melting of Erythritol in Plate Heat Exchangers via Machine Learning0

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  1. AI-Driven Autonomous Platforms for Nanomaterial Discovery and Optimization: Bridging Simulation, Synthesis, and In Situ Characterization

    SSRN Electronic Journal · 2025-01-01

    Dilshod Nematov, Iskandar Raufov

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  2. Temporal Governance Gaps: Oversight Latency in Accelerated Materials Discovery Systems

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

    Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich

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  3. The Future of Materials Science with AI: Self-Driving Laboratories and Closed-Loop Discovery

    SSRN Electronic Journal · 2025-01-01

    Dilshod Nematov, Iskandar Raufov

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  4. Learning the flow from the get-go

    Nature Chemical Engineering · 2025-08-06

    Mahshid Ahmadi, Sergei V. Kalinin

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  5. Programmable Light-Driven Color Tuning of Perovskite Quantum Dots

    ACS Central Science · 2025-11-13

    Pragyan Jha, Nikolai Mukhin, Jinge Xu, Christopher H.J. Moran, Arup Ghorai, Felix N. Castellano, Milad Abolhasani

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  6. Accelerating multimetallic catalyst discovery with robotics and agentic AI

    AI Agent · 2025-11-24

    Jiayu Peng, Chuanyu Liu, Yiwen Luo, Kritarth Dandapat

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  7. Toward AI ecosystems for electrolyte and interface engineering in solid-state batteries

    Science Advances · 2025-11-26

    Zhilong Wang, Wolfgang G. Zeier, Fengqi You

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  8. Aqueous Continuous Flow Synthesis of Cadmium Chalcogenide Quantum Dots: Opportunities and Challenges

    JACS Au · 2025-12-18

    Carlotta Campalani, Guillaume Petit, Jean‐Christophe M. Monbaliu

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  9. Interpreting X-ray Diffraction Patterns of Metal–Organic Frameworks via Generative Artificial Intelligence

    Journal of the American Chemical Society · 2025-12-20

    Bin Feng, Bingxu Wang, Linpeng Lv, Mingzheng Zhang, Zhefeng Chen, Feng Ming Pan, Shunning Li

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  10. A modular platform for in-flow synthesis and characterization of upconverting nanoparticles

    Lab on a Chip · 2026-01-01

    Turar Tanirbergenov, Ірина Корякіна, Balmiki Kumar, Suryavarshini Sundar, Ben Zheng, Jiaze Wu, Emory M. Chan, Han Hao, Eugenia Kumacheva

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  11. AI-driven design and applications of quantum dots

    Nano Today · 2026-01-13

    Prince Kumar Soni, Manmohan Lal Satnami, Rekha Nagwanshi, Yogyata Chawre, Ankita Beena Kujur, Akash Sinha, Pinki Miri, Indrapal Karbhal, Kallol Kumar Ghosh

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  12. A scientist's guide to AI-driven molecular discovery

    Artificial Intelligence Chemistry · 2026-01-24

    Jakes Udabe

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  13. Machine-Learning-Guided Discovery and Statistical Analysis of Multielemental Reverse Water–Gas Shift Catalysts

    ACS Catalysis · 2026-02-25

    Duotian Chen, Shinya Mine, Guanghui Wang, Ichigaku Takigawa, Akihiko Anzai, Ken‐ichi Shimizu, Takashi Toyao

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  14. Mechanism-embedded deep learning platform enabling accurate structure–property prediction for complex systems

    Chemical Engineering Science · 2026-03-11

    Yi Li, Yewei Ding, Siqi Wang, Yutong Song, Kai Ge, Gabriele Sadowski, Yuanhui Ji

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  15. From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science

    Journal of the Physical Society of Japan · 2026-03-25

    Hieu‐Chi Dam, Hiori Kino, Takashi Miyake

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  16. Autonomous microfluidic experimentation for exploring reaction inference and synthesizing double perovskite nanoplatelets

    Nature Communications · 2026-05-04

    Junbin Li, Fernando Delgado‐Licona, Zhenyang Liu, Hayden Perry, Jinge Xu, Nikolai Mukhin, Sina Sadeghi, Ou Chen, Milad Abolhasani

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  17. Microfluidics: A Scalable Solution to Data Challenges in Chemical AI

    Synlett · 2026-05-06

    Rico Warias, Detlev Belder, Julia Westermayr, Tobias A. M. Gulder, Tanja Gulder

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  18. A chromatographic process design and optimization multi-agent platform powered by large language models: A case application on extract of Ginkgo biloba leaf

    Journal of Chromatography A · 2026-05-12

    Zhilong Tang, Shaohua Wu, Xinyan Zhao, Yu Wang, Xingchu Gong

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  19. Open-source robotic chip-to-plate interface for high-throughput microfluidic generation of materials libraries

    bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-14

    Isabel B. Navarro, Gregory Datto, Lameck Beni, Diego Barragan, Katherine J. Mossburg, Shiny Shen, Andrew R. Hanna, David P. Cormode, David Issadore

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  20. Autonomous control of quantum-confined CsPbBr3 nanoplatelets

    Matter · 2026-07-08

    Pragyan Jha, Nikolai Mukhin, Jinge Xu, Arup Ghorai, Junbin Li, Christopher H.J. Moran, Joseph Supik, Milad Abolhasani

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  21. Autonomous laboratories for sustainable nanomaterials discovery

    Next Materials · 2026-07-23

    Aarti Jathar, Beena R. Nawghare, Ketankumar A. Ganure

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  22. The past, present and future of self-driving laboratories

    Nature Reviews Chemistry · 2026-07-30

    Richard B. Canty, Milad Abolhasani

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  23. Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

    Advanced Science · 2026-08-03

    Olympia Dartsi, Lauren N. Walters, Amalie Trewartha, Steven B. Torrisi, Amanda A. Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain

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  24. Towards self-driving laboratories in the biopharmaceutical industry

    Nature Synthesis · 2026-08-04

    Samagra Dvivedi, Nitin Minocha, Shuang Chen, Beata Chertok, Daniel A. Estabrook, Yuchen Fan, Suyong Han, Deepak Jain, Manish S. Kelkar, Alison Lui, Nandkishor K. Nere, Phenil J. Patel, Kenneth G. Rodriguez, Eric R. Sacia, Priyanka G. Singh, Dimitri B. Skliar, Emad Ibrahim Wafa, Meenesh R. Singh

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  25. Improving Close-Contact Melting of Erythritol in Plate Heat Exchangers via Machine Learning

    Journal of Thermal Science · 2026-08-27

    Jiajie Jiang, Zirui Li, Liwu Fan

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