Gregoire, John

Combined from CaltechAUTHORS

• Jones, Ryan J. R. and Lai, Yungchieh, et el. (2024) Accelerated screening of gas diffusion electrodes for carbon dioxide reduction; Digital Discovery; Vol. 3; No. 6; 1144-1149; 10.1039/D4DD00061G
• Watkins, Nicholas B. and Lai, Yungchieh, et el. (2024) Electrode Surface Heating with Organic Films Improves CO₂ Reduction Kinetics on Copper; ACS Energy Letters; Vol. 9; No. 4; 1440-1445; PMCID PMC11019637; 10.1021/acsenergylett.4c00204
• Jones, Ryan J. R. and Lai, Yungchieh, et el. (2024) Accelerated screening of carbon dioxide capture by liquid sorbents; Digital Discovery; Vol. 3; No. 4; 674-680; 10.1039/d3dd00232b
• Kan, Kevin and Guevarra, Dan, et el. (2024) Accelerated Characterization of Electrode‐Electrolyte Equilibration; ChemCatChem; Vol. 16; No. 6; e202301300; 10.1002/cctc.202301300
• Statt, Michael J. and Rohr, Brian A., et el. (2024) Event-driven data management with cloud computing for extensible materials acceleration platforms; Digital Discovery; Vol. 3; No. 2; 238-242; 10.1039/d3dd00220a
• Guevarra, Dan and Kan, Kevin, et el. (2023) Orchestrating nimble experiments across interconnected labs; Digital Discovery; Vol. 2; No. 6; 1806-1812; 10.1039/d3dd00166k
• Min, Yimeng and Chang, Ming-Chiang, et el. (2023) Physically Informed Graph-Based Deep Reasoning Net for Efficient Combinatorial Phase Mapping; ISBN 979-8-3503-4534-6; 2023 International Conference on Machine Learning and Applications (ICMLA); 392-399; 10.1109/icmla58977.2023.00061
• Statt, Michael J. and Rohr, Brian A., et el. (2023) ESAMP: event-sourced architecture for materials provenance management and application to accelerated materials discovery; Digital Discovery; Vol. 2; No. 4; 1078-1088; 10.1039/d3dd00054k
• Statt, Michael J. and Rohr, Brian A., et el. (2023) The materials experiment knowledge graph; Digital Discovery; Vol. 2; No. 4; 909-914; 10.1039/d3dd00067b
• Gregoire, John M. and Zhou, Lan, et el. (2023) Combinatorial synthesis for AI-driven materials discovery; Nature Synthesis; Vol. 2; No. 6; 493-504; 10.1038/s44160-023-00251-4
• Statt, Michael J. and Rohr, Brian A., et el. (2023) The Materials Experiment Knowledge Graph; 10.26434/chemrxiv-2023-md55t
• Watkins, Nicholas B. and Schiffer, Zachary J., et el. (2023) Hydrodynamics Change Tafel Slopes in Electrochemical CO₂ Reduction on Copper; ACS Energy Letters; Vol. 8; No. 5; 2185-2192; 10.1021/acsenergylett.3c00442
• Statt, Michael J. and Rohr, Brian A., et el. (2023) The Materials Provenance Store; Scientific Data; Vol. 10; 184; PMCID PMC10079965; 10.1038/s41597-023-02107-0
• Watkins, Nicholas B. and Schiffer, Zachary J., et el. (2023) Hydrodynamics Determine Tafel Slopes in Electrochemical CO₂ Reduction on Copper; 10.26434/chemrxiv-2023-npdmn
• Rao, Karun K. and Zhou, Lan, et el. (2023) Resolving atomistic structure and oxygen evolution activity in nickel antimonates; Journal of Materials Chemistry A; Vol. 11; No. 10; 5166-5178; 10.1039/d2ta08854a
• Zhou, Lan and Peterson, Elizabeth A., et el. (2022) Fe Substitutions Improve Spectral Response of Bi₂WO₆-Based Photoanodes; ACS Applied Energy Materials; Vol. 5; No. 12; 15333-15344; 10.1021/acsaem.2c02964
• Zhou, Lan and Wang, Yu, et el. (2022) Surveying Metal Antimonate Photoanodes for Solar Fuel Generation; ACS Sustainable Chemistry & Engineering; Vol. 10; No. 48; 15898-15908; 10.1021/acssuschemeng.2c05239
• Zhou, Lan and Guevarra, Dan, et el. (2022) High throughput discovery of enhanced visible photoactivity in Fe–Cr vanadate solar fuels photoanodes; Journal of Physics: Energy; Vol. 4; No. 4; Art. No. 044001; 10.1088/2515-7655/ac817e
• Burke Stevens, Michaela and Anand, Megha, et el. (2022) New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research; Energy and Environmental Science; Vol. 15; No. 9; 3775-3794; 10.1039/d2ee01333a
• Segev, Gideon and Kibsgaard, Jakob, et el. (2022) The 2022 solar fuels roadmap; Journal of Physics D: Applied Physics; Vol. 55; No. 32; Art. No. 323003; 10.1088/1361-6463/ac6f97
• Greenaway, Ann L. and Ke, Sijia, et el. (2022) Zinc Titanium Nitride Semiconductor toward Durable Photoelectrochemical Applications; Journal of the American Chemical Society; Vol. 144; No. 30; 13673-13687; PMCID PMC9354241; 10.1021/jacs.2c04241
• Zhou, Lan and Peterson, Elizabeth A., et el. (2022) Addressing solar photochemistry durability with an amorphous nickel antimonate photoanode; Cell Reports Physical Science; Vol. 3; No. 7; Art. No. 100959; 10.1016/j.xcrp.2022.100959
• Yano, Junko and Gaffney, Kelly J., et el. (2022) The case for data science in experimental chemistry: examples and recommendations; Nature Reviews Chemistry; Vol. 6; No. 5; 357-370; 10.1038/s41570-022-00382-w
• Guevarra, Dan and Zhou, Lan, et el. (2022) Materials structure–property factorization for identification of synergistic phase interactions in complex solar fuels photoanodes; npj Computational Materials; Vol. 8; Art. No. 57; 10.1038/s41524-022-00747-1
• Lai, Yungchieh and Watkins, Nicholas B., et el. (2022) Molecular Coatings Improve the Selectivity and Durability of CO₂ Reduction Chalcogenide Photocathodes; ACS Energy Letters; Vol. 7; No. 3; 1195-1201; 10.1021/acsenergylett.1c02762
• Rahmanian, Fuzhan and Flowers, Jackson, et el. (2022) Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration; Advanced Materials Interfaces; Vol. 9; No. 8; Art. No. 2101987; 10.1002/admi.202101987
• Zhou, Lan and Li, Hao, et el. (2022) Stability and Activity of Cobalt Antimonate for Oxygen Reduction in Strong Acid; ACS Energy Letters; Vol. 7; No. 3; 993-1000; 10.1021/acsenergylett.1c02673
• Kong, Shufeng and Ricci, Francesco, et el. (2022) Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings; Nature Communications; Vol. 13; Art. No. 949; 10.1038/s41467-022-28543-x
• Rao, Karun K. and Lai, Yungchieh, et el. (2022) Overcoming Hurdles in Oxygen Evolution Catalyst Discovery via Codesign; Chemistry of Materials; Vol. 34; No. 3; 899-910; 10.1021/acs.chemmater.1c04120
• Lamaison, Sarah and Wakerley, David, et el. (2022) Designing a Zn–Ag Catalyst Matrix and Electrolyzer System for CO₂ Conversion to CO and Beyond; Advanced Materials; Vol. 34; No. 1; Art. No. 2103963; 10.1002/adma.202103963
• Guevarra, Dan and Haber, Joel A., et el. (2022) High Throughput Discovery of Complex Metal Oxide Electrocatalysts for the Oxygen Reduction Reaction; Electrocatalysis; Vol. 13; No. 1; 1-10; 10.1007/s12678-021-00694-3
• Ament, Sebastian and Amsler, Maximilian, et el. (2021) Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams; Science Advances; Vol. 7; No. 51; Art. No. abg4930; PMCID PMC8682983; 10.1126/sciadv.abg4930
• Lai, Yunchieh and Watkins, Nicholas B., et el. (2021) Breaking Scaling Relationships in CO₂ Reduction on Copper Alloys with Organic Additives; ACS Central Science; Vol. 7; No. 10; 1756-1762; PMCID PMC8554824; 10.1021/acscentsci.1c00860
• Richter, Matthias H. and Peterson, Elizabeth A., et el. (2021) Band Edge Energy Tuning through Electronic Character Hybridization in Ternary Metal Vanadates; Chemistry of Materials; Vol. 33; No. 18; 7242-7253; 10.1021/acs.chemmater.1c01415
• Yang, Lusann and Haber, Joel A., et el. (2021) Discovery of complex oxides via automated experiments and data science; Proceedings of the National Academy of Sciences; Vol. 118; No. 37; Art. No. e2106042118; PMCID PMC8449358; 10.1073/pnas.2106042118
• Stach, Eric and DeCost, Brian, et el. (2021) Autonomous experimentation systems for materials development: A community perspective; Matter; Vol. 4; No. 9; 2702-2726; 10.1016/j.matt.2021.06.036
• Chen, Di and Bai, Yiwei, et el. (2021) Automating crystal-structure phase mapping by combining deep learning with constraint reasoning; Nature Machine Intelligence; Vol. 3; No. 9; 812-822; 10.1038/s42256-021-00384-1
• Wang, Lei and Peng, Hongjie, et el. (2021) Bimetallic effects on Zn-Cu electrocatalysts enhance activity and selectivity for the conversion of CO₂ to CO; Chem Catalysis; Vol. 1; No. 3; 663-680; 10.1016/j.checat.2021.05.006
• Gomes, Carla P. and Fink, Daniel, et el. (2021) Computational sustainability meets materials science; Nature Reviews Materials; Vol. 6; No. 8; 645-647; 10.1038/s41578-021-00348-2
• Statt, Michael J. and Rohr, Brian A., et el. (2021) ESAMP: Event-Sourced Architecture for Materials Provenance Management and Application to Accelerated Materials Discovery; 10.26434/chemrxiv.14583258.v1
• Li, Hao and Kelly, Sara, et el. (2021) Analysis of the limitations in the oxygen reduction activity of transition metal oxide surfaces; Nature Catalysis; Vol. 4; No. 6; 463-468; 10.1038/s41929-021-00618-w
• Kong, Shufeng and Guevarra, Dan, et el. (2021) Materials representation and transfer learning for multi-property prediction; Applied Physics Reviews; Vol. 8; No. 2; Art. No. 021409; 10.1063/5.0047066
• Newhouse, Paul F. and Zhou, Lan, et el. (2020) Bi Alloying into Rare Earth Double Perovskites Enhances Synthesizability and Visible Light Absorption; ACS Combinatorial Science; Vol. 22; No. 12; 895-901; 10.1021/acscombsci.0c00177
• Sutherland, Duncan R. and Connolly, Aine Boyer, et el. (2020) Optical Identification of Materials Transformations in Oxide Thin Films; ACS Combinatorial Science; Vol. 22; No. 12; 887-894; 10.1021/acscombsci.0c00172
• Zhou, Lan and Shinde, Aniketa, et el. (2020) Quaternary Oxide Photoanode Discovery Improves the Spectral Response and Photovoltage of Copper Vanadates; Matter; Vol. 3; No. 5; 1614-1630; 10.1016/j.matt.2020.08.031
• Newhouse, Paul F. and Guevarra, Dan, et el. (2020) Enhanced Bulk Transport in Copper Vanadate Photoanodes Identified by Combinatorial Alloying; Matter; Vol. 3; No. 5; 1601-1613; 10.1016/j.matt.2020.08.032
• Chen, Di and Bai, Yiwei, et el. (2020) Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning; Proceedings of Machine Learning Research; Vol. 119; 1500-1509
• Zhang, Zemin and Lindley, Sarah A., et el. (2020) Fermi Level Engineering of Passivation and Electron Transport Materials for p-Type CuBi₂O₄ Employing a High‐Throughput Methodology; Advanced Functional Materials; Vol. 30; No. 24; Art. No. 2000948; 10.1002/adfm.202000948
• Umehara, Mitsutaro and Zhou, Lan, et el. (2020) Combinatorial synthesis of oxysulfides in the lanthanum-bismuth-copper system; ACS Combinatorial Science; Vol. 22; No. 6; 319-326; 10.1021/acscombsci.0c00015
• Zhou, Lan and Shinde, Aniketa, et el. (2020) On the successes and opportunities for discovery of metal oxide photoanodes for solar fuels generators; ACS Energy Letters; Vol. 5; No. 5; 1413-1421; 10.1021/acsenergylett.0c00067
• Yao, Yonggang and Huang, Zhennan, et el. (2020) High-throughput, combinatorial synthesis of multimetallic nanoclusters; Proceedings of the National Academy of Sciences of the United States of America; Vol. 117; No. 12; 6316-6322; PMCID PMC7104385; 10.1073/pnas.1903721117
• Rohr, Brian and Stein, Helge S., et el. (2020) Benchmarking the Acceleration of Materials Discovery by Sequential Learning; Chemical Science; Vol. 11; No. 10; 2696-2706; 10.1039/c9sc05999g
• Zhou, Lan and Shinde, Aniketa, et el. (2020) Combinatorial screening yields discovery of 29 metal oxide photoanodes for solar fuel generation; Journal of Materials Chemistry A; Vol. 8; No. 8; 4239-4243; 10.1039/c9ta13829c
• Lai, Yungchieh and Jones, Ryan J. R., et el. (2019) The Sensitivity of Cu for Electrochemical Carbon Dioxide Reduction to Hydrocarbons as Revealed by High Throughput Experiments; Journal of Materials Chemistry A; Vol. 7; No. 47; 26785-26790; 10.1039/c9ta10111j
• Aykol, Muratahan and Gregoire, John M. (2019) The Materials Research Platform: Defining the Requirements from User Stories; Matter; Vol. 1; No. 6; 1433-1438; 10.1016/j.matt.2019.10.024
• Noh, Juhwan and Kim, Sungwon, et el. (2019) Unveiling new stable manganese based photoanode materials via theoretical high-throughput screening and experiments; Chemical Communications; Vol. 55; No. 89; 13418-13421; 10.1039/c9cc06736a
• Stein, Helge S. and Gregoire, John M. (2019) Progress and prospects for accelerating materials science with automated and autonomous workflows; Chemical Science; Vol. 10; No. 42; 9640-9649; PMCID PMC7020936; 10.1039/c9sc03766g
• Noh, Juhwan and Kim, Jaehoon, et el. (2019) Inverse Design of Solid-State Materials via a Continuous Representation; Matter; Vol. 1; No. 5; 1370-1384; 10.1016/j.matt.2019.08.017
• Lai, Yungchieh and Jones, Ryan J. R., et el. (2019) Scanning electrochemical flow cell with online mass spectroscopy for accelerated screening of carbon dioxide reduction electrocatalysts; ACS Combinatorial Science; Vol. 21; No. 10; 692-704; 10.1021/acscombsci.9b00130
• Gregoire, John M. (2019) Unexpected Transitions Yield Interesting Science and High-Performance Materials; Matter; Vol. 1; No. 4; 790-791; 10.1016/j.matt.2019.09.006
• Gomes, Carla and Gregoire, John (2019) Computational sustainability: computing for a better world and a sustainable future; Communications of the ACM; Vol. 62; No. 9; 56-65; 10.1145/3339399
• Newhouse, Paul and Guevarra, Dan, et el. (2019) Multi-modal optimization of bismuth vanadate photoanodes via combinatorial alloying and hydrogen processing
• Haber, Joel and Stein, Helge S., et el. (2019) Functional mapping reveals mechanistic clusters for OER catalysis across (Cu-Mn-Ta-Co-Sn-Fe)Ox composition and pH space
• Soedarmadji, Edwin and Stein, Helge S., et el. (2019) Tracking materials science data lineage to manage millions of materials experiments and analyses; npj Computational Materials; Vol. 5; Art. No. 79; 10.1038/s41524-019-0216-x
• Ament, Sebastian E. and Stein, Helge S., et el. (2019) Multi-component background learning automates signal detection for spectroscopic data; npj Computational Materials; Vol. 5; Art. No. 77; 10.1038/s41524-019-0213-0
• Stein, Helge S. and Guevarra, Dan, et el. (2019) Functional mapping reveals mechanistic clusters for OER catalysis across (Cu–Mn–Ta–Co–Sn–Fe)O_x composition and pH space; Materials Horizons; Vol. 6; No. 6; 1251-1258; 10.1039/c8mh01641k
• Gomes, Carla P. and Selman, Bart, et el. (2019) Artificial intelligence for materials discovery; MRS Bulletin; Vol. 44; No. 7; 538-544; 10.1557/mrs.2019.158
• Gomes, Carla P. and Bai, Junwen, et el. (2019) CRYSTAL: a multi-agent AI system for automated mapping of materials' crystal structures; MRS Communications; Vol. 9; No. 2; 600-608; 10.1557/mrc.2019.50
• Bai, Junwen and Lai, Zihang, et el. (2019) Imitation Refinement for X-ray Diffraction Signal Processing; ISBN 978-1-5386-4658-8; 2019 IEEE International Conference on Acoustics, Speech and Signal Processing; 3337-3341; 10.1109/ICASSP.2019.8683723
• Stein, Helge S. and Soedarmadji, Edwin, et el. (2019) Synthesis, optical imaging, and absorption spectroscopy data for 179072 metal oxides; Scientific Data; Vol. 6; Art. No. 9; PMCID PMC6437643; 10.1038/s41597-019-0019-4
• Umehara, Mitsutaro and Stein, Helge S., et el. (2019) Analyzing machine learning models to accelerate generation of fundamental materials insights; npj Computational Materials; Vol. 5; Art. No. 34; 10.1038/s41524-019-0172-5
• Singh, Arunima K. and Montoya, Joseph H., et el. (2019) Robust and synthesizable photocatalysts for CO₂ reduction: a data-driven materials discovery; Nature Communications; Vol. 10; Art. No. 443; PMCID PMC6347635; 10.1038/s41467-019-08356-1
• Newhouse, P. F. and Guevarra, D., et el. (2019) Multi-modal optimization of bismuth vanadate photoanodes via combinatorial alloying and hydrogen processing; Chemical Communications; Vol. 55; No. 4; 489-492; 10.1039/c8cc07156j
• Stein, Helge S. and Guevarra, Dan, et el. (2019) Machine learning of optical properties of materials - predicting spectra from images and images from spectra; Chemical Science; Vol. 10; No. 1; 47-55; PMCID PMC6334722; 10.1039/c8sc03077d
• Alberi, Kirstin and Gregoire, John (2019) The 2019 materials by design roadmap; Journal of Physics D: Applied Physics; Vol. 52; No. 1; Art. No. 013001; 10.1088/1361-6463/aad926
• Liu, Guiji and Eichhorn, Johanna, et el. (2019) Interface engineering for light-driven water oxidation: unravelling the passivating and catalytic mechanism in BiVO₄ overlayers; Sustainable Energy and Fuels; Vol. 3; No. 1; 127-135; 10.1039/C8SE00473K
• Zhou, Lan and Shinde, Aniketa, et el. (2018) Rutile alloys in the Mn-Sb-O system stabilize Mn^(+3) to enable oxygen evolution in strong acid; ACS Catalysis; Vol. 8; No. 12; 10938-10948; 10.1021/acscatal.8b02689
• Jones, Ryan J. R. and Wang, Yu, et el. (2018) Reactor design and integration with product detection to accelerate screening of electrocatalysts for carbon dioxide reduction; Review of Scientific Instruments; Vol. 89; No. 12; Art. No. 124102; 10.1063/1.5049704
• Zhou, Lan and Shinde, Aniketa, et el. (2018) Bi-containing n-FeWO_4 Thin Films Provide the Largest Photovoltage and Highest Stability for a sub-2 eV Band Gap Photoanode; ACS Energy Letters; Vol. 3; No. 11; 2769-2774; 10.1021/acsenergylett.8b01514
• Zhou, Lan and Shinde, Aniketa, et el. (2018) Balancing Surface Passivation and Catalysis with Integrated BiVO_4/(Fe-Ce)O_x Photoanodes in pH 9 Borate Electrolyte; ACS Applied Energy Materials; Vol. 1; No. 10; 5766-5771; 10.1021/acsaem.8b01377
• Newhouse, P. F. and Guevarra, D., et el. (2018) Combinatorial Alloying Improves Bismuth Vanadate Photoanodes via Reduced Monoclinic Distortion; Energy and Environmental Science; Vol. 11; No. 9; 2444-2457; 10.1039/c8ee00179k
• Bai, Junwen and Ament, Sebastian, et el. (2018) An Efficient Relaxed Projection Method for Constrained Non-negative Matrix Factorization with Application to the Phase-Mapping Problem in Materials Science; ISBN 978-3-319-93030-5; Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 52-62; 10.1007/978-3-319-93031-2_4
• Suram, Santosh K. and Zhou, Lan, et el. (2018) Alkaline-stable nickel manganese oxides with ideal band gap for solar fuel photoanodes; Chemical Communications; Vol. 54; No. 36; 4625-4628; 10.1039/c7cc08002f
• Bai, Junwen and Xue, Yexiang, et el. (2018) Phase Mapper: Accelerating Materials Discovery with AI; AI Magazine; Vol. 39; No. 1; 15-26; 10.1609/aimag.v39i1.2785
• Gregoire, John (2018) Accelerated experimental materials discovery through integration with theory and artificial intelligence
• Haber, Joel and Guevarra, Dan, et el. (2018) Development of solar fuels photoanodes through combinatorial integration of multifunctional Fe-Ce oxide coatings on BiVO4 as a function of coating composition, loading, and electrolyte
• Haber, Joel and Guevarra, Dan, et el. (2018) High throughput, multi-pH evaluation of earth-abundant pseudo-quaternary metal oxide catalysts for the oxygen evolution reaction
• Suram, Santosh K. and Fackler, Sean W., et el. (2018) Combinatorial Discovery of Lanthanum-Tantalum Oxynitride Solar Light Absorbers with Dilute Nitrogen for Solar Fuels Applications; ACS Combinatorial Science; Vol. 20; No. 1; 26-34; 10.1021/acscombsci.7b00143
• Gregoire, John M. and Boyd, David A., et el. (2018) High Throughput Experimentation for the Discovery of Water Splitting Materials; ISBN 978-1-78262-555-1; Integrated Solar Fuel Generators; 307-340; 10.1039/9781788010313-00305
• Singh, Arunima K. and Zhou, Lan, et el. (2017) Electrochemical Stability of Metastable Materials; Chemistry of Materials; Vol. 29; No. 23; 10159-10167; 10.1021/acs.chemmater.7b03980
• Newhouse, Paul F. and Reyes-Lillo, Sebastian E., et el. (2017) Discovery and Characterization of a Pourbaix-Stable, 1.8 eV Direct Gap Bismuth Manganate Photoanode; Chemistry of Materials; Vol. 29; No. 23; 10027-10036; 10.1021/acs.chemmater.7b03591
• Shinde, Aniketa and Suram, Santosh K., et el. (2017) Discovery of Manganese-Based Solar Fuel Photoanodes via Integration of Electronic Structure Calculations, Pourbaix Stability Modeling, and High-Throughput Experiments; ACS Energy Letters; Vol. 2; No. 10; 2307-2312; 10.1021/acsenergylett.7b00607
• Liu, Guiji and Eichhorn, Johanna, et el. (2017) Optical, morphological, and electrochemical multimodal characterization for integrated BiVO4 photoanodes
• Bai, Junwen and Bjorck, Johan, et el. (2017) Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery; ISBN 978-3-319-59775-1; Integration of AI and OR Techniques in Constraint Programming; 104-112; 10.1007/978-3-319-59776-8_9
• Newhouse, Paul and Boyd, David, et el. (2017) Solar fuels photoanodes prepared by inkjet printing of copper vanadates
• Haber, Joel and Guevarra, Dan, et el. (2017) Development of solar fuels photoanodes through combinatorial integration of Ni- La-Co-Ce oxide and Ni-Fe-Co-Ce oxide catalysts on BiVO₄
• Gregoire, John (2017) High throughput discovery of solar fuels photoanodes
• Yan, Qimin and Yu, Jie, et el. (2017) Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment; Proceedings of the National Academy of Sciences of the United States of America; Vol. 114; No. 12; 3040-3043; PMCID PMC5373381; 10.1073/pnas.1619940114
• Green, M. L. and Choi, C. L., et el. (2017) Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies; Applied Physics Reviews; Vol. 4; No. 1; Art. No. 011105; 10.1063/1.4977487
• Favaro, Marco and Drisdell, Walter S., et el. (2017) An Operando Investigation of (Ni-Fe-Co-Ce)O_x System as Highly Efficient Electrocatalyst for Oxygen Evolution Reaction; ACS Catalysis; Vol. 7; No. 2; 1248-1258; 10.1021/acscatal.6b03126
• Suram, Santosh K. and Xue, Yexiang, et el. (2017) Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System; ACS Combinatorial Science; Vol. 19; No. 1; 37-46; 10.1021/acscombsci.6b00153
• Suram, Santosh K. and Newhouse, Paul F., et el. (2016) High Throughput Light Absorber Discovery, Part 1: An Algorithm for Automated Tauc Analysis; ACS Combinatorial Science; Vol. 18; No. 11; 673-681; 10.1021/acscombsci.6b00053
• Suram, Santosh K. and Newhouse, Paul F., et el. (2016) High Throughput Light Absorber Discovery, Part 2: Establishing Structure–Band Gap Energy Relationships; ACS Combinatorial Science; Vol. 18; No. 11; 682-688; 10.1021/acscombsci.6b00054
• Shinde, A. and Li, G., et el. (2016) The role of the CeO_2/BiVO_4 interface in optimized Fe-Ce oxide coatings for solar fuels photoanodes; Journal of Materials Chemistry A; Vol. 4; No. 37; 14356-14363; 10.1039/c6ta04746g
• Shinde, Aniketa and Guevarra, Dan, et el. (2016) Discovery of Fe–Ce Oxide/BiVO₄ Photoanodes through Combinatorial Exploration of Ni–Fe–Co–Ce Oxide Coatings; ACS Applied Materials & Interfaces; Vol. 8; No. 36; 23696-23705; 10.1021/acsami.6b06714
• Haber, Joel and Guevarra, Dan, et el. (2016) Development of solar fuels photoanodes through combinatorial integration of Ni-La-Co-Ce oxide and Ni-Fe-Co-Ce oxide catalysts on BiVO₄
• Newhouse, P. F. and Boyd, D. A., et el. (2016) Solar fuel photoanodes prepared by inkjet printing of copper vanadates; Journal of Materials Chemistry A; Vol. 4; No. 19; 7483-7494; 10.1039/C6TA01252C
• Hattrick-Simpers, Jason R. and Gregoire, John M., et el. (2016) Perspective: Composition–structure–property mapping in high-throughput experiments: Turning data into knowledge; APL Materials; Vol. 4; No. 5; Art. No. 053211; 10.1063/1.4950995
• Zhou, Lan and Yan, Qimin, et el. (2016) Stability and self-passivation of copper vanadate photoanodes under chemical, electrochemical, and photoelectrochemical operation; Physical Chemistry Chemical Physics; Vol. 18; No. 14; 9349-9352; 10.1039/C6CP00473C
• Guevarra, D. and Shinde, A., et el. (2016) Development of solar fuels photoanodes through combinatorial integration of Ni–La–Co–Ce oxide catalysts on BiVO₄; Energy and Environmental Science; Vol. 9; No. 2; 565-580; 10.1039/c5ee03488d
• Suram, Santosh K. and Pesenson, Meyer Z., et el. (2015) High Throughput Combinatorial Experimentation + Informatics = Combinatorial Science; ISBN 978-3-319-23870-8; Information Science for Materials Discovery and Design; 271-300; 10.1007/978-3-319-23871-5_14
• Zhou, Lan and Yan, Qimin, et el. (2015) High Throughput Discovery of Solar Fuels Photoanodes in the CuO-V_2O_5 System; Advanced Energy Materials; Vol. 5; No. 22; Art. No. 1500968; 10.1002/aenm.201500968
• Fenwick, Aidan Q. and Gregoire, John M., et el. (2015) Electrocatalytic Reduction of Nitrogen and Carbon Dioxide to Chemical Fuels: Challenges and Opportunities for a Solar Fuel Device; Journal of Photochemistry and Photobiology B: Biology; Vol. 152; 47-57; 10.1016/j.jphotobiol.2014.12.019
• Zhou, Lan and Suram, Santosh K., et el. (2015) Combining reactive sputtering and rapid thermal processing for synthesis and discovery of metal oxynitrides; Journal of Materials Research; Vol. 30; No. 19; 2928-2933; 10.1557/jmr.2015.140
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• Haber, Joel A. and Anzenburg, Eitan, et el. (2015) Multiphase Nanostructure of a Quinary Metal Oxide Electrocatalyst Reveals a New Direction for OER Electrocatalyst Design; Advanced Energy Materials; Vol. 5; No. 10; Art. No. 1402307; 10.1002/aenm.201402307
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