These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
126 related articles for article (PubMed ID: 38512022)
1. Efficient Machine Learning Model Focusing on Active Sites for the Discovery of Bifunctional Oxygen Electrocatalysts in Binary Alloys. Wang C; Wang B; Wang C; Chang Z; Yang M; Wang R ACS Appl Mater Interfaces; 2024 Apr; 16(13):16050-16061. PubMed ID: 38512022 [TBL] [Abstract][Full Text] [Related]
2. Small-Molecule Adsorption Energy Predictions for High-Throughput Screening of Electrocatalysts. Raghavan S; Chaplin BP; Mehraeen S J Chem Inf Model; 2023 Sep; 63(17):5529-5538. PubMed ID: 37625148 [TBL] [Abstract][Full Text] [Related]
3. Accurate and efficient machine learning models for predicting hydrogen evolution reaction catalysts based on structural and electronic feature engineering in alloys. Zhang J; Wang Y; Zhou X; Zhong C; Zhang K; Liu J; Hu K; Lin X Nanoscale; 2023 Jul; 15(26):11072-11082. PubMed ID: 37335261 [TBL] [Abstract][Full Text] [Related]
4. Bifunctional diatomic site catalysts supported by β Liu J; Zhang M; Li SD; Mu Y Phys Chem Chem Phys; 2023 Dec; 26(1):594-601. PubMed ID: 38086640 [TBL] [Abstract][Full Text] [Related]
5. Machine Learning-Driven High-Throughput Screening of Alloy-Based Catalysts for Selective CO Roy D; Mandal SC; Pathak B ACS Appl Mater Interfaces; 2021 Dec; 13(47):56151-56163. PubMed ID: 34787997 [TBL] [Abstract][Full Text] [Related]
6. Elucidating the impact of oxygen functional groups on the catalytic activity of M-N Xie L; Zhou W; Huang Y; Qu Z; Li L; Yang C; Ding Y; Li J; Meng X; Sun F; Gao J; Zhao G; Qin Y Mater Horiz; 2024 Apr; 11(7):1719-1731. PubMed ID: 38277153 [TBL] [Abstract][Full Text] [Related]
7. Machine-learning-accelerated screening of single metal atoms anchored on MnPS Li X; Lin S; Yan T; Wang Z; Cai Q; Zhao J Nanoscale; 2023 Jul; 15(27):11616-11624. PubMed ID: 37377102 [TBL] [Abstract][Full Text] [Related]
8. Machine-Learning-Assisted Discovery of High-Efficient Oxygen Evolution Electrocatalysts. Mao X; Wang L; Li Y J Phys Chem Lett; 2023 Jan; 14(1):170-177. PubMed ID: 36579956 [TBL] [Abstract][Full Text] [Related]
9. Machine-learning-assisted discovery of highly efficient high-entropy alloy catalysts for the oxygen reduction reaction. Wan X; Zhang Z; Yu W; Niu H; Wang X; Guo Y Patterns (N Y); 2022 Sep; 3(9):100553. PubMed ID: 36124306 [TBL] [Abstract][Full Text] [Related]
10. The Perfect Imperfections in Electrocatalysts. Majee R; Parvin S; Arif Islam Q; Kumar A; Debnath B; Mondal S; Bhattacharjee S; Das S; Kumar A; Bhattacharyya S Chem Rec; 2022 Sep; 22(9):e202200070. PubMed ID: 35675947 [TBL] [Abstract][Full Text] [Related]
11. Intelligent route to design efficient CO Gheytanzadeh M; Baghban A; Habibzadeh S; Jabbour K; Esmaeili A; Mashhadzadeh AH; Mohaddespour A Sci Rep; 2022 Dec; 12(1):20859. PubMed ID: 36460814 [TBL] [Abstract][Full Text] [Related]
12. Theoretical Insights on the Charge State and Bifunctional OER/ORR Electrocatalyst Activity in 4d-Transition-Metal-Doped g-C Li D; Zhang A; Feng Z; Wang W ACS Appl Mater Interfaces; 2024 Feb; 16(5):5779-5791. PubMed ID: 38270099 [TBL] [Abstract][Full Text] [Related]
13. Intrinsic activity modulation and structural design of NiFe alloy catalysts for an efficient oxygen evolution reaction. Kang Q; Lai D; Tang W; Lu Q; Gao F Chem Sci; 2021 Feb; 12(11):3818-3835. PubMed ID: 34163652 [TBL] [Abstract][Full Text] [Related]
14. Transition Metal and N Doping on AlP Monolayers for Bifunctional Oxygen Electrocatalysts: Density Functional Theory Study Assisted by Machine Learning Description. Liu X; Zhang Y; Wang W; Chen Y; Xiao W; Liu T; Zhong Z; Luo Z; Ding Z; Zhang Z ACS Appl Mater Interfaces; 2022 Jan; 14(1):1249-1259. PubMed ID: 34941239 [TBL] [Abstract][Full Text] [Related]
15. Group and Period-Based Representations for Improved Machine Learning Prediction of Heterogeneous Alloy Catalysts. Li X; Chiong R; Page AJ J Phys Chem Lett; 2021 Jun; 12(21):5156-5162. PubMed ID: 34032450 [TBL] [Abstract][Full Text] [Related]
16. Iridium-Tungsten Alloy Nanodendrites as pH-Universal Water-Splitting Electrocatalysts. Lv F; Feng J; Wang K; Dou Z; Zhang W; Zhou J; Yang C; Luo M; Yang Y; Li Y; Gao P; Guo S ACS Cent Sci; 2018 Sep; 4(9):1244-1252. PubMed ID: 30276259 [TBL] [Abstract][Full Text] [Related]