| Machine-learned coarse-grained models KK Bejagam, S Singh, Y An, SA Deshmukh The journal of physical chemistry letters 9 (16), 4667-4672, 2018 | 66 | 2018 |
| Machine learning approach for accurate backmapping of coarse-grained models to all-atom models Y An, SA Deshmukh Chemical Communications 56 (65), 9312-9315, 2020 | 40 | 2020 |
| PSO-assisted development of new transferable coarse-grained water models KK Bejagam, S Singh, Y An, C Berry, SA Deshmukh The Journal of Physical Chemistry B 122 (6), 1958-1971, 2018 | 40 | 2018 |
| Machine-learning enabled new insights into the coil-to-globule transition of thermosensitive polymers using a coarse-grained model KK Bejagam, Y An, S Singh, SA Deshmukh The Journal of Physical Chemistry Letters 9 (22), 6480-6488, 2018 | 38 | 2018 |
| Preparation and properties of PVDF hollow fiber membrane for desalination using air gap membrane distillation L Lin, H Geng, Y An, P Li, H Chang Desalination 367, 145-153, 2015 | 35 | 2015 |
| Development of new transferable coarse-grained models of hydrocarbons Y An, KK Bejagam, SA Deshmukh The Journal of Physical Chemistry B 122 (28), 7143-7153, 2018 | 33 | 2018 |
| Machine-learning based stacked ensemble model for accurate analysis of molecular dynamics simulations SK Singh, KK Bejagam, Y An, SA Deshmukh The Journal of Physical Chemistry A 123 (24), 5190-5198, 2019 | 30 | 2019 |
| Development of an accurate coarse-grained model of poly (acrylic acid) in explicit solvents Y An, S Singh, KK Bejagam, SA Deshmukh Macromolecules 52 (13), 4875-4887, 2019 | 22 | 2019 |
| Solvation dynamics of N-substituted acrylamide polymers and the importance for phase transition behavior IO de Solorzano, KK Bejagam, Y An, SK Singh, SA Deshmukh Soft Matter 16 (6), 1582-1593, 2020 | 20 | 2020 |
| Development of transferable coarse-grained models of amino acids O Conway, Y An, KK Bejagam, SA Deshmukh Molecular Systems Design & Engineering 5 (3), 675-685, 2020 | 17 | 2020 |
| Development of transferable nonbonded interactions between coarse-grained hydrocarbon and water models Y An, KK Bejagam, SA Deshmukh The Journal of Physical Chemistry B 123 (4), 909-921, 2019 | 15 | 2019 |
| A combined experimental and computational approach reveals how aromatic peptide amphiphiles self-assemble to form ion-conducting nanohelices Y Wang, Y An, Y Shmidov, R Bitton, SA Deshmukh, JB Matson Materials chemistry frontiers 4 (10), 3022-3031, 2020 | 12 | 2020 |
| Synergistic role of temperature and salinity in aggregation of nonionic surfactant-coated silica nanoparticles Y Ma, C Heil, G Nagy, WT Heller, Y An, A Jayaraman, B Bharti Langmuir 39 (16), 5917-5928, 2023 | 5 | 2023 |
| Active learning of the thermodynamics-dynamics trade-off in protein condensates Y An, MA Webb, WM Jacobs Science Advances 10 (1), eadj2448, 2024 | 3 | 2024 |
| An Accurate Coarse-Grained Model of Poly (acrylic Acid) with Explicit Solvent Models of DMF and Water Y An, S Singh, KK Bejagam, S Deshmukh 2019 AIChE Annual Meeting, 2019 | 1 | 2019 |
| Selective Vapor Condensation for the Synthesis and Assembly of Spherical Colloids with a Precise Rough Patch KA Guillot, PJ Brahana, A Al Harraq, ND Ogbonna, NS Lombardo, ... JACS Au, 2024 | | 2024 |
| Effect of Therapeutic Molecules on Phase Separation and Dynamics of Intrinsically Disordered Proteins T Gao, Y An AIChE Annual Meeting, 2023 | | 2023 |
| Assemblies of Multi-Component Intrinsically Disordered Proteins and Their Spatial Organization T Gao, Y An AIChE Annual Meeting, 2023 | | 2023 |
| Thermodynamic and Dynamics Data for Coarse-grained Intrinsically Disordered Proteins Generated by Active Learning WO Michael Webb, William Jacobs, Yaxin An https://dataspace.princeton.edu/handle/88435/dsp01mp48sh02m, 2023 | | 2023 |
| Transferable Coarse-Grained Models: From Hydrocarbons to Polymers, and Backmapped by Machine Learning Y An Virginia Tech, 2021 | | 2021 |
Sanket A. DeshmukhAssociate Professor, Department of Chemical Engineering, Virginia Tech確認したメール アドレス: vt.edu
