Flaviu Cipcigan
Flaviu Cipcigan
IBM Research
Verified email at - Homepage
Cited by
Cited by
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ...
Nature Biomedical Engineering 5 (6), 613-623, 2021
Signature properties of water: Their molecular electronic origins
VP Sokhan, AP Jones, FS Cipcigan, J Crain, GJ Martyna
Proceedings of the National Academy of Sciences 112 (20), 6341-6346, 2015
Hydrogen bonding and molecular orientation at the liquid–vapour interface of water
FS Cipcigan, VP Sokhan, AP Jones, J Crain, GJ Martyna
Physical Chemistry Chemical Physics 17 (14), 8660-8669, 2015
Electronically coarse-grained model for water
A Jones, F Cipcigan, VP Sokhan, J Crain, GJ Martyna
Physical Review Letters 110 (22), 227801, 2013
Structure and hydrogen bonding at the limits of liquid water stability
F Cipcigan, V Sokhan, G Martyna, J Crain
Scientific reports 8 (1), 1718, 2018
Switching cytolytic nanopores into antimicrobial fractal ruptures by a single side chain mutation
K Hammond, F Cipcigan, K Al Nahas, V Losasso, H Lewis, J Cama, ...
ACS nano 15 (6), 9679-9689, 2021
Molecular-scale remnants of the liquid-gas transition in supercritical polar fluids
VP Sokhan, A Jones, FS Cipcigan, J Crain, GJ Martyna
Physical review letters 115 (11), 117801, 2015
Membrane binding of antimicrobial peptides is modulated by lipid charge modification
PW Simcock, M Bublitz, F Cipcigan, MG Ryadnov, J Crain, PJ Stansfeld, ...
Journal of Chemical Theory and Computation 17 (2), 1218-1228, 2021
Electronic coarse graining: Predictive atomistic modeling of condensed matter
FS Cipcigan, J Crain, VP Sokhan, GJ Martyna
Reviews of Modern Physics 91 (2), 025003, 2019
Electronically coarse-grained molecular dynamics using quantum Drude oscillators
AP Jones, J Crain, FS Cipcigan, VP Sokhan, M Modani, GJ Martyna
Molecular Physics 111 (22-23), 3465-3477, 2013
Membrane permeability in cyclic peptides is modulated by core conformations
F Cipcigan, P Smith, J Crain, A Hogner, L De Maria, A Llinas, E Ratkova
Journal of Chemical Information and Modeling 61 (1), 263-269, 2020
Accelerating molecular discovery through data and physical sciences: Applications to peptide-membrane interactions
F Cipcigan, AP Carrieri, EO Pyzer-Knapp, R Krishna, YW Hsiao, M Winn, ...
The Journal of Chemical Physics 148 (24), 2018
Accelerating antimicrobial discovery with controllable deep generative models and molecular dynamics
P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ...
arXiv preprint arXiv:2005.11248, 2020
Electronic coarse graining enhances the predictive power of molecular simulation allowing challenges in water physics to be addressed
FS Cipcigan, VP Sokhan, J Crain, GJ Martyna
Journal of Computational Physics 326, 222-233, 2016
MacroConf–dataset & workflows to assess cyclic peptide solution structures
D Crusius, JR Schnell, F Cipcigan, PC Biggin
Digital Discovery 2 (4), 1163-1177, 2023
Artificial intelligence designed antimicrobial peptides
P Das, F Cipcigan, JL Hedrick, YY Yang, K Wadhawan, I Padhi, EC Vijil, ...
US Patent App. 17/487,225, 2022
Chemical space analysis and property prediction for carbon capture solvent molecules
JL McDonagh, S Zavitsanou, A Harrison, D Zubarev, T van Kessel, ...
Digital Discovery 3 (3), 528-543, 2024
A Framework for Toxic PFAS Replacement based on GFlowNet and Chemical Foundation Model
E Soares, F Cipcigan, D Zubarev, EV Brazil
NeurIPS 2023 AI for Science Workshop, 2023
Discovery of Novel Reticular Materials for Carbon Dioxide Capture using GFlowNets
F Cipcigan, J Booth, RNB Ferreira, CR Santo, M Steiner
NeurIPS 2023 AI for Materials, 2023
MDLab: AI frameworks for carbon capture and battery materials
B Elmegreen, HF Hamann, B Wunsch, T Van Kessel, B Luan, T Elengikal, ...
Frontiers in Environmental Science 11, 1204690, 2023
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