Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Emre Sevgen"'
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Salts in water at extreme conditions play a fundamental role in determining the properties of the Earthʼs mantle constituents. Here the authors shed light on ion-water and ion-ion interactions for NaCl dissolved in water at conditions relevant to th
Externí odkaz:
https://doaj.org/article/4c6b8a94125449e4bb57c033ee37b56e
Autor:
Emre Sevgen, Joshua Moller, Adrian Lange, John Parker, Sean Quigley, Jeff Mayer, Poonam Srivastava, Sitaram Gayatri, David Hosfield, Maria Korshunova, Micha Livne, Michelle Gill, Rama Ranganathan, Anthony B. Costa, Andrew L. Ferguson
The data-driven design of protein sequences with desired function is challenged by the absence of good theoretical models for the sequence-function mapping and the vast size of protein sequence space. Deep generative models have demonstrated success
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64c920f3acf3e7849a02e4f8b84b588e
https://doi.org/10.1101/2023.01.23.525232
https://doi.org/10.1101/2023.01.23.525232
Autor:
Ventura Rivera, Brendan Folie, Emily Rosenthal, Andrea Jacobs, Edward Kim, Jason Koeller, Julia Ling, Emre Sevgen
Publikováno v:
Industrial & Engineering Chemistry Research. 60:14176-14184
Autor:
Edward Kim, Erin Antono, Jason Koeller, Astha Gargt, Julia Ling, James S. Peerless, Emre Sevgen, Stephen D. Edkins, Yoolhee Kim
Publikováno v:
MRS Communications. 10:18-24
In many materials development projects, scientists and research heads make decisions to guide the project direction. For example, scientists may decide which processing steps to use, what elements to include in their material selection, or from what
Publikováno v:
Journal of Chemical Theory and Computation. 16:1448-1455
An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinc
Publikováno v:
Nature communications, vol 11, iss 1
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
The investigation of salts in water at extreme conditions is crucial to understanding the properties of aqueous fluids in the Earth. We report first principles (FP) and classical molecular dynamics simulations of NaCl in the dilute limit, at temperat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eea90926c29c9a77459d3336db744730
https://escholarship.org/uc/item/8cf3k9r1
https://escholarship.org/uc/item/8cf3k9r1
Publikováno v:
Macromolecules. 51:9538-9546
Micelle formation generally relies on hydrophobic or electrostatic interactions between distinct regions of amphiphilic molecules. In this work, a different mechanism is considered in which nanocrystalline domains are formed from short ethylene sulfi
Autor:
Juan J. de Pablo, Giulia Galli, Jonathan K. Whitmer, Emre Sevgen, Hythem Sidky, Federico Giberti, Francois Gygi
Publikováno v:
Journal of Chemical Theory and Computation. 14:2881-2888
We present a seamless coupling of a suite of codes designed to perform advanced sampling simulations, with a first-principles molecular dynamics (MD) engine. As an illustrative example, we discuss results for the free energy and potential surfaces of
Autor:
Mohammad Rahimi, Wei Bu, Zhu Liang, Benoît Roux, Mark L. Schlossman, Binhua Lin, Monirosadat Sadati, Cem Erol, Juan J. de Pablo, Emre Sevgen, Nicholas L. Abbott, Nader Taheri Qazvini, Hadi Ramezani-Dakhel
Publikováno v:
Journal of the American Chemical Society. 139:3841-3850
Numerous applications of liquid crystals rely on control of molecular orientation at an interface. However, little is known about the precise molecular structure of such interfaces. In this work, synchrotron X-ray reflectivity measurements, accompani
Autor:
Jonathan K. Whitmer, Ashley Z. Guo, Juan J. de Pablo, Hythem Sidky, Emre Sevgen, Jeffrey A. Hubbell
Publikováno v:
The Journal of chemical physics. 148(13)
A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here,