Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Nils E. R. Zimmermann"'
Publikováno v:
Frontiers in Materials, Vol 4 (2017)
Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity
Externí odkaz:
https://doaj.org/article/1a4a262d9b9e44708e76689258c6eb00
Autor:
Kristin A. Persson, Muratahan Aykol, Hillary Pan, Nils E. R. Zimmermann, Matthew Horton, Anubhav Jain, Alex M. Ganose
Publikováno v:
Inorganic Chemistry. 60:1590-1603
Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning (ML) and automatic structura
Thermodiffusion is a coupled heat and mass transport process, in which a temperature gradient initiates the separation of components in a mixture. It occurs in many natural and technical processes, but experimental measurements are indirect and expen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8c98193c20692d08a512d5372a6d64e
https://doi.org/10.26434/chemrxiv-2022-56xw9
https://doi.org/10.26434/chemrxiv-2022-56xw9
Publikováno v:
Zeitschrift für Kristallographie - Crystalline Materials. 234:437-450
Zeolites are important microporous framework materials, where 200+ structures are known to exist and many millions so-called hypothetical materials can be computationally created. Here, we screen the “Deem” database of hypothetical zeolite struct
Autor:
Alex M. Ganose, Muratahan Aykol, Matthew Horton, Anubhav Jain, Hillary Pan, Kristin A. Persson, Nils E. R. Zimmermann
Publikováno v:
Inorganic Chemistry: including bioinorganic chemistry, vol 60, iss 3
Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning and automatic structural ana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbbc9c78170fb8b2a3b2f7c1368236f8
https://escholarship.org/uc/item/0sj353dg
https://escholarship.org/uc/item/0sj353dg
Autor:
Nils E. R. Zimmermann, Anubhav Jain
Publikováno v:
RSC advances, vol 10, iss 10
Structure characterization and classification is frequently based on local environment information of all or selected atomic sites in the crystal structure. Therefore, reliable and robust procedures to find coordinated neighbors and to evaluate the r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fbde064116991aab80dd6bc3d4bf37e
https://escholarship.org/uc/item/4qr765x8
https://escholarship.org/uc/item/4qr765x8
Autor:
Joseph Montoya, John Dagdelen, Donny Winston, Kristin A. Persson, Shyue Ping Ong, Matthew Horton, Shreyas Cholia, Anubhav Jain, Patrick Huck, Shyam Dwaraknath, Nils E. R. Zimmermann
Publikováno v:
Handbook of Materials Modeling ISBN: 9783319429137
Handbook of Materials Modeling
Handbook of Materials Modeling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab1791a079eacb954eb4671e5520fdcb
https://doi.org/10.1007/978-3-319-44677-6_60
https://doi.org/10.1007/978-3-319-44677-6_60
Autor:
Kyle Chard, Alexander Dunn, Anubhav Jain, Logan Ward, Maxwell Dylla, Joseph Montoya, Saurabh Bajaj, Nils E. R. Zimmermann, Alireza Faghaninia, Mark Asta, Kristin A. Persson, Jiming Chen, G. Jeffrey Snyder, Kyle Bystrom, Qi Wang, Ian Foster
Publikováno v:
Computational Materials Science. 152:60-69
As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source,
Autor:
Daniel C. Hannah, Miao Liu, Maciej Haranczyk, Gerbrand Ceder, Ziqin Rong, Kristin A. Persson, Nils E. R. Zimmermann
Publikováno v:
The journal of physical chemistry letters, vol 9, iss 3
Zimmermann, NER; Hannah, DC; Rong, Z; Liu, M; Ceder, G; Haranczyk, M; et al.(2018). Electrostatic Estimation of Intercalant Jump-Diffusion Barriers Using Finite-Size Ion Models. Journal of Physical Chemistry Letters, 9(3), 628-634. doi: 10.1021/acs.jpclett.7b03199. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/6nj0h4s8
Zimmermann, NER; Hannah, DC; Rong, Z; Liu, M; Ceder, G; Haranczyk, M; et al.(2018). Electrostatic Estimation of Intercalant Jump-Diffusion Barriers Using Finite-Size Ion Models. Journal of Physical Chemistry Letters, 9(3), 628-634. doi: 10.1021/acs.jpclett.7b03199. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/6nj0h4s8
We report on a scheme for estimating intercalant jump-diffusion barriers that are typically obtained from demanding density functional theory-nudged elastic band calculations. The key idea is to relax a chain of states in the field of the electrostat
Correction to Benchmarking Coordination Number Prediction Algorithms on Inorganic Crystal Structures
Autor:
Muratahan Aykol, Anubhav Jain, Kristin A. Persson, Hillary Pan, Alex M. Ganose, Nils E. R. Zimmermann, Matthew Horton
Publikováno v:
Inorganic chemistry, vol 60, iss 10
Author(s): Pan, Hillary; Ganose, Alex M; Horton, Matthew; Aykol, Muratahan; Persson, Kristin; Zimmermann, Nils ER; Jain, Anubhav | Abstract: The corrections are typographical errors only and do not alter the results or analysis in the original manusc