Results 71 to 80 of about 305,413 (295)

Emerging DFT Methods and Their Importance for Challenging Molecular Systems with Orbital Degeneracy

Computation, 2019
We briefly present some of the most modern and outstanding non-conventional density-functional theory (DFT) methods, which have largely broadened the field of applications with respect to more traditional calculations.
E. San-Fabián, J. C. Sancho-García
doaj   +1 more source

Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single and binary component solids [PDF]

, 2014
A combination of systematic density functional theory (DFT) calculations and machine learning techniques has a wide range of potential applications.
Maekawa, Tomoya, Seko, Atsuto, Tanaka, Isao, Tsuda, Koji   +3 more
core   +2 more sources

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

Rational Fine‐Tuning of MOF Pore Metrics: Enhanced SO2 Capture and Sensing with Optimal Multi‐Site Interactions

Advanced Functional Materials, EarlyView.
A pore tuning strategy to amplify the multi‐site MOF‐SO2 interactions is proposed to achieve an enhanced trace SO2 capture and chemiresistive sensing in highly stable isostructural DMOFs by annelating benzene rings. This work provides a facile strategy to achieve tailor‐made stable MOF materials for specific multifunctional applications.
Shanghua Xing, Abdulrahman Mohabbat, István Boldog, Jens Möllmer, Marcus Lange, Yulyan Haiduk, Tobias Heinen, Vladimir Pankov, Oliver Weingart, Christoph Janiak   +9 more
wiley   +1 more source

Theoretical and experimental investigation of magnetotransport in iron chalcogenides

Science and Technology of Advanced Materials, 2012
We explore the electronic, transport and thermoelectric properties of Fe1+ySexTe1−x compounds to clarify the mechanisms of superconductivity in Fe-based compounds.
Federico Caglieris, Fabio Ricci, Gianrico Lamura, Albert Martinelli, A Palenzona, Ilaria Pallecchi, Alberto Sala, Gianni Profeta and Marina Putti
doaj   +1 more source

Predicting electronic structures at any length scale with machine learning

npj Computational Materials, 2023
The properties of electrons in matter are of fundamental importance. They give rise to virtually all material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant gas planets.
Lenz Fiedler, Normand A. Modine, Steve Schmerler, Dayton J. Vogel, Gabriel A. Popoola, Aidan P. Thompson, Sivasankaran Rajamanickam, Attila Cangi   +7 more
doaj   +1 more source

Assessment of Various Density Functional Theory Methods for Finding Accurate Structures of Actinide Complexes

Molecules, 2022
Density functional theory (DFT) is a widely used computational method for predicting the physical and chemical properties of metals and organometals. As the number of electrons and orbitals in an atom increases, DFT calculations for actinide complexes ...
Youngjin Kwon, Hee-Kyung Kim, Keunhong Jeong   +2 more
doaj   +1 more source

Conductance of a quantum point contact based on spin-density-functional theory

, 2007
We present full quantum mechanical conductance calculations of a quantum point contact (QPC) performed in the framework of the density functional theory (DFT) in the local spin-density approximation (LDA).
A. Kristensen, G. F. Giuliani, H. Bruus, H. Mizuta, I. V. Zozoulenko, S. Datta, S. Ihnatsenka   +6 more
core   +1 more source

Calibrating DFT Formation Enthalpy Calculations by Multifidelity Machine Learning

JACS Au, 2022
Machine learning materials properties measured by experiments is valuable yet difficult due to the limited amount of experimental data. In this work, we use a multi-fidelity random forest model to learn the experimental formation enthalpy of materials with prediction accuracy higher than the empirically corrected PBE functional (PBEfe) and meta-GGA ...
Sheng Gong, Shuo Wang, Tian Xie, Woo Hyun Chae, Runze Liu, Yang Shao-Horn, Jeffrey C. Grossman   +6 more
openaire   +3 more sources

Modulating Two‐Photon Absorption in a Pyrene‐Based MOF Series: An In‐Depth Investigation of Structure–Property Relationships

Advanced Functional Materials, EarlyView.
This study investigates H4TBAPy‐based metal–organic frameworks (MOFs) ‐ NU‐1000, NU‐901, SrTBAPy, and BaTBAPy ‐ for multiphoton absorption (MPA) performance. It observes topology‐dependent variations in the 2PA cross‐section, with BaTBAPy exhibiting the highest activity.
Simon N. Deger, Helmy Pacheco Hernandez, Yang Cui, Hongxing Hao, Vanessa Ramm, David C. Mayer, Khai‐Nghi Truong, Roland A. Fischer, Jürgen Hauer, Mariana Kozlowska, Alexander Pöthig   +10 more
wiley   +1 more source