Results 71 to 80 of about 1,035,532 (286)

Chemical bonding in the quantum and classical models

Salud, Ciencia y Tecnología - Serie de Conferencias
Many questions arise when writing reaction mechanisms, and therefore require answers for which the molecular formulas of the different species, reagents or intermediates, conform to the rules of classical and quantum models for the construction of different species, and show single, double or triple bonds, non-bonding doublets, electron vacancies and ...
Lahbib Abbas, Lahcen Bih, Abdessamad Mezdar Abdessamad Mezdar, Khalid Sellam, Ilyas Jalafi, Zahra Ramzi   +5 more
openaire   +2 more sources

Atomistic simulations of transition metal catalyzed reactions using specialized force fields and quantum mechanical methods [PDF]

, 2014
In this thesis, we utilized current computational methods for exploring molecular architectures and dynamical properties of metal-catalyzed reactions. The importance of transition metals (TM) in catalysis was our motivation to work on the development of ...
Hofmann, Franziska D.
core   +1 more source

Deep neural network based quantum simulations and quasichemical theory for accurate modeling of molten salt thermodynamics

, 2022
With dual goals of efficient and accurate modeling of solvation thermodynamics in molten salt liquids, we employ ab initio molecular dynamics (AIMD) simulations, deep neural network interatomic potentials (NNIP), and quasichemical theory (QCT) to ...
Thomas, Beck, Yu, Shi, Stephen, Lam
core   +1 more source

Carboxylic‐Acid Functionalized Multiwalled Carbon Nanotube‐Alkane‐Based Resistive Temperature Sensor for Cold Chain Applications

Advanced Engineering Materials, EarlyView.
This study presents a reversible temperature sensor with high switching ratio, ∼103. The device is fabricated using PET‐ITO and carbon nanotube dispersions in alkane. Considering its application in cold chain logistics, a proof‐of‐concept with LED is showcased. Thus, a temperature drop below the threshold temperature (crystallization temperature of the
Sunil Kumar Behera, Philippe Marrec, A. Jorge Parola, Madalena Dionísio, Hugo Águas, Andreia F. M. Santos, Hamed Pourkheirollah, Donald Lupo, César A. T. Laia   +8 more
wiley   +1 more source

Quantum Chemical Modeling of Hydrogen Binding in Metal--Organic Frameworks: Validation, Insight, Predictions and Challenges.

, 2023
A detailed chemical understanding of \ce{H2} interactions with binding sites in the nanoporous crystalline structure of metal--organic frameworks (MOFs) can lay a sound basis for the design of new sorbent materials.
Kurtis , Carsch, Justin, Talbot, Yuto , Yabuuchi, Jeffrey R. , Long, Hiroyasu , Furukawa, Henry Z. H. , Jiang, Martin , Head-Gordon, Romit, Chakraborty, Hengyuan , Shen   +8 more
core   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Transition state structure detection with machine learningś

npj Computational Materials
Transition structure calculations via quantum chemistry methods have become a staple in modern chemical reaction research. Yet, success rates in optimizing transition structures rely heavily on rational initial guesses and expert supervision.
Yitao Si, Yiding Ma, Tao Yu, Yifan Wu, Yingzhe Liu, Weipeng Lai, Zhixiang Zhang, Jinwen Shi, Liejin Guo, Oleg V. Prezhdo, Maochang Liu   +10 more
doaj   +1 more source

Quantum‐chemical modeling of squaric acid ferroelectric behavior

International Journal of Quantum Chemistry, 2010
AbstractThe properties of layered 2d‐ferroelectric and at the same time 3d‐antiferroelectric materials H2C4O4/D2C4O4 are studied by quantum‐chemical approach using pseudospin formalism in frames of Ising‐type model Hamiltonian with tunneling terms.
Dolin S.P., Levin A.A., Mikhailova T.Yu., Solin M.V., Zinova N.V.   +4 more
openaire   +3 more sources

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

Predicting Infrared Spectra with Message Passing Neural Networks

, 2021
Infrared (IR) spectroscopy remains an important tool for chemical characterization and identification. Chemprop-IR has been developed as a software package for the prediction of IR spectra through the use of machine learning.
Green Jr, William H, McGill, Charles, Guan, Yanfei, Forsuelo, Michael   +3 more
core   +1 more source