Results 81 to 90 of about 921,873 (354)

Equilibrium Bond Lengths from Orbital-Free Density Functional Theory

Molecules, 2020
This work presents an investigation to model chemical bonding in various dimers based on the atomic fragment approach. The atomic fragment approach is an ab-initio, parameter-free implementation of orbital-free density functional theory which is based on
Kati Finzel
doaj   +1 more source

The epithelial barrier theory proposes a comprehensive explanation for the origins of allergic and other chronic noncommunicable diseases

FEBS Letters, EarlyView.
Exposure to common noxious agents (1), including allergens, pollutants, and micro‐nanoplastics, can cause epithelial barrier damage (2) in our body's protective linings. This may trigger an immune response to our microbiome (3). The epithelial barrier theory explains how this process can lead to chronic noncommunicable diseases (4) affecting organs ...
Can Zeyneloglu, Huseyn Babayev, Ismail Ogulur, Sena Ardicli, Yagiz Pat, Duygu Yazici, Bingjie Zhao, Lihong Chang, Xiaoqing Liu, Paolo D'Avino, Manru Li, Ceren Biçer, Fatma Hacer Kurtoğlu Babayev, Raja Dhir, Kari C. Nadeau, Marie‐Charlotte Brüggen, Mubeccel Akdis, Cezmi A. Akdis   +17 more
wiley   +1 more source

Density-functional theory formulated in terms of functional integrals

AIP Advances
In a previous study, the author formulated the density functional theory in terms of functional integrals. It was valid at zero and finite temperature.
Gérald Faussurier
doaj   +1 more source

Efficient learning of a one-dimensional density functional theory

Physical Review Research, 2020
Density functional theory underlies the most successful and widely used numerical methods for electronic structure prediction of solids. However, it has the fundamental shortcoming that the universal density functional is unknown.
M. Michael Denner, Mark H. Fischer, Titus Neupert   +2 more
doaj   +1 more source

Machine Learning Approaches toward Orbital-free Density Functional Theory: Simultaneous Training on the Kinetic Energy Density Functional and Its Functional Derivative

Journal of Chemical Theory and Computation, 2020
Orbital-free approaches might offer a way to boost the applicability of density functional theory by orders of magnitude in system size. An important ingredient for this endeavor is the kinetic energy density functional. Snyder et al. [Phys. Rev.
R. Meyer, Manuel Weichselbaum, A. Hauser
semanticscholar   +1 more source

Goodbye flat lymphoma biology

FEBS Letters, EarlyView.
Three‐dimensional (3D) biological systems have become key tools in lymphoma research, offering reliable in vitro and ex vivo platforms to explore pathogenesis and support precision medicine. This review highlights current 3D non‐Hodgkin lymphoma models, detailing their features, advantages, and limitations, and provides a broad perspective on future ...
Carla Faria, Cèlia Dobaño‐López, Patricia Pérez‐Galán, Christine Bezombes   +3 more
wiley   +1 more source

Density functional theory

Density functional theory (DFT) is an essential building block for modern theoretical physics, chemistry, and engineering, especially those concerning electronic properties. Through decades of development, various program packages for first-principles electronic structure calculation are now available.
Nomura, Yusuke, Akashi, Ryosuke
openaire   +2 more sources

Stochastic density functional theory

WIREs Computational Molecular Science, 2019
Linear‐scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn–Sham density matrix (DM). This causes a problem since many types of large systems of interest have a rather broad DM range and are therefore not amenable to ...
Roi Baer, Daniel Neuhauser, Ben Shpiro, Eran Rabani, Eran Rabani, Eran Rabani, Marcel David Fabian   +6 more
openaire   +6 more sources

From omics to AI—mapping the pathogenic pathways in type 2 diabetes

FEBS Letters, EarlyView.
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan, Lu Qi, Pierre Zalloua   +2 more
wiley   +1 more source

Thermostable neutral metalloprotease from Geobacillus sp. EA1 does not share thermolysin's preference for substrates with leucine at the P1′ position

FEBS Letters, EarlyView.
Knowing how proteases recognise preferred substrates facilitates matching proteases to applications. The S1′ pocket of protease EA1 directs cleavage to the N‐terminal side of hydrophobic residues, particularly leucine. The S1′ pocket of thermolysin differs from EA's at only one position (leucine in place of phenylalanine), which decreases cleavage ...
Grant R. Broomfield, Torsten Kleffmann, David J. Saul, Sigurd M. Wilbanks   +3 more
wiley   +1 more source