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View article: Green and sustainable metal-organic frameworks (MOFs) in wastewater treatment: A review
Green and sustainable metal-organic frameworks (MOFs) in wastewater treatment: A review Open
Metal-organic frameworks (MOFs) possess unique structural, physical, and chemical properties, making them promising materials for wastewater treatment applications, particularly in photocatalysis. However, conventional synthesis methods su…
View article: Unravelling the cleavage-rate relationship from both the experimental and theoretical standpoint: The instance of fluorite dissolution
Unravelling the cleavage-rate relationship from both the experimental and theoretical standpoint: The instance of fluorite dissolution Open
The phenomenon of solid dissolution into a solution constitutes a fundamental aspect in both natural and industrial contexts. Nevertheless, its intricate nature at the microscale poses a significant challenge for precise quantitative chara…
View article: Enhancing the electronic and photocatalytic properties of (SnO<sub>2</sub>)<sub><i>n</i></sub>/(TiO<sub>2</sub>)<sub><i>m</i></sub> oxide superlattices for efficient hydrogen production: a first-principles study
Enhancing the electronic and photocatalytic properties of (SnO<sub>2</sub>)<sub><i>n</i></sub>/(TiO<sub>2</sub>)<sub><i>m</i></sub> oxide superlattices for efficient hydrogen production: a first-principles study Open
DFT calculations reveal that strain engineering in (SnO 2 ) n /(TiO 2 ) m superlattices provides a promising strategy to enhance photocatalytic properties, particularly for hydrogen production via water splitting.
View article: Vector Field Oriented Diffusion Model for Crystal Material Generation
Vector Field Oriented Diffusion Model for Crystal Material Generation Open
Discovering crystal structures with specific chemical properties has become an increasingly important focus in material science. However, current models are limited in their ability to generate new crystal lattices, as they only consider a…
View article: Vector Field Oriented Diffusion Model for Crystal Material Generation
Vector Field Oriented Diffusion Model for Crystal Material Generation Open
Discovering crystal structures with specific chemical properties has become an increasingly important focus in material science. However, current models are limited in their ability to generate new crystal lattices, as they only consider a…
View article: Optimized Crystallographic Graph Generation for Material Science
Optimized Crystallographic Graph Generation for Material Science Open
Graph neural networks are widely used in machine learning applied to chemistry, and in particular for material science discovery. For crystalline materials, however, generating graph-based representation from geometrical information for ne…
View article: Unified Model for Crystalline Material Generation
Unified Model for Crystalline Material Generation Open
One of the greatest challenges facing our society is the discovery of new innovative crystal materials with specific properties. Recently, the problem of generating crystal materials has received increasing attention, however, it remains u…
View article: Equivariant Message Passing Neural Network for Crystal Material Discovery
Equivariant Message Passing Neural Network for Crystal Material Discovery Open
Automatic material discovery with desired properties is a fundamental challenge for material sciences. Considerable attention has recently been devoted to generating stable crystal structures. While existing work has shown impressive succe…
View article: Unified Model for Crystalline Material Generation
Unified Model for Crystalline Material Generation Open
One of the greatest challenges facing our society is the discovery of new innovative crystal materials with specific properties. Recently, the problem of generating crystal materials has received increasing attention, however, it remains u…
View article: Optimized Crystallographic Graph Generation for Material Science
Optimized Crystallographic Graph Generation for Material Science Open
Graph neural networks are widely used in machine learning applied to chemistry, and in particular for material science discovery. For crystalline materials, however, generating graph-based representation from geometrical information for ne…
View article: Design of Potent Inhibitors Targeting the Main Protease of SARS-CoV-2 Using QSAR Modeling, Molecular Docking, and Molecular Dynamics Simulations
Design of Potent Inhibitors Targeting the Main Protease of SARS-CoV-2 Using QSAR Modeling, Molecular Docking, and Molecular Dynamics Simulations Open
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a serious global public health threat. The evolving strains of SARS-CoV-2 have reduced the effectiveness of vaccines. Therefore, antiviral drugs against SARS-CoV-2 a…
View article: Equivariant Message Passing Neural Network for Crystal Material Discovery
Equivariant Message Passing Neural Network for Crystal Material Discovery Open
Automatic material discovery with desired properties is a fundamental challenge for material sciences. Considerable attention has recently been devoted to generating stable crystal structures. While existing work has shown impressive succe…
View article: Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning: Raw Data and Generation Script
Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning: Raw Data and Generation Script Open
Determining the association constant between a cyclodextrin and a guest molecule is an important task for various applications in various industrial and academical fields. However, such a task is time consuming, tedious and requires sample…
View article: Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning
Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning Open
Determining the association constant between a cyclodextrin and a guest molecule is an important task for various applications in various industrial and academical fields. However, such a task is time consuming, tedious and requires sample…
View article: Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning
Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning Open
Determining the association constant between a cyclodextrin and a guest molecule is an important task for various applications in various industrial and academical fields. However, such a task is time consuming, tedious and requires sample…
View article: Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning: Raw Data and Generation Script
Curated Dataset of Association Constants Between a Cyclodextrin and a Guest for Machine Learning: Raw Data and Generation Script Open
Determining the association constant between a cyclodextrin and a guest molecule is an important task for various applications in various industrial and academical fields. However, such a task is time consuming, tedious and requires sample…
View article: Photoelectrochemical properties of copper pyrovanadate (Cu<sub>2</sub>V<sub>2</sub>O<sub>7</sub>) thin films synthesized by pulsed laser deposition
Photoelectrochemical properties of copper pyrovanadate (Cu<sub>2</sub>V<sub>2</sub>O<sub>7</sub>) thin films synthesized by pulsed laser deposition Open
The photoelectrochemical properties of copper pyrovanadate (bulk α-Cu 2 V 2 O 7 and thin films β-Cu 2 V 2 O 7 elaborated by pulsed laser deposition) were investigated. For thin films, the best photocurrent efficiency was obtained under blu…
View article: Equivariant Graph Neural Network for Crystalline Materials
Equivariant Graph Neural Network for Crystalline Materials Open
Proceedings of the 1st International Workshop on Spatio-Temporal Reasoning and Learning co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence
View article: First-principles study of electronic structures, thermodynamic, and thermoelectric properties of the new Rattling Full Heusler compounds Ba2AgZ (Z = As, Sb, Bi)
First-principles study of electronic structures, thermodynamic, and thermoelectric properties of the new Rattling Full Heusler compounds Ba2AgZ (Z = As, Sb, Bi) Open
The ab initio calculations based on the density functional theory (DFT) using the self-consistent Full potential linearized augmented plane wave (FPLAPW) method were performed to explore the electronic structures, thermodynamic and thermoe…
View article: Molecular DFT Investigation on the Inclusion Complexation of Benzo[a]pyrene with γ-Cyclodextrin
Molecular DFT Investigation on the Inclusion Complexation of Benzo[a]pyrene with γ-Cyclodextrin Open
International audience
View article: Investigating structure, magneto-electronic, and thermoelectric properties of the new d0 quaternary Heusler compounds RbCaCZ (Z = P, As, Sb) from first principle calculations
Investigating structure, magneto-electronic, and thermoelectric properties of the new d0 quaternary Heusler compounds RbCaCZ (Z = P, As, Sb) from first principle calculations Open
The ab initio calculations based on the density functional theory (DFT) using the self-consistent full potential linearized augmented plane wave (FPLAPW) method were performed to explore the electronic structures, magnetic and thermoelectr…
View article: Recent Insights Into Electronic Performance, Magnetism and Exchange Splittings in the Cr-substituted CaO
Recent Insights Into Electronic Performance, Magnetism and Exchange Splittings in the Cr-substituted CaO Open
The first-principles computations of density functional theory are employed to characterize the structural properties, electronic structures, and ferromagnetism induced by Cr impurities in Ca(1-x)Cr(x)O compounds at concentrations x = 0. 2…
View article: Physical Properties of RhCrZ (Z= Si, Ge, P, As) Half-Heusler Compounds: A First-Principles Study
Physical Properties of RhCrZ (Z= Si, Ge, P, As) Half-Heusler Compounds: A First-Principles Study Open
We use the first-principles-based density functional theory with full potential linearized augmented plane wave method in order to investigate the structural, elastic, electronic, magnetic and thermoelectric properties of RhCrZ (Z= Si, Ge,…
View article: Ferromagnetism, half-metallicity and spin-polarised electronic structures characterisation insights in Ca<sub>1−<i>x</i></sub>Ti<i><sub>x</sub></i>O
Ferromagnetism, half-metallicity and spin-polarised electronic structures characterisation insights in Ca<sub>1−<i>x</i></sub>Ti<i><sub>x</sub></i>O Open
In this study, we have computed the structural, electronic and half-metallic ferromagnetic properties of Ca1−xTixO compounds at concentrations x = 0.125, 0.25, 0.5 and 0.75 by employing the first-principle approaches of density functional …