Publications associées à Defect levels through hybrid density functionals: Insights and applications

Publications associées (30)

Automated all-functionals infrared and Raman spectra

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

Nature Portfolio2024

Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

Giulia Tagliabue, Alan Richard Bowman, Fateme Kiani Shahvandi, Theodoros Tsoulos

This dataset accompanies the publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films" published in Light: Science & Applications (https://doi.org/10.1038/s41377-024-01408-2). The data can be used to reproduce plots 1-4 ...

Zenodo2024

Gyrokinetic simulations of turbulence in magnetic fusion plasmas using a delta-f PIC scheme with evolving background

Moahan Murugappan

Using the GKEngine code which simulates an electrostatic plasma with adiabatic electron response under a sheared-slab geometry, an attempt at developing a hybrid approach between the delta-f and full-f schemes to describe plasma profiles exhibiting high fl ...

EPFL2024

Quantum-mechanical effects in photoluminescence from thin crystalline gold films

Giulia Tagliabue, Alan Richard Bowman, Fateme Kiani Shahvandi, Theodoros Tsoulos

Luminescence constitutes a unique source of insight into hot carrier processes in metals, including those in plasmonic nanostructures used for sensing and energy applications. However, being weak in nature, metal luminescence remains poorly understood, its ...

2024

Data-Intensive Exploration of the Photoelectrochemical Responses of Main-Group Metal Sulfides

Nicola Colonna

Materials that efficiently promote the thermodynamically uphill water-splitting reaction under solar illumination are essential for generating carbon-free ("green") hydrogen. Mapping out the combinatorial space of potential photocatalysts for this reaction ...

Amer Chemical Soc2024

Memristive Control of Plasmon-Mediated Nonlinear Photoluminescence in Au Nanowires

Konstantin Malchow

Nonlinear photoluminescence (N-PL) is a broadband photon emission arising from a nonequilibrium heated electron distribution generated at the surface of metallic nanostructures by ultrafast pulsed laser illumination. N-PL is sensitive to surface morphology ...

Amer Chemical Soc2024

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Zhenyu Wang

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

EPFL2024

Orbital-Resolved DFT plus U for Molecules and Solids

Nicola Marzari, Iurii Timrov

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Amer Chemical Soc2024

Nonempirical semilocal density functionals for correcting the self-interaction of polaronic states

Alfredo Pasquarello, Stefano Falletta

Through the use of the piecewise-linearity condition of the total energy, we correct the self-interaction for the study of polarons by constructing nonempirical functionals at the semilocal level of theory. We consider two functionals, the gamma DFT and mu ...

Aip Publishing2024

Charge-Transfer States in Organic Nanowires

Lucile Annie Chassat

Charge separation processes in organic semiconductors play a pivotal role in diverse applications ranging from photovoltaics to photocatalysis. Understanding these mechanisms, particularly the role of hybrid charge-transfer (CT) states, is essential for ad ...

EPFL2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Alfredo Pasquarello, Stefano Falletta, Jing Yang

In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We obs ...

NATURE PORTFOLIO2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

koopmans: An Open-Source Package for Accurately and Efficiently Predicting Spectral Properties with Koopmans Functionals

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Ngoc Linh Nguyen, Giovanni Borghi, Riccardo De Gennaro

Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional framework. These functionals impose a generalized piecewise linearity conditio ...

Amer Chemical Soc2023

Self-Interaction and Polarons in Density Functional Theory

Stefano Falletta

The electron self-interaction is a long-standing problem in density functional theory and is particularly critical in the description of polarons. Polarons are quasiparticles involving charge localization coupled with self-induced lattice distortions. Sinc ...

EPFL2023

Foldable Hole-Transporting Materials for Merging Electronic States between Defective and Perfect Perovskite Sites

Mohammad Khaja Nazeeruddin, Paul Joseph Dyson, Yi Zhang, Hiroyuki Kanda, Kasparas Rakstys, Jianxing Xia, Keith Gregory Brooks, Xiaoxin Gao

Defective and perfect sites naturally exist within electronic semiconductors, and considerable efforts to reduce defects to improve the performance of electronic devices, especially in hybrid organic-inorganic perovskites (ABX(3)), are undertaken. Herein, ...

Wiley-V C H Verlag Gmbh2023

Berry curvature dipole generation and helicity-to-spin conversion at symmetry-mismatched heterointerfaces

Peng Chen, Xupeng Yang

The Berry curvature dipole (BCD) is a key parameter that describes the geometric nature of energy bands in solids. It defines the dipole-like distribution of Berry curvature in the band structure and plays a key role in emergent nonlinear phenomena. The th ...

Nature Portfolio2023

Murunskite - a new class of functional material

Davor Tolj

The subject of the present work is discovery and in-depth characterization of a new class of functional materials. Tuning of the bond polarity and orbital occupation with a goal of establishing balance between localization and delocalization of electrons - ...

EPFL2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Giovanni Pizzi, Antimo Marrazzo, Junfeng Qiao

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations ...

NATURE PORTFOLIO2023