Publications associées à The role of dispersion forces on the atomic structure of glassy chalcogenides: The case of GeSe4 and GeS4

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

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

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Visualizing Chiral Interactions in Carbohydrates Adsorbed on Au(111) by High-Resolution STM Imaging

Klaus Kern, Stephan Rauschenbach, Uta Schlickum

Carbohydrates are the most abundant organic material on Earth and the structural "material of choice" in many living systems. Nevertheless, design and engineering of synthetic carbohydrate materials presently lag behind that for protein and nucleic acids. ...

Wiley-VCH Verlag GmbH2023

Structures of the (Imidazole)(n)H+ ... Ar (n=1,2,3) complexes determined from IR spectroscopy and quantum chemical calculations

Valeriu Scutelnic

Here, we present new cryogenic infrared spectra of the (Imidazole) H-n(+) (n=1,2,3) ions. The data was obtained using helium tagging infrared predissociation spectroscopy. The new results were compared with the data obtained by Gerardi et al. (Chem. Phys. ...

SPRINGER/PLENUM PUBLISHERS2023

Unified theory of atom-centered representations and message-passing machine-learning schemes

Michele Ceriotti, Jigyasa Nigam, Guillaume André Jean Fraux, Sergey Pozdnyakov

Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-cen ...

AIP Publishing2022

Nuclei with Up to A=6 Nucleons with Artificial Neural Network Wave Functions

Giuseppe Carleo

The ground-breaking works of Weinberg have opened the way to calculations of atomic nuclei that are based on systematically improvable Hamiltonians. Solving the associated many-body Schrodinger equation involves non-trivial difficulties, due to the non-per ...

SPRINGER WIEN2022

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Anne-Clémence Corminboeuf, Veronika Juraskova, Rubén Laplaza Solanas, Frédéric Célerse

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Evidence of a coupled electron-phonon liquid in NbGe2

Mathieu François Padlewski, Philip Johannes Walter Moll, Matthias Carsten Putzke, Hao Yang

Whereas electron-phonon scattering relaxes the electron's momentum in metals, a perpetual exchange of momentum between phonons and electrons may conserve total momentum and lead to a coupled electron-phonon liquid. Such a phase of matter could be a platfor ...

Nature Portfolio2021

Variational Monte Carlo Calculations of A

Giuseppe Carleo

The complexity of many-body quantum wave functions is a central aspect of several fields of physics and chemistry where nonperturbative interactions are prominent. Artificial neural networks (ANNs) have proven to be a flexible tool to approximate quantum m ...

AMER PHYSICAL SOC2021

Facilitating Experiential Learning in Higher Education Teaching and Supervising in Labs, Fieldwork, Studios, and Projects

Siara Ruth Isaac, Roland John Tormey

This book provides evidence-informed and practical advice on how to design, teach, and facilitate hands-on, experiential learning in practical higher education settings. With rich case studies and carefully considered analysis tasks, all underpinned by res ...

Routledge2021

Atom-surface van der Waals potentials of topological insulators and semimetals from scattering measurements

Davide Campi

The phenomenology of resonant scattering has been known since the earliest experiments upon scattering of atomic beams from surfaces and is a means of obtaining experimental information about the fundamentals of weak adsorption systems in the van der Waals ...

2021

Coherent energy exchange between carriers and phonons in Peierls-distorted bismuth unveiled by broadband XUV pulses

Iurii Timrov

In Peierls-distorted materials, photoexcitation leads to a strongly coupled transient response between structural and electronic degrees of freedom, always measured independently of each other. Here we use transient reflectivity in the extreme ultraviolet ...

AMER PHYSICAL SOC2021

Incompleteness of Atomic Structure Representations

Michele Ceriotti, Michael John Willatt, Sergey Pozdnyakov

Many-body descriptors are widely used to represent atomic environments in the construction of machine-learned interatomic potentials and more broadly for fitting, classification, and embedding tasks on atomic structures. There is a widespread belief in the ...

AMER PHYSICAL SOC2020

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Michele Ceriotti, Michael John Willatt

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020

Balancing Density Functional Theory Interaction Energies in Charged Dimers Precursors to Organic Semiconductors

Anne-Clémence Corminboeuf, Alberto Fabrizio, Riccardo Petraglia

The pursuit of an increasingly accurate description of intermolecular interactions within the framework of Kohn-Sham density functional theory (KS-DFT) has motivated the construction of numerous benchmark databases over the past two decades. By far, the la ...

AMER CHEMICAL SOC2020

Deterministic and Statistical Approaches to Quantum Chemistry

Alberto Fabrizio

The field of quantum chemistry has recently undergone a series of paradigm shifts, including a boom in machine learning applications that target the electronic structure problem. Along with these technological innovations, the community continues to identi ...

EPFL2020

Modelling long-range interactions in multiscale simulations of ferromagnetic materials

Doghonay Arjmand

Atomistic-continuum multiscale modelling is becoming an increasingly popular tool for simulating the behaviour of materials due to its computational efficiency and reliable accuracy. In the case of ferromagnetic materials, the atomistic approach handles th ...

SPRINGER2020

Thermal spin crossover in Fe(ii) and Fe(iii). Accurate spin state energetics at the solid state

Sergio Vela Llausi, Maria Fumanal Quintana

The thermal spin crossover (SCO) phenomenon refers to an entropy-driven spin transition in some materials based on d(6)-d(9) transition metal complexes. While its molecular origin is well known, intricate SCO behaviours are increasingly common, in which th ...

ROYAL SOC CHEMISTRY2020