Publications related to Group (periodic table)

Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table

Changpeng Lin, Hong Zhang, Chen Shen, Yong Zhao

Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottlen ...

NATURE PORTFOLIO2023

Plasmonic effects in the neutralization of slow ions at a metallic surface

Marnik Bercx

Secondary electron emission is an important process that plays a significant role in several plasma-related applications. As measuring the secondary electron yield experimentally is very challenging, quantitative modelling of this process to obtain reliabl ...

WILEY-V C H VERLAG GMBH2023

Koopmans Spectral Functionals in Periodic Boundary Conditions

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Riccardo De Gennaro

Koopmans spectral functionals aim to describe simultaneously ground-state properties and charged excitations of atoms, molecules, nanostructures, and periodic crystals. This is achieved by augmenting standard density functionals with simple but physically ...

AMER CHEMICAL SOC2022

Improved Cooperation by Exploiting a Common Signal

Boi Faltings, Zeki Doruk Erden, Panayiotis Danassis

Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, rea ...

International Foundation for Autonomous Agents and Multiagent Systems2022

Neural-network quantum states for periodic systems in continuous space

Giuseppe Carleo, Gabriel Maria Pescia

We introduce a family of neural quantum states for the simulation of strongly interacting systems in the presence of spatial periodicity. Our variational state is parametrized in terms of a permutationally invariant part described by the Deep Sets neural-n ...

AMER PHYSICAL SOC2022

Synthesis, structural characterization, and coordination chemistry of imidazole-based alkylidene ketenes

Rosario Scopelliti, Kay Severin, Farzaneh Fadaei Tirani, Paul Varava, Wolfram Feuerstein

Alkylidene ketenes typically display high intrinsic reactivity, impeding isolation on a preparative scale. Herein, we report the synthesis of alkylidene ketenes by reaction of imidazole-based diazoolefins with carbon monoxide. The good thermal stability of ...

Royal Society of Chemistry2021

Crowding and the importance of grouping and segmentation processes in human vision

Alban Bornet

Human vision has evolved to make sense of a world in which elements almost never appear in isolation. Surprisingly, the recognition of an element in a visual scene is strongly limited by the presence of other nearby elements, a phenomenon known as visual c ...

EPFL2021

Spatial and temporal integration of visual features

Oh-Hyeon Choung

Visual processing can be seen as the integration and segmentation of features. Objects are composed of contours, integrated into shapes and segmented from other contours. Information also needs to be integrated to solve the ill-posed problems of vision. Fo ...

EPFL2021

A class of 2-local finite spectra which admit a v1/2-self-map

Philip Egger

At the prime 2, Behrens, Hill, Hopkins and Mahowald showed that M-2 (1, 4) admits a 32-periodic v(2)-self-map. More recently, in joint work with Mahowald, we showed that A(1) also admits a 32-periodic v(2)-self-map. This leads to the question of whether th ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

A water-based and metal-free dye solar cell exceeding 7% efficiency using a cationic poly(3,4-ethylenedioxythiophene) derivative

A green, efficient and stable solar cell based only on water and safe and cheap elements of the periodic table is proposed in this work, finally consolidating (also from a sustainability viewpoint) the concept of "artificial photosynthesis" studied for dec ...

2020

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

The Periodic Table and Kinetics?

André Merbach, Lothar Helm

Mendeleev in his first publication ordered the chemical elements following an apparent periodicity of properties such as atomic volume and valence. The reactivity of the elements was only studied systematically many years later. To illustrate the systemati ...

2019

To bend or not to bend, the dilemma of multiple bonds

Michele Pizzochero

Beyond the second row of the periodic table, the nature of the multiple bonds between the elements of the main groups remains yet elusive, and "non-classical" bonding schemes are often invoked for their description. Here, focusing on group 14, we have perf ...

ROYAL SOC CHEMISTRY2019

Predicting the reflectivity and colour of metals from first principles

Gianluca Prandini

Gold and copper are the only two elemental metals that show a characteristic colour, due to the presence of a drop in the reflectivity curve inside the visible range. Reflectivities of all other metals are in general high and flat for all visible frequenci ...

EPFL2019

Crystal field, ligand field, and interorbital effects in two-dimensional transition metal dichalcogenides across the periodic table

Oleg Yazyev, Diego José Pasquier

Two-dimensional (2D) transition metal dichalcogenides (TMDs) exist in two polymorphs, referred to as 1T and 1H, depending on the coordination sphere of the transition metal atom. The broken octahedral and trigonal prismatic symmetries lead to different cry ...

IOP PUBLISHING LTD2019

Crystalline and correlated phases in two-dimensional transition metal dichalcogenides

Diego José Pasquier

This thesis is dedicated to the study of various aspects of the electronic structure of two-dimensional transition metal dichalcogenides (TMDs) of chemical composition MX

_2

(where M is a transition metal atom and X= S, Se, Te), using a combination of \te ...

EPFL2019

Electronic Structure and Topology of Novel Materials

Antimo Marrazzo

The ground and excited electronic states are responsible for several materials' properties. The modern capability of rapidly solving on a computer the fundamental equations of relativistic or semi-relativistic quantum mechanics allows to compute the electr ...

EPFL2019

Representations and descriptors unifying the study of molecular and bulk systems

Kevin Rossi

Establishing a unified framework for describing the structures of molecular and periodic systems is a long-standing challenge in physics, chemistry, and material science. With the rise of machine learning methods in these fields, there is a growing need fo ...

WILEY2019

Non-Precious Electrodes for Practical Alkaline Water Electrolysis

Hubert Girault, Alberto Battistel, Alejandro Nicolás Colli

Water electrolysis is a promising approach to hydrogen production from renewable energy sources. Alkaline water electrolyzers allow using non-noble and low-cost materials. An analysis of common assumptions and experimental conditions (low concentrations, l ...

2019

Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elements

Michele Ceriotti, Félix Benedito Clément Musil, Michael John Willatt

Machine-learning of atomic-scale properties amounts to extracting correlations between structure, composition and the quantity that one wants to predict. Representing the input structure in a way that best reflects such correlations makes it possible to im ...

2018