Publications related to What Are the Best Materials To Separate a Xenon/Krypton Mixture?

Related publications (41)

Constructing multicomponent cluster expansions with machine-learning and chemical embedding

Yann Lorris Müller, Anirudh Raju Natarajan

Cluster expansions are commonly employed as surrogate models to link the electronic structure of an alloy to its finite-temperature properties. Using cluster expansions to model materials with several alloying elements is challenging due to a rapid increas ...

NATURE PORTFOLIO2025

On the added value of sequential deep learning for the upscaling of evapotranspiration

Devis Tuia

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

2025

Synergistically optimizing electrical and thermal transport in layered BiCuSeO via biaxial strain modulation

Changpeng Lin

Decoupling electrical and thermal parameters in figure of merit (zT) is still a major challenge for thermoelectric materials. Layered oxyselenides have the advantages of superlattice structures, including the quantum confinement effect and independent domi ...

2025

Preliminary Sensitivity Analysis of Time-Dependent Code Outputs in Fuel Performance Models Using OFFBEAT for Future Calibration

Mathieu Hursin, Alessandro Scolaro, Edoardo Luciano Brunetto, Sara Maccario

Fuel performance codes are essential for predicting fuel rod behavior in nuclear reactors. These codes comprise a complex system of models with empirical constants that require calibration against experimental data. To support this calibration, this study ...

American Nuclear Society2025

The rise of transient robotics

Dario Floreano, Alexander Scott Keller

Transient robots are robots designed to be non-long-lasting and degradable over time. This design philosophy is ideal for a wide range of applications, from environmental monitors to implantable systems. In this commentary, we explore the concept of transi ...

Elsevier BV2024

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

Xhemsi Malja

Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

EPFL2024

High-Throughput Nanopore Fabrication and Classification Using Xe-Ion Irradiation and Automated Pore-Edge Analysis

Aleksandra Radenovic, Andras Kis, Martina Lihter, Michal Daniel Macha, Sanjin Marion, Mukesh Kumar Tripathi, Mukeshchand Thakur

Large-area nanopore drilling is a major bottleneck in state-of-the-art nanoporous 2D membrane fabrication protocols. In addition, high-quality structural and statistical descriptions of as-fabricated porous membranes are key to predicting the corresponding ...

AMER CHEMICAL SOC2022

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

cRacklet: a spectral boundary integral method library for interfacial rupture simulation

Jean-François Molinari, Fabian Barras, Thibault Didier Roch

The study of dynamically propagating rupture along interfaces is of prime importance in various fields and system sizes, including tribology (nm to m), engineering (mm to m) and geophysics (m to km) (Armstrong-Hélouvry et al., 1994; Ben-Zion, 2008; Vanossi ...

2022

A Comparative Analysis of Tools & Task Types for Measuring Computational Problem-Solving

Richard Lee Davis, Engin Walter Bumbacher, Jérôme Guillaume Brender

How to measure students' Computational Problem-Solving (CPS) competencies is an ongoing research topic. Prevalent approaches vary by measurement tools (e.g., interactive programming, multiple-choice tests, or programming-independent tests) and task types ( ...

Association for Computing Machinery2024

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Mahdi Hijazi

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

EPFL2024

Towards coupling conventional with high-fidelity fuel behavior analysis tools

Andreas Pautz, Carlo Fiorina, Alessandro Scolaro, Edoardo Luciano Brunetto

Multi-dimensional fuel performance codes have the potential to enhance the understanding of complex phenomena affecting fuel integrity, but their application is often limited by the high computational cost. Recognizing that many multi-dimensional aspects s ...

PERGAMON-ELSEVIER SCIENCE LTD2022

The Electronic-Structure Genome of Inorganic Crystals

Junfeng Qiao

Electronic structure theory plays a central role in understanding properties of crystalline materials. Among all the ab initio methods, density functional theory (DFT) is the most popular choice due to its balance between accuracy and computational cost, a ...

EPFL2024

Adhesive wear with a coarse-grained discrete element model

Jean-François Molinari, Son-Jonathan Pham-Ba

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high computational c ...

ELSEVIER SCIENCE SA2022

Computational Studies of the Proton-Coupled Metal Ion Transport in the SLC11/NRAMP Family of Transporters

Maria Letizia Merlini

In the last years, it has been demonstrated a link between the overload of metal ions inside nervous system cells and the onset of severe neurodegenerative diseases. This prompted the investigation of the structural and functional properties of transporter ...

EPFL2022

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2023

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Computational design of novel protein–protein interactions – An overview on methodological approaches and applications

Bruno Emanuel Ferreira De Sousa Correia, Anthony Marchand, Alexandra Krina Van Hall-Beauvais

Protein–protein interactions (PPIs) govern numerous cellular functions in terms of signaling, transport, defense and many others. Designing novel PPIs poses a fundamental challenge to our understanding of molecular interactions. The capability to robustly ...

2022

A general and efficient framework for atomistic machine learning

Félix Benedito Clément Musil

Over the last two decades, many technological and scientific discoveries, ranging from the development of materials for energy conversion and storage through the design of new drugs, have been accelerated by the use of preliminary in silico experiments, to ...

EPFL2021