Synergy of classical and quantum computational methods to investigate the properties of microporous materials

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. However, advanced methods like CutMix blend images and assign labels based on pixel ratios, often introducing label noise by neglecting ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

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 ...

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 ...

This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a hig ...

Industrial chemistry heavily relies on traditional separation methods which are both energy-demanding and environmentally detrimental. This thesis addresses critical separation challenges, specifically carbon capture applications and the separation of ethy ...

Hydrogen clathrate hydrates are ice-like crystalline substances in which hydrogen molecules are trapped inside polyhedral cages formed by the water molecules. Small cages can host only a single H-2 molecule, while each large cage can be occupied by up to f ...

Metal-organic frameworks (MOFs) are a rapidly growing class of materials that offer great promise in various applications. However, the synthesis remains challenging: for example, a range of crystal structures can often be accessed from the same building b ...

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 ...

Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...

The escalating energy demand and the imperative necessity to reduce the carbon footprint require transformative approaches to energy conversion. Materials chemistry plays a pivotal role in addressing these global challenges by developing novel materials fo ...

Base excision repair enzymes (BERs) detect and repair oxidative DNA damage with efficacy despite the small size of the defects and their often only minor structural impact. A charge transfer (CT) model for rapid scanning of DNA stretches has been evoked to ...

Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space. We highlight he ...

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

Ordered two-dimensional (2D) materials hosting Å-scale pores are highly promising for enabling challenging separation, thanks to well-defined pore geometry resulting in tight confinement of ions when hosted inside the pore. In addition, the 2D nature of th ...

Single-layer graphene, hosting a high density of functionalized molecular-sieving atom-thick pores, is considered to be an excellent material for gas separation membranes. These functionalized atom-thick pores enable the shortest transport pathway across t ...

MOFs are a class of porous crystalline materials whose unique properties have led to applicability in several fields ranging from gas adsorption to drug delivery. Despite their high potential, MOFs are usually found as fine powders, a property that can lim ...

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack ...

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Synergy of classical and quantum computational methods to investigate the properties of microporous materials

Chat with Graph Search

SaliencyMix plus : Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

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

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

Deep learning-based recommendation system for metal-organic frameworks (MOFs)

Harnessing Porous Materials for Efficient Gas Capture: A Computational Exploration of Structure, Function, and Workflow Automation

Large-cage occupation and quantum dynamics of hydrogen molecules in sII clathrate hydrates

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Efficient and insightful descriptors for representing molecular and material space

Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

Hybrid organic/metal-oxide shells on semiconductor nanocrystals via colloidal atomic layer deposition

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach

The rule of four: anomalous distributions in the stoichiometries of inorganic compounds

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Crystal, defect, and morphology engineering of porous two-dimensional materials for ionic separation

Functionalized Å-scale Pores in Graphene for Carbon Capture

Densification and shaping of pure Cu-BTC powders using a solid-state chemical transformation

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Fungal community composition predicts forest carbon storage at a continental scale

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites