Quantum Chemistry Meets Machine Learning

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Over the past decade, lead halide perovskites (LHPs) have received considerable attention thanks to their impressive optoelectronic properties. Today, LHP-based devices are one of the most efficient single-junction solar cells, with power-conversion effici ...

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...

Semiconducting polymers are being studied intensively for optoelectronic device applications, including solution-processed light-emitting diodes (PLEDs). Charge traps in polymers limit the charge transport and thus the PLED efficiency. It is firmly establi ...

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used i ...

Monitoring human sweat with wearable biochemical sensors could give insights into the hydration, fatigue, and health status, tracking the variations of biomarkers non-invasively and in real-time. In this field, organic electrochemical transistors (OECTs) a ...

Over the last two decades, data-powered machine learning (ML) tools have profoundly transformed numerous scientific fields. In computational chemistry, machine learning applications have permitted faster predictions of chemical properties and provided powe ...

Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

Polymeric semiconductors have gained significant attention in the field of organic electronics due to their unique properties and potential applications. Through their ability to transport charge carriers and to absorb or emit light, they have attracted mu ...

The high-throughput exploration and screening of molecules for organic electronics involves either a 'top-down' curation and mining of existing repositories, or a 'bottom-up' assembly of user-defined fragments based on known synthetic templates. Both are t ...

The color-tuning strategies of solid-state light-emitting devices (ss-LEDs) are mainly focused on engineering molecular structures. In this paper, for the first time, we developed a facile strategy for tuning the electroluminescence (EL) color from orange ...

The exploration of open quantum many-body systems -systems of microscopic size exhibiting quantum coherence and interacting with their surrounding- has emerged as a key research area over the last years. The recent advances in controlling and preserving qu ...

Singlet fission (SF) is a multiexciton-generating process whereby an excited state singlet (S1) is converted into two lower-energy triplets (T1). The inclusion of a SF-capable material into a photovoltaic device offers the potential for the absorption of p ...

An enduring challenge in constructing mechanical-oscillator-based hybrid quantum systems is to ensure engineered coupling to an auxiliary degree of freedom and maintain good mechanical isolation from the environment, that is, low quantum decoherence, consi ...

Pixelation is common in quantum imaging systems and limit the image spatial resolution. Here, the authors introduce a pixel super-resolution approach based on measuring the full spatially-resolved joint probability distribution of spatially-entangled photo ...

Squaraines are organic dyes showing the advantages of a simple synthesis, high absorption coefficients and tunable bandgaps from the visible to the near-infrared (NIR) region. Their molecular structure is based on a polymethine chain and a donor-acceptor-d ...

Transition-metal dichalcogenide bilayers exhibit a rich exciton landscape including layer-hybridized excitons, i.e. excitons which are of partly intra- and interlayer nature. In this work, we study hybrid exciton-exciton interactions in naturally stacked W ...

The work presented in this thesis is focused on the design and discovery of new luminescent, porous, crystalline materials for targeted applications. In particular, we focus on luminescent Metal-Organic Frameworks (MOFs) and Organic Molecules of Intrinsic ...

Molecules with inversion of the singlet and triplet excited-state energies are highly promising for the development of organic light-emitting diodes (OLEDs). To date, azaphenalenes are the only class of molecules where these inversions have been identified ...

Quantum many-body control is a central milestone en route to harnessing quantum technologies. However, the exponential growth of the Hilbert space dimension with the number of qubits makes it challenging to classically simulate quantum many-body systems an ...

The mechanism of photoinduced symmetry-breaking charge separation in solid cyanine salts at the base of organic photovoltaic and optoelectronic devices is still debated. Here, we employ femtosecond transient absorption spectroscopy (TAS) to monitor the cha ...

Quantum Chemistry Meets Machine Learning

Chattez avec Graph Search

Ultrafast carrier and quasiparticle dynamics in strongly confined perovskite nanoplatelets

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

Electron Trap Dynamics in Polymer Light-Emitting Diodes

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

Configurable Organic Electrochemical Transistors with Printed Functional Materials for Multiplexed Sweat Analysis

Kernel Methods and Similarity Learning Applied in Computational Chemistry

Reinforcement Learning for the occupant-centric operation of building energy systems: Theoretical and experimental investigations

Drift-Diffusion Simulations of Charge Transport and Trap Dynamics in Organic Semiconductor Materials

Data-Driven Discovery of Organic Electronic Materials Enabled by Hybrid Top-Down/Bottom-Up Design

Versatile Electroluminescence Color-Tuning Strategy of an Efficient Light-Emitting Electrochemical Cell (LEC) by an Ionic Additive

Engineering and characterizing nonclassical states of light in quantum optical networks

Data-driven design of organic electronic materials

A squeezed mechanical oscillator with millisecond quantum decoherence

Pixel super-resolution with spatially entangled photons

Synthesis of NIR-Absorbing Squaraine Dyes and their Use in Organic Upconversion Devices

Electrically tunable dipolar interactions between layer-hybridized excitons

Luminescent, porous, metal-organic crystals: Design, synthesis, and applications

Symmetry-Induced Singlet-Triplet Inversions in Non-Alternant Hydrocarbons

Self-correcting quantum many-body control using reinforcement learning with tensor networks

Critical role of H-aggregation for high-efficiency photoinduced charge generation in pristine pentamethine cyanine salts