Modeling the Ga/As binary system across temperatures and compositions from first principles

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Computational Studies on the Stability of Organic-Inorganic Hybrid Halide Lead Perovskites

Perovskite-based solar cells are currently the most rapidly advancing photovoltaic technology but concerns about their long-term stability are still impeding full-scale commercialization. This thesis provides computational insights into some of the stabili ...

EPFL2024

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

Roya Moghaddasi Fereidani

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 ...

EPFL2024

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Ekaterina Krymova, Mike Seidel, Davide Di Croce, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Iop Publishing Ltd2024

Ion Spectroscopy Reveals Structural Difference for Proteins Microhydrated by Retention and Condensation of Water

Oleg Boyarkine, Andrei Zviagin

Protein ubiquitin in its +7 charge state microhydrated by 5 and 10 water molecules has been interrogated in the gas phase by cold ion UV/IR spectroscopy. The complexes were formed either by condensing water onto the unfolded bare proteins in a temperature- ...

Amer Chemical Soc2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Mixed ionic-electronic conduction in Ruddlesden-Popper and Dion-Jacobson layered hybrid perovskites with aromatic organic spacers

Michael Graetzel, Jovana Milic, Algirdas Ducinskas, Joachim Maier, Davide Moia, Mina Jung

The understanding of mixed ionic-electronic conductivity in hybrid perovskites has enabled major advances in the development of optoelectronic devices based on this class of materials. While recent investigations revealed the potential of using dimensional ...

Royal Society of Chemistry2024

Phase diagram of the J-Jd Heisenberg model on the maple leaf lattice: Neural networks and density matrix renormalization group

Pratyay Ghosh, Ronny Thomale

We microscopically analyze the nearest-neighbor Heisenberg model on the maple leaf lattice through neural quantum state (NQS) and infinite density matrix renormalization group (iDMRG) methods. Embarking to parameter regimes beyond the exact dimer singlet g ...

Amer Physical Soc2024

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Michele Ceriotti, Federico Grasselli

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

Amer Physical Soc2024

Molecular intercalation in the van der Waals antiferromagnets FePS3 and NiPS3

Bruce Normand, Ying Chen, Sheng Xu, Shuo Li, Xiaoyu Xu, Zeyu Wang, Weiqiang Yu

We have performed electrochemical treatment of the van der Waals antiferromagnetic materials FePS3 and NiPS3 with the ionic liquid EMIM-BF4, achieving significant molecular intercalation. Mass analysis of the intercalated compounds, EMIMx-FePS3 and EMIMx-N ...

Amer Physical Soc2024

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Zhenyu Wang

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

EPFL2024

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Computational Studies on the Stability of Organic-Inorganic Hybrid Halide Lead Perovskites

Mathias Dankl

EPFL2024

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

Roya Moghaddasi Fereidani

EPFL2024

Mixed ionic-electronic conduction in Ruddlesden-Popper and Dion-Jacobson layered hybrid perovskites with aromatic organic spacers

Michael Graetzel, Jovana Milic, Algirdas Ducinskas, Joachim Maier, Davide Moia, Mina Jung

Royal Society of Chemistry2024

Phase diagram of the J-Jd Heisenberg model on the maple leaf lattice: Neural networks and density matrix renormalization group

Pratyay Ghosh, Ronny Thomale

Amer Physical Soc2024