Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

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Related publications (32)

Thermoelectric power of overdoped Tl2201 crystals: charge density waves and T1 and T2 resistivities

Matthias Carsten Putzke

We report measurements of the in-plane thermoelectric power (TEP) for an overdoped (OD) crystal of the single layer cuprate superconductor Tl2Ba2CuO6+x (Tl2201) at several hole concentrations (p), from 300 or 400 K to below the superconducting transition t ...

Iop Publishing Ltd2024

Type-I antiferromagnetic Weyl semimetal InMnTi2

Nicola Marzari, Luca Binci, Davide Grassano

Topological materials have been a main focus of studies in the past decade due to their protected properties that can be exploited for the fabrication of new devices. Among them, Weyl semimetals are a class of topological semimetals with nontrivial linear ...

Amer Physical Soc2024

High-Quality Data Enabling Universality of Band Gap Descriptor and Discovery of Photovoltaic Perovskites

Alfredo Pasquarello, Haiyuan Wang, Wei Chen

Extensive machine-learning-assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band gap data sets, particular ...

Amer Chemical Soc2024

Shortwave Infrared-Sensitive, Narrowband Organic Upconversion Devices with a Gain

Wei-Hsu Hu

Sensing and imaging of light in the shortwave infrared (SWIR) range is increasingly used in various fields, including bio-imaging, remote sensing, and semiconductor process control. SWIR-sensitive organic photodetectors (OPDs) are promising because organic ...

EPFL2024

Weyl metallic state induced by helical magnetic order

Henrik Moodysson Rønnow, Ivica Zivkovic, Jan Hugo Dil, Jian Rui Soh, Xupeng Yang

In the rapidly expanding field of topological materials there is growing interest in systems whose topological electronic band features can be induced or controlled by magnetism. Magnetic Weyl semimetals, which contain linear band crossings near the Fermi ...

Nature Portfolio2024

Interfacial engineering through lead binding using crown ethers in perovskite solar cells

Kevin Sivula, Jun Ho Yum, Jovana Milic, Yeonju Kim, Jiyoun Seo

In the domain of perovskite solar cells (PSCs), the imperative to reconcile impressive photovoltaic performance with lead-related issue and environmental stability has driven innovative solutions. This study pioneers an approach that not only rectifies lea ...

Elsevier2024

Absolute energy levels of liquid water from many-body perturbation theory with effective vertex corrections

Alfredo Pasquarello, Thomas Bischoff, Aleksei Tal

We demonstrate the importance of addressing the F vertex and thus going beyond the GW approximation for achieving the energy levels of liquid water in manybody perturbation theory. In particular, we consider an effective vertex function in both the polariz ...

National Academy of Sciences2024

High-throughput screening of Weyl semimetals

Nicola Marzari, Davide Grassano, Davide Campi

Topological Weyl semimetals represent a novel class of nontrivial materials, where band crossings with linear dispersions take place at generic momenta across reciprocal space. These crossings give rise to low -energy properties akin to those of Weyl fermi ...

Amer Physical Soc2024

Plasmonic Nanostructures for Photocatalysis: Material, Photonic and Electronic Effects

Fateme Kiani Shahvandi

Plasmonic photochemistry has a large potential to replace energy-intensive chemical processes with low-temperature, low-pressure light-driven chemical reactions. Plasmonic nanostructures have emerged as promising photocatalysts with exceptional and tunable ...

EPFL2024

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

Ksenia Briling

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 ...

EPFL2024

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