works on

From the 1 of 4.4k papers with an AI index.

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20022025
most citedQuantum ESPRESSO: a modular and open-source software project for quantum simulations of materials

29.3k citations

Showing 2023Show all

149 papers · 1 filter

cond-mat.mtrl-sci20236 cited

Spin-orbit torques and magnetization switching in Gd/Fe multilayers generated by current injection in NiCu alloys

Federica Nasr, Federico Binda, Charles-Henri Lambert +3

Light transition metals have recently emerged as a sustainable material class for efficient spin-charge interconversion. We report measurements of current-induced spin-orbit torque…

eess.SY202368 cited

Actors in Multi-Sector Transitions -- Discourse Analysis on Hydrogen in Germany

Nils Ohlendorf, Meike Löhr, Jochen Markard

With net-zero emission goals, low-carbon transitions enter a new phase of development, leading to new challenges for policymaking and research. Multiple transitions unfold in paral…

cs.GR202330 cited

GroomGen: A High-Quality Generative Hair Model Using Hierarchical Latent Representations

Yuxiao Zhou, Menglei Chai, Alessandro Pepe +2

Despite recent successes in hair acquisition that fits a high-dimensional hair model to a specific input subject, generative hair models, which establish general embedding spaces f…

astro-ph.EP202343 cited

15NH3 in the atmosphere of a cool brown dwarf

David Barrado, Paul Mollière, Polychronis Patapis +40

Brown dwarfs serve as ideal laboratories for studying the atmospheres of giant exoplanets on wide orbits as the governing physical and chemical processes in them are nearly identic…

q-bio.QM20238 cited

Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry

Yuming Jiang, Devasahayam Arokia Balaya Rex, Dina Schuster +16

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up…

stat.ML20231 cited

Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds

Paul Rosa, Viacheslav Borovitskiy, Alexander Terenin +1

Gaussian processes are used in many machine learning applications that rely on uncertainty quantification. Recently, computational tools for working with these models in geometric…