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20042022
most citedDScribe: Library of Descriptors for Machine Learning in Materials Science

857 citations · 2.8k across the 19 of their papers we have counts for

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Showing cond-mat.mtrl-sciShow all

11 papers · 1 filter

cond-mat.mtrl-sci2022★ 11 cited

Control of molecular orbital ordering using a van der Waals monolayer ferroelectric

Mohammad Amini, Orlando J. Silveira, Viliam Vaňo +4

Two-dimensional (2D) ferroelectric materials provide a promising platform for the electrical control of quantum states. In particular, due to their 2D nature, they are suitable for…

cond-mat.mtrl-sci2021★ 68 cited

Silabenzene Incorporated Covalent Organic Frameworks

Kewei Sun, Orlando J. Silveira, Yujing Ma +6

Covalent organic frameworks (COFs) are a promising material for various applications such as gas storage/separation, catalysis, and energy storage, besides offering a confined spac…

cond-mat.mtrl-sci2021★ 42 cited

A Two-Dimensional Metal-Organic Framework on Superconducting NbSe

Linghao Yan, Orlando J. Silveira, Benjamin Alldritt +3

The combination of two-dimensional (2D) materials into vertical heterostructures has emerged as a promising path to designer quantum materials with exotic properties. Here, we exte…

cond-mat.mtrl-sci2020★ 60 cited

Electronic and magnetic characterization of epitaxial CrBr monolayers

Shawulienu Kezilebieke, Orlando J. Silveira, Md N. Huda +8

The ability to imprint a given material property to another through proximity effect in layered two-dimensional materials has opened the way to the creation of designer materials.…

cond-mat.mtrl-sci2020★ 40 cited

Synthesis and Local Probe Gating of a Monolayer Metal-Organic Framework

Linghao Yan, Orlando J. Silveira, Benjamin Alldritt +3

Achieving large-area uniform two-dimensional (2D) metal-organic frameworks (MOFs) and controlling their electronic properties on inert surfaces is a big step towards future applica…

cond-mat.mtrl-sci2019★ 857 cited

DScribe: Library of Descriptors for Machine Learning in Materials Science

Lauri Himanen, Marc O. J. Jäger, Eiaki V. Morooka +5

DScribe is a software package for machine learning that provides popular feature transformations ("descriptors") for atomistic materials simulations. DScribe accelerates the applic…