Here we present the Mendeleev-Meyer Force Project which aims at tabulating all materials and substances in a fashion similar to the periodic table. The goal is to group and tabulate substances using nanoscale force footprints rather than atomic number or electronic configuration as in the periodic table. The process is divided into: (1) acquiring nanoscale force data from materials, (2) parameterizing the raw data into standardized input features to generate a library, (3) feeding the standardized library into an algorithm to generate, enhance or exploit a model to identify a material or property. We propose producing databases mimicking the Materials Genome Initiative, the Medical Literature Analysis and Retrieval System Online (MEDLARS) o...
Computational tools have been widely used for predicting material properties in the past. Nowadays, ...
Thesis (Ph.D.)--University of Washington, 2022Machine learning and natural language processing techn...
Interatomic potential (i.e. force-field) plays a vital role in atomistic simulation of materials. Em...
Here we present the Mendeleev-Meyer Force Project which aims at tabulating all materials and substan...
Classical force fields (FFs) based on machine learning (ML) methods show great potential for large s...
Classical force fields (FF) based on machine learning (ML) methods show great potential for large sc...
Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departament...
Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and app...
Atomic-scale modeling and understanding of materials have made remarkable progress, but they are sti...
Defence is held on 12.1.2022 15:00 – 19:00 (Zoom), https://aalto.zoom.us/j/61312770423Atomic forc...
Machine learning techniques using artificial neural networks (ANNs) have proven to be effective tool...
The application of materials informatics for the rational design of materials has been inspired by t...
Accurate modelling of chemical and physical interactions is crucial for obtaining thermodynamic and ...
Cataloged from PDF version of article.We demonstrate high speed force–distance mapping using a doubl...
In materials science, the first principles modeling, especially density functional theory (DFT), ser...
Computational tools have been widely used for predicting material properties in the past. Nowadays, ...
Thesis (Ph.D.)--University of Washington, 2022Machine learning and natural language processing techn...
Interatomic potential (i.e. force-field) plays a vital role in atomistic simulation of materials. Em...
Here we present the Mendeleev-Meyer Force Project which aims at tabulating all materials and substan...
Classical force fields (FFs) based on machine learning (ML) methods show great potential for large s...
Classical force fields (FF) based on machine learning (ML) methods show great potential for large sc...
Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departament...
Machine-learning force fields (MLFF) should be accurate, computationally and data efficient, and app...
Atomic-scale modeling and understanding of materials have made remarkable progress, but they are sti...
Defence is held on 12.1.2022 15:00 – 19:00 (Zoom), https://aalto.zoom.us/j/61312770423Atomic forc...
Machine learning techniques using artificial neural networks (ANNs) have proven to be effective tool...
The application of materials informatics for the rational design of materials has been inspired by t...
Accurate modelling of chemical and physical interactions is crucial for obtaining thermodynamic and ...
Cataloged from PDF version of article.We demonstrate high speed force–distance mapping using a doubl...
In materials science, the first principles modeling, especially density functional theory (DFT), ser...
Computational tools have been widely used for predicting material properties in the past. Nowadays, ...
Thesis (Ph.D.)--University of Washington, 2022Machine learning and natural language processing techn...
Interatomic potential (i.e. force-field) plays a vital role in atomistic simulation of materials. Em...