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High throughput inverse design and Bayesian optimization of functionalities: ...
The development of spintronic devices demands the existence of materials with some kind of spin splitting (SS). In this work, we have built a database of ab initio calculated SS... -
Motif based high-throughput structure prediction of superconducting monolayer...
Two-dimensional boron structures, due to the diversity of properties, attract great attention because of their potential applications in nanoelectronic devices. A series of... -
High-throughput computation of Raman spectra from first principles
Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
Finding new crystalline compounds using chemical similarity
We proposed an efficient high-throughput scheme for the discovery of new stable crystalline phases. Our approach was based on the transmutation of known compounds, through the... -
Crystal-graph attention networks for the prediction of stable materials
Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions... -
High-throughput computational screening of nanoporous adsorbents for CO 2 cap...
With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
Benchmarking the GW100 dataset with the Yambo code by means of G₀W₀ approxima...
In this work we provide the results for IP and EA of all the 100 molecules of the set as computed within the Yambo code. In this way, we enlarge the GW100 benchmark considering... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
Stability and magnetic behavior of exfoliable nanowire 1D materials
Low-dimensional materials can display enhanced electronic, magnetic, and quantum properties. However, 1D exfoliable nanowires have not been explored as much as their 2D and 0D... -
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage...
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate... -
A Standard Solid State Pseudopotentials (SSSP) library optimized for precisio...
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here,... -
Large-scale machine-learning-assisted exploration of the whole materials space
Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal... -
Crystal-graph attention networks for the prediction of stable materials
Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions... -
A new dataset of 175k stable and metastable materials calculated with the PBE...
In the past decade we have witnessed the appearance of large databases of calculated material properties. These are most often obtained with the Perdew-Burke-Ernzerhof (PBE)... -
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage...
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate... -
The Materials Cloud 2D database (MC2D)
Two-dimensional (2D) materials are among the most promising candidates for beyond silicon electronic and optoelectronic applications. Recently, their recognized importance,...