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Physical Chemistry Chemical Physics : PCCP
|
June 3, 2021
Determining usefulness of machine learning in materials discovery using simulated research landscapes
Marcos Del Cueto, Alessandro Troisi
Digital Discovery
|
June 30, 2022
Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors
Zhi-Wen Zhao, Marcos Del Cueto, Alessandro Troisi
Journal of Materials Chemistry. C
|
November 8, 2021
High-throughput virtual screening for organic electronics: a comparative study of alternative strategies
Ömer H Omar, Marcos Del Cueto, Tahereh Nematiaram, et al.
Journal of Chemical Theory and Computation
|
January 22, 2026
Predicting S<sub>1</sub> TDDFT Energies from ZINDO Calculations Using Message-Passing ΔML with Electronically Informed Descriptors
Adam Coxson, Ömer H Omar, Marcos Del Cueto, et al.
The Journal of Physical Chemistry. C, Nanomaterials and Interfaces
|
August 19, 2022
Data-Driven Analysis of Hole-Transporting Materials for Perovskite Solar Cells Performance
Marcos Del Cueto, Charles Rawski-Furman, Juan Aragó, et al.
Physical Chemistry Chemical Physics : PCCP
|
July 10, 2019
Prominent out-of-plane diffraction in helium scattering from a methyl-terminated Si(111) surface
Marcos Del Cueto, Alberto S Muzas, Terry J Frankcombe, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal
|
January 10, 2019
Performance of van der Waals DFT approaches for helium diffraction on metal surfaces
Marcos Del Cueto, Reinhard J Maurer, Amjad Al Taleb, et al.
The Journal of Chemical Physics
|
September 3, 2016
Experimental and theoretical study of rotationally inelastic diffraction of H2(D2) from methyl-terminated Si(111)
Kevin J Nihill, Zachary M Hund, Alberto Muzas, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 8) with videos related to
Sort By:
Page
of 1
Physical Chemistry Chemical Physics : PCCP
|
June 3, 2021
Determining usefulness of machine learning in materials discovery using simulated research landscapes
Marcos Del Cueto, Alessandro Troisi
Digital Discovery
|
June 30, 2022
Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors
Zhi-Wen Zhao, Marcos Del Cueto, Alessandro Troisi
Journal of Materials Chemistry. C
|
November 8, 2021
High-throughput virtual screening for organic electronics: a comparative study of alternative strategies
Ömer H Omar, Marcos Del Cueto, Tahereh Nematiaram, et al.
Journal of Chemical Theory and Computation
|
January 22, 2026
Predicting S<sub>1</sub> TDDFT Energies from ZINDO Calculations Using Message-Passing ΔML with Electronically Informed Descriptors
Adam Coxson, Ömer H Omar, Marcos Del Cueto, et al.
The Journal of Physical Chemistry. C, Nanomaterials and Interfaces
|
August 19, 2022
Data-Driven Analysis of Hole-Transporting Materials for Perovskite Solar Cells Performance
Marcos Del Cueto, Charles Rawski-Furman, Juan Aragó, et al.
Physical Chemistry Chemical Physics : PCCP
|
July 10, 2019
Prominent out-of-plane diffraction in helium scattering from a methyl-terminated Si(111) surface
Marcos Del Cueto, Alberto S Muzas, Terry J Frankcombe, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal
|
January 10, 2019
Performance of van der Waals DFT approaches for helium diffraction on metal surfaces
Marcos Del Cueto, Reinhard J Maurer, Amjad Al Taleb, et al.
The Journal of Chemical Physics
|
September 3, 2016
Experimental and theoretical study of rotationally inelastic diffraction of H2(D2) from methyl-terminated Si(111)
Kevin J Nihill, Zachary M Hund, Alberto Muzas, et al.
Page
of 1