Comprehensive review on the application of inorganic and organic photovoltaics as greenhouse shading materials
Agrivoltaic greenhouse is a win–win concept which is a creative integration between
agriculture and Photovoltaic infrastructures to address the land use competition between …
agriculture and Photovoltaic infrastructures to address the land use competition between …
ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data
M Haghighatlari, G Vishwakarma… - Wiley …, 2020 - Wiley Online Library
ChemML is an open machine learning (ML) and informatics program suite that is designed
to support and advance the data‐driven research paradigm that is currently emerging in the …
to support and advance the data‐driven research paradigm that is currently emerging in the …
Firefly Monte Carlo: Exact MCMC with subsets of data
D Maclaurin, RP Adams - arXiv preprint arXiv:1403.5693, 2014 - arxiv.org
Markov chain Monte Carlo (MCMC) is a popular and successful general-purpose tool for
Bayesian inference. However, MCMC cannot be practically applied to large data sets …
Bayesian inference. However, MCMC cannot be practically applied to large data sets …
The solution is the solution: data-driven elucidation of solution-to-device feature transfer for π-conjugated polymer semiconductors
The advent of data analytics techniques and materials informatics provides opportunities to
accelerate the discovery and development of organic semiconductors for electronic devices …
accelerate the discovery and development of organic semiconductors for electronic devices …
Combining first-principles and data modeling for the accurate prediction of the refractive index of organic polymers
Organic materials with a high index of refraction (RI) are attracting considerable interest due
to their potential application in optic and optoelectronic devices. However, most of these …
to their potential application in optic and optoelectronic devices. However, most of these …
[HTML][HTML] A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules
The process of developing new compounds and materials is increasingly driven by
computational modeling and simulation, which allow us to characterize candidates before …
computational modeling and simulation, which allow us to characterize candidates before …
Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space
The use of modern data science has recently emerged as a promising new path to tackling
the complex challenges involved in the creation of next-generation chemistry and materials …
the complex challenges involved in the creation of next-generation chemistry and materials …
Benchmarking DFT approaches for the calculation of polarizability inputs for refractive index predictions in organic polymers
MAF Afzal, J Hachmann - Physical Chemistry Chemical Physics, 2019 - pubs.rsc.org
In a previous study, we introduced a new computational protocol to accurately predict the
index of refraction (RI) of organic polymers using a combination of first-principles and data …
index of refraction (RI) of organic polymers using a combination of first-principles and data …
Accelerating MCMC via parallel predictive prefetching
We present a general framework for accelerating a large class of widely used Markov chain
Monte Carlo (MCMC) algorithms. Our approach exploits fast, iterative approximations to the …
Monte Carlo (MCMC) algorithms. Our approach exploits fast, iterative approximations to the …
From virtual high-throughput screening and machine learning to the discovery and rational design of polymers for optical applications
MAF Afzal - 2018 - search.proquest.com
FROM VIRTUAL HIGH-THROUGHPUT SCREENING AND MACHINE LEARNING TO THE
DISCOVERY AND RATIONAL DESIGN OF POLYMERS FOR OPTICAL APPLICA Page 1 FROM …
DISCOVERY AND RATIONAL DESIGN OF POLYMERS FOR OPTICAL APPLICA Page 1 FROM …