TY - JOUR
T1 - Computational materials science
T2 - Discovering and accelerating future technologies
AU - Tahini, Hassan A.
AU - Tan, Xin
AU - Smith, Sean C.
N1 - Publisher Copyright:
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
PY - 2019
Y1 - 2019
N2 - Moving the boundaries of knowledge, scientific research and technologies forward through the field of computational materials science requires a combination of fundamental understanding of materials properties, an appreciation of the limitations with our current approaches, and the ability to embrace new and emergent technologies. This short Essay highlights the works of the authors in the special issue "Computational Materials Design" published in Advanced Theory and Simulations. It emphasises the role that computational materials design plays in rationalizing and guiding experimental efforts in in the fields of catalysis, semiconductors, hydrogels, and solid-state electrolytes. Increases in computational power together with accurate hybrid functionals within density functional theory are enabling more reliable and trustworthy descriptions of solids for various electronic and optoelectronic applications. Additionally, high-throughput screening and machine learning are rapidly becoming indispensable tools in computational materials science across diverse applications such as engineering and predicting new catalysts. Such advances are setting the pace for our discovery of new and novel materials of the future.
AB - Moving the boundaries of knowledge, scientific research and technologies forward through the field of computational materials science requires a combination of fundamental understanding of materials properties, an appreciation of the limitations with our current approaches, and the ability to embrace new and emergent technologies. This short Essay highlights the works of the authors in the special issue "Computational Materials Design" published in Advanced Theory and Simulations. It emphasises the role that computational materials design plays in rationalizing and guiding experimental efforts in in the fields of catalysis, semiconductors, hydrogels, and solid-state electrolytes. Increases in computational power together with accurate hybrid functionals within density functional theory are enabling more reliable and trustworthy descriptions of solids for various electronic and optoelectronic applications. Additionally, high-throughput screening and machine learning are rapidly becoming indispensable tools in computational materials science across diverse applications such as engineering and predicting new catalysts. Such advances are setting the pace for our discovery of new and novel materials of the future.
UR - http://www.scopus.com/inward/record.url?scp=85081138151&partnerID=8YFLogxK
U2 - 10.1002/ADTS.201900023
DO - 10.1002/ADTS.201900023
M3 - Review article
SN - 2513-0390
VL - 2
JO - Advanced Theory and Simulations
JF - Advanced Theory and Simulations
IS - 3
M1 - 1900023
ER -