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pro vyhledávání: '"Jake Graser"'
Advancements in materials discovery tend to rely disproportionately on happenstance and luck rather than employing a systematic approach. Recently, advances in computational power have allowed researchers to build computer models to predict the mater
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0deca804a0bb48a4035d605cf4511651
https://doi.org/10.26434/chemrxiv-2023-444s3
https://doi.org/10.26434/chemrxiv-2023-444s3
Autor:
Kyu Bum Han, Laercio Martins de Mendonca Filho, John McLennan, Christian J. Robert, Taylor D. Sparks, Jake Graser
Publikováno v:
Ceramics International. 44:9976-9983
An ideal proppant for hydraulic fracturing should be neutrally buoyant, implying a very low bulk specific gravity, while maintaining crush resistance and low acid solubility. To this end, an iron oxide and kaolinite based proppant has been developed.
Publikováno v:
Integrating Materials and Manufacturing Innovation. 7:43-51
Many thermodynamic calculations and engineering applications require the temperature-dependent heat capacity (Cp) of a material to be known a priori. First-principle calculations of heat capacities can stand in place of experimental information, but
Publikováno v:
Chemistry of Materials. 30:3601-3612
Predicting crystal structure has always been a challenging problem for physical sciences. Recently, computational methods have been built to predict crystal structure with success but have been limited in scope and computational time. In this paper,
Autor:
Nicholas O’Dea, Steven P. DenBaars, Jake Graser, Ram Seshadri, Taylor D. Sparks, Shuji Nakamura, Clayton Cozzan, Emily E. Levin, Claude Weisbuch, Guillaume Lheureux
Publikováno v:
ACS Applied Materials & Interfaces. 10:5673-5681
Solid-state lighting using laser diodes is an exciting new development that requires new phosphor geometries to handle the greater light fluxes involved. The greater flux from the source results in more conversion and therefore more conversion loss i
One of the most common criticisms of machine learning is an assumed inability for models to extrapolate, i.e. to identify extraordinary materials with properties beyond those present in the training data set. To investigate whether this is indeed the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49044bc8811358c6e48e02f6b424f982
https://doi.org/10.26434/chemrxiv.9396623
https://doi.org/10.26434/chemrxiv.9396623
Autor:
Isaac Nelson, Steven E. Naleway, Jake Graser, Taylor D. Sparks, Shadi Al Khateeb, Jake J. Abbott, Taylor A. Ogden
Publikováno v:
Advanced Engineering Materials. 21:1801092
Publikováno v:
ACS nano. 7(12)
A facile and scalable solution-based, spray pyrolysis synthesis technique was used to synthesize individual carbon nanospheres with specific surface area (SSA) up to 1106 m(2)/g using a novel metal-salt catalyzed reaction. The carbon nanosphere diame