Výsledky vyhledávání - "Elsa A, Olivetti"

Akademický článek

Emission impacts of China’s solid waste import ban and COVID-19 in the copper supply chain

Autor: John Ryter, Xinkai Fu, Karan Bhuwalka, Richard Roth, Elsa A. Olivetti

Publikováno v: Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)

Advanced copper supply chain modeling shows China’s new waste trade policy may increase pollution, while limiting other low-value imports reverses this trend. Here the authors show that recycling is vulnerable to supply chain shocks, requiring inve

Externí odkaz: https://doaj.org/article/c0ab4e480f3d437c85d019bc165795e8

Zobrazit plný text záznamu

Akademický článek

Discovering Relationships between OSDAs and Zeolites through Data Mining and Generative Neural Networks

Autor: Zach Jensen, Soonhyoung Kwon, Daniel Schwalbe-Koda, Cecilia Paris, Rafael Gómez-Bombarelli, Yuriy Román-Leshkov, Avelino Corma, Manuel Moliner, Elsa A. Olivetti

Publikováno v: ACS Central Science, Vol 7, Iss 5, Pp 858-867 (2021)

Externí odkaz: https://doaj.org/article/747e577a23b8402896ea1fa2a918df49

Zobrazit plný text záznamu

Akademický článek

Data-Driven Prediction of Quartz Dissolution Rates at Near-Neutral and Alkaline Environments

Autor: Kai Gong, Tunahan Aytas, Shu Yang Zhang, Elsa A. Olivetti

Publikováno v: Frontiers in Materials, Vol 9 (2022)

Dissolution of silicate-based materials is important to many natural processes and engineering applications, including cement and concrete production. Here, we present a data-driven study to predict the dissolution rates of crystalline silica (i.e.,

Externí odkaz: https://doaj.org/article/1af60877b2834b2bbd0966ddf4753786

Zobrazit plný text záznamu

Akademický článek

Opportunities and challenges of text mining in materials research

Autor: Olga Kononova, Tanjin He, Haoyan Huo, Amalie Trewartha, Elsa A. Olivetti, Gerbrand Ceder

Publikováno v: iScience, Vol 24, Iss 3, Pp 102155- (2021)

Summary: Research publications are the major repository of scientific knowledge. However, their unstructured and highly heterogenous format creates a significant obstacle to large-scale analysis of the information contained within. Recent progress in

Externí odkaz: https://doaj.org/article/fb853d448a01416691beacc49ccf30d0

Zobrazit plný text záznamu

Akademický článek

Text mining for processing conditions of solid-state battery electrolyte

Autor: Rubayyat Mahbub, Kevin Huang, Zach Jensen, Zachary D. Hood, Jennifer L.M. Rupp, Elsa A. Olivetti

Publikováno v: Electrochemistry Communications, Vol 121, Iss , Pp 106860- (2020)

The search for safer next-generation lithium ion batteries has motivated development of solid-state electrolytes (SSEs), owing to their wide electrochemical potential window, high ionic conductivity (10−3 to 10−4 S cm−1) and good chemical stabi

Externí odkaz: https://doaj.org/article/a291871a80ee4f569cceea46ee3a7472

Zobrazit plný text záznamu

Akademický článek

Learning the crystal structure genome for property classification

Autor: Yiqun Wang, Xiao-Jie Zhang, Fei Xia, Elsa A. Olivetti, Stephen D. Wilson, Ram Seshadri, James M. Rondinelli

Publikováno v: Physical Review Research, Vol 4, Iss 2, p 023029 (2022)

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely on featuri

Externí odkaz: https://doaj.org/article/41b6ce69ef7a48c185937e6741b8033a

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání