Literature DB >> 30939240

Early Years of High-Throughput Experimentation and Combinatorial Approaches in Catalysis and Materials Science.

Wilhelm F Maier1.   

Abstract

This is a report on the early years of combinatorial materials science and technology. High-throughput technologies (HTTs) are found in life- and materials-science laboratories. Although HTTs have long been the standard in life sciences in academia as well as in industry, HTTs in materials science have become the standard in industry but not in academia. In life science, successful drugs developed with HTTs have been reported, but there is no information on successful materials developed with HTTs that have made it to the market. Some initial development of HTTs in materials science is summarized, especially early applications of artificial intelligence. This outlook attempts to summarize the development of combinatorial materials sciences from the early years to today.

Keywords:  combinatorial catalysis research; combinatorial chemistry; combinatorial materials science; high-throughput technologies; history

Year:  2019        PMID: 30939240     DOI: 10.1021/acscombsci.8b00189

Source DB:  PubMed          Journal:  ACS Comb Sci        ISSN: 2156-8944            Impact factor:   3.784


  6 in total

1.  Ultra-High-Throughput Acoustic Droplet Ejection-Open Port Interface-Mass Spectrometry for Parallel Medicinal Chemistry.

Authors:  Kenneth J DiRico; Wenyi Hua; Chang Liu; Joseph W Tucker; Anokha S Ratnayake; Mark E Flanagan; Matthew D Troutman; Mark C Noe; Hui Zhang
Journal:  ACS Med Chem Lett       Date:  2020-05-01       Impact factor: 4.345

Review 2.  Technological Innovations in Photochemistry for Organic Synthesis: Flow Chemistry, High-Throughput Experimentation, Scale-up, and Photoelectrochemistry.

Authors:  Laura Buglioni; Fabian Raymenants; Aidan Slattery; Stefan D A Zondag; Timothy Noël
Journal:  Chem Rev       Date:  2021-08-10       Impact factor: 60.622

3.  High-Throughput Evaluation of Emission and Structure in Reduced-Dimensional Perovskites.

Authors:  Husna Anwar; Andrew Johnston; Suhas Mahesh; Kamalpreet Singh; Zhibo Wang; Douglas A Kuntz; Isaac Tamblyn; Oleksandr Voznyy; Gilbert G Privé; Edward H Sargent
Journal:  ACS Cent Sci       Date:  2022-05-06       Impact factor: 18.728

4.  Defining inkjet printing conditions of superconducting cuprate films through machine learning.

Authors:  Albert Queraltó; Adrià Pacheco; Nerea Jiménez; Susagna Ricart; Xavier Obradors; Teresa Puig
Journal:  J Mater Chem C Mater       Date:  2022-04-07       Impact factor: 8.067

Review 5.  Automation and data-driven design of polymer therapeutics.

Authors:  Rahul Upadhya; Shashank Kosuri; Matthew Tamasi; Travis A Meyer; Supriya Atta; Michael A Webb; Adam J Gormley
Journal:  Adv Drug Deliv Rev       Date:  2020-11-24       Impact factor: 15.470

Review 6.  Progress and prospects for accelerating materials science with automated and autonomous workflows.

Authors:  Helge S Stein; John M Gregoire
Journal:  Chem Sci       Date:  2019-09-20       Impact factor: 9.825

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.