Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Wai Kuan Wong"'
Autor:
Flore Mekki-Berrada, Zekun Ren, Tan Huang, Wai Kuan Wong, Fang Zheng, Jiaxun Xie, Isaac Parker Siyu Tian, Senthilnath Jayavelu, Zackaria Mahfoud, Daniil Bash, Kedar Hippalgaonkar, Saif Khan, Tonio Buonassisi, Qianxiao Li, Xiaonan Wang
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
Abstract In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming. In this study, we present a two-step framework for a machine learning-driven high-throughput microfluidic p
Externí odkaz:
https://doaj.org/article/0ac9eaf9fc9e46a2ad63c0e8d956006b
Publikováno v:
Reaction Chemistry & Engineering. 5:1058-1063
The development of light-promoted organic synthesis has gained great momentum in recent years. However, the rates of photochemical reactions are dependent on the photon flux, which is typically limited by Beer–Lambert attenuation, and hampers their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9219ac780e5a0e2385acc2ce9269cfc0
https://doi.org/10.1039/d0re00080a
https://doi.org/10.1039/d0re00080a
Autor:
Mazie Tsang, Kara E. Bischoff, Kelly L. Schoenbeck, Kim Berry, David O'Riordan, Bita Fakhri, Sandy Wai Kuan Wong, Nina Shah, Eve Cohen, Nancy Shepard Lopez, Gabriel N. Mannis, Michael W. Rabow
Publikováno v:
Journal of Clinical Oncology. 40:12117-12117
12117 Background: Patients with hematologic malignancies are less likely to receive outpatient palliative care (OPC) compared to patients with other cancer types. Little is known about the characteristics or health care utilization of patients with h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0c77af0ba8cbc181f59e93c47ec67e0
https://doi.org/10.1200/jco.2022.40.16_suppl.12117
https://doi.org/10.1200/jco.2022.40.16_suppl.12117
Autor:
Kedar Hippalgaonkar, Saif A. Khan, Xiaonan Wang, Senthilnath Jayavelu, Qianxiao Li, Daniil Bash, Zackaria Mahfoud, Flore Mekki-Berrada, Tonio Buonassisi, Tan Huang, Isaac Parker Siyu Tian, Fang Zheng, Wai Kuan Wong, Zekun Ren, Jiaxun Xie
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming. In this study, we present a two-step framework for a machine learning-driven high-throughput microfluidic platform t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5157e15b5c3a97c296cd2bef74c82092
https://doi.org/10.1038/s41524-021-00520-w
https://doi.org/10.1038/s41524-021-00520-w
Autor:
Tonio Buonassisi, Kedar Hippalgaonkar, Saif A. Khan, Jayce Jian Wei Cheng, Qianxiao Li, Flore Mekki-Berrada, Wai Kuan Wong, Chellappan Vijila, Pawan Kumar, Yongqiang Cai, Yang Xu, Jatin N. Kumar, Isaac Parker Siyu Tian, Jin Da Tan, Swee Liang Wong, Yee-Fun Lim, Daniil Bash, Anas Abutaha, Zekun Ren
Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that machine learning, combined with multi-labeled datasets, can additionally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d8842894a190b456584155c630b06c1
Publikováno v:
Chemical Engineering Journal. 430:132778
Ultra-small noble metal nanoparticles, such as palladium, platinum and rhodium, are invaluable catalysts for the synthesis of a plethora of materials, ranging from pharmaceutical drugs to polymers and fertilizers due to their high catalytic activitie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b3f2677be88cf088903bdc7765c128f
https://doi.org/10.1016/j.cej.2021.132778
https://doi.org/10.1016/j.cej.2021.132778
Autor:
Saif A. Khan, Wai Kuan Wong, Qianxiao Li, Pawan Kumar, Yee-Fun Lim, Xu Yang, Jayce J. Cheng, Jatin N. Kumar, Jiaxun Xie, Swee Liang Wong, Zekun Ren, Siyu Isaac Parker Tian, Flore Mekki-Berrada, Daniil Bash, Anas Abutaha, Jin Da Tan, Kedar Hippalgaonkar, Tonio Buonassisi, Yongqiang Cai, Vijila Chellappan
Publikováno v:
Advanced Functional Materials. 31:2102606
Combining high-throughput experiments with machine learning accelerates materials and process optimization toward user-specified target properties. In this study, a rapid machine learning-driven automated flow mixing setup with a high-throughput drop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19c0311e1eabec70f564988980f61a7e
https://doi.org/10.1002/adfm.202102606
https://doi.org/10.1002/adfm.202102606
Publikováno v:
Chemical Engineering Science. 169:117-127
We present a design framework for the robust, self-regulating long-term operation of parallelized multiphase microfluidic reactor networks without the use of any active flow control elements. A fluidic circuit-based design scheme is developed for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e388b45f61234d64e3d9e7299b88dd77
https://doi.org/10.1016/j.ces.2016.12.005
https://doi.org/10.1016/j.ces.2016.12.005
Publikováno v:
Chemistry of Materials. 28:5095-5101
Covalent organic frameworks (COFs) have recently emerged as a new class of crystalline porous materials with many potential applications. The development of facile and effective synthetic methods of COFs is highly desirable for their large-scale appl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c822765870be34893b6b41780d59f278
https://doi.org/10.1021/acs.chemmater.6b01954
https://doi.org/10.1021/acs.chemmater.6b01954
Publikováno v:
Reaction Chemistry & Engineering; Jun2020, Vol. 5 Issue 6, p1058-1063, 6p