Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Kedar Hippalgaonkar"'
Autor:
Aniket Chitre, Robert C. M. Querimit, Simon D. Rihm, Dogancan Karan, Benchuan Zhu, Ke Wang, Long Wang, Kedar Hippalgaonkar, Alexei A. Lapkin
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-10 (2024)
Abstract Liquid formulations are ubiquitous yet have lengthy product development cycles owing to the complex physical interactions between ingredients making it difficult to tune formulations to customer-defined property targets. Interpolative ML mod
Externí odkaz:
https://doaj.org/article/8fa8db7a70894f60b16d6db492fee624
Autor:
Andre K. Y. Low, Flore Mekki-Berrada, Abhishek Gupta, Aleksandr Ostudin, Jiaxun Xie, Eleonore Vissol-Gaudin, Yee-Fun Lim, Qianxiao Li, Yew Soon Ong, Saif A. Khan, Kedar Hippalgaonkar
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental
Externí odkaz:
https://doaj.org/article/0fb91db8811d4d46a6d55d2c7d7fdeed
Autor:
Syed Zulfiqar Hussain Shah, Zhenyu Ding, Zainul Aabdin, Weng Weei Tjiu, Jose Recatala‐Gomez, Haiwen Dai, Xiaoping Yang, Repaka Durga Venkata Maheswar, Gang Wu, Kedar Hippalgaonkar, Iris Nandhakumar, Pawan Kumar
Publikováno v:
Advanced Science, Vol 11, Iss 35, Pp n/a-n/a (2024)
Abstract Organic–inorganic hybrid thermoelectric (TE) materials have attracted tremendous interest for harvesting waste heat energy. Due to their mechanical flexibility, inorganic‐organic hybrid TE materials are considered to be promising candida
Externí odkaz:
https://doaj.org/article/7c69a30d368641bb80c3e7782b77eaec
Autor:
Shakti P. Padhy, Varun Chaudhary, Yee-Fun Lim, Ruiming Zhu, Muang Thway, Kedar Hippalgaonkar, Raju V. Ramanujan
Publikováno v:
iScience, Vol 27, Iss 5, Pp 109723- (2024)
Summary: This study presents a machine learning (ML) framework aimed at accelerating the discovery of multi-property optimized Fe-Ni-Co alloys, addressing the time-consuming, expensive, and inefficient nature of traditional methods of material discov
Externí odkaz:
https://doaj.org/article/f92cef09f5714bfe9b0d70727d955d3a
Autor:
Carina Yi Jing Lim, Meltem Yilmaz, Juan Manuel Arce-Ramos, Albertus D. Handoko, Wei Jie Teh, Yuangang Zheng, Zi Hui Jonathan Khoo, Ming Lin, Mark Isaacs, Teck Lip Dexter Tam, Yang Bai, Chee Koon Ng, Boon Siang Yeo, Gopinathan Sankar, Ivan P. Parkin, Kedar Hippalgaonkar, Michael B. Sullivan, Jia Zhang, Yee-Fun Lim
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract Intensive research in electrochemical CO2 reduction reaction has resulted in the discovery of numerous high-performance catalysts selective to multi-carbon products, with most of these catalysts still being purely transition metal based. Her
Externí odkaz:
https://doaj.org/article/2c718d61d24d45b8abee949e2f302094
Autor:
Madhavkrishnan Lakshminarayanan, Rajdeep Dutta, D. V. Maheswar Repaka, Senthilnath Jayavelu, Wei Lin Leong, Kedar Hippalgaonkar
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract The past few decades have seen an uptick in the scope and range of device applications of organic semiconductors, such as organic field-effect transistors, organic photovoltaics and light-emitting diodes. Several researchers have studied ele
Externí odkaz:
https://doaj.org/article/32bf8f41d2f44a38b5bbd820302cbc34
Autor:
Qiaohao Liang, Aldair E. Gongora, Zekun Ren, Armi Tiihonen, Zhe Liu, Shijing Sun, James R. Deneault, Daniil Bash, Flore Mekki-Berrada, Saif A. Khan, Kedar Hippalgaonkar, Benji Maruyama, Keith A. Brown, John Fisher III, Tonio Buonassisi
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
Abstract Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad range of experimental materials domains. In this work,
Externí odkaz:
https://doaj.org/article/bfc6d1e9f14b4b8bbc093f32c3360b8c
Autor:
Lei Hu, Yue-Wen Fang, Feiyu Qin, Xun Cao, Xiaoxu Zhao, Yubo Luo, Durga Venkata Maheswar Repaka, Wenbo Luo, Ady Suwardi, Thomas Soldi, Umut Aydemir, Yizhong Huang, Zheng Liu, Kedar Hippalgaonkar, G. Jeffrey Snyder, Jianwei Xu, Qingyu Yan
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Lillianite materials usually have low thermoelectric efficiency due to the inherently inferior electrical properties. Here, the authors evaluate thermoelectric performances in Pb7Bi4Se13 based lillianites enabled by convergence of nested conduction b
Externí odkaz:
https://doaj.org/article/ef0462e36b6f4c3aa55c21999851f87a
Autor:
Carina Yi Jing Lim, Meltem Yilmaz, Juan Manuel Arce-Ramos, Albertus D. Handoko, Wei Jie Teh, Yuangang Zheng, Zi Hui Jonathan Khoo, Ming Lin, Mark Isaacs, Teck Lip Dexter Tam, Yang Bai, Chee Koon Ng, Boon Siang Yeo, Gopinathan Sankar, Ivan P. Parkin, Kedar Hippalgaonkar, Michael B. Sullivan, Jia Zhang, Yee-Fun Lim
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/0dc2c85a2fcc49108c18f2dbb71c86b5
Autor:
Tao Liu, Du Xiang, Hong Kuan Ng, Zichao Han, Kedar Hippalgaonkar, Ady Suwardi, Jens Martin, Slaven Garaj, Jing Wu
Publikováno v:
Advanced Science, Vol 9, Iss 20, Pp n/a-n/a (2022)
Abstract Transition metal dichalcogenides (TMDs) possess intrinsic spin–orbit interaction (SOI) with high potential to be exploited for various quantum phenomena. SOI allows the manipulation of spin degree of freedom by controlling the carrier's or
Externí odkaz:
https://doaj.org/article/77de528133e84b8abe3e5ec37600faa0