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Daniil Bash
Daniil Bash
Verified email at u.nus.edu
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Cited by
Year
Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains
Q Liang, AE Gongora, Z Ren, A Tiihonen, Z Liu, S Sun, JR Deneault, ...
npj Computational Materials 7 (1), 188, 2021
137*2021
Two-step machine learning enables optimized nanoparticle synthesis
F Mekki-Berrada, Z Ren, T Huang, WK Wong, F Zheng, J Xie, IPS Tian, ...
npj Computational Materials 7 (1), 55, 2021
1362021
Inertial effective mass as an effective descriptor for thermoelectrics via data-driven evaluation
A Suwardi, D Bash, HK Ng, JR Gomez, DVM Repaka, P Kumar, ...
Journal of Materials Chemistry A 7 (41), 23762-23769, 2019
632019
Multi‐Fidelity High‐Throughput Optimization of Electrical Conductivity in P3HT‐CNT Composites
D Bash, Y Cai, V Chellappan, SL Wong, X Yang, P Kumar, JD Tan, ...
Advanced Functional Materials 31 (36), 2102606, 2021
47*2021
Predicting thermoelectric properties from crystal graphs and material descriptors-first application for functional materials
L Laugier, D Bash, J Recatala, HK Ng, S Ramasamy, CS Foo, ...
arXiv preprint arXiv:1811.06219, 2018
182018
Accelerated automated screening of viscous graphene suspensions with various surfactants for optimal electrical conductivity
D Bash, FH Chenardy, Z Ren, JJW Cheng, T Buonassisi, R Oliveira, ...
Digital Discovery, 2022
152022
Synthesis of Bi‐and Polyfunctional Isoxazoles from Amino Acid Derived Halogenoximes and Active Methylene Nitriles
BA Chalyk, KV Hrebeniuk, KS Gavrilenko, OV Shablykin, OO Yanshyna, ...
European Journal of Organic Chemistry 2018 (22), 2753-2761, 2018
152018
Automated pipetting robot for proxy high-throughput viscometry of Newtonian fluids
BW Soh, A Chitre, WY Lee, D Bash, JN Kumar, K Hippalgaonkar
Digital Discovery 2 (2), 481-488, 2023
72023
Machine learning based feature engineering for thermoelectric materials by design
US Vaitesswar, D Bash, T Huang, J Recatala-Gomez, T Deng, SW Yang, ...
Digital Discovery 3 (1), 210-220, 2024
62024
Two-Step Machine Learning Enables Optimized Nanoparticle Synthesis. ChemRxiv
F Mekki-Berrada, Z Ren, T Huang, WK Wong, F Zheng, J Xie, IPS Tian, ...
Preprint, 2020
62020
Mass Balance Integration with the Opentrons OT-2 Robot
A Chitre, D Bash, J Cheng, AA Lapkin, K Hippalgaonkar
Opentrons App. Notes, 2023
22023
Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films
SIP Tian, Z Ren, S Venkataraj, Y Cheng, D Bash, F Oviedo, J Senthilnath, ...
Digital Discovery 2 (5), 1334-1346, 2023
22023
Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization
R Dutta, SIP Tian, Z Liu, M Lakshminarayanan, S Venkataraj, Y Cheng, ...
Plos one 17 (11), e0276555, 2022
22022
Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films.
S TIAN, Z Ren, S Venkataraj, Y Cheng, D Bash, F Oviedo, J Senthilnath, ...
ArXiv 2207, 02209, 2022
22022
Flow reactor system and flow reaction method
YF Lim, Y Xu, JWJ Cheng, SL Wong, V Chellappan, J Kumar, B Daniil, ...
US Patent App. 18/576,009, 2024
2024
Data collection apparatus and computer-implemented data collection method using same
JWJ Cheng, P Kumar, A Abutaha, B Daniil, T Buonassisi, ...
US Patent App. 18/569,997, 2024
2024
Correction: Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films
SIP Tian, Z Ren, S Venkataraj, Y Cheng, D Bash, F Oviedo, J Senthilnath, ...
Digital Discovery 3 (5), 1068-1068, 2024
2024
OPTIMIZATION OF COMPOSITION AND PROPERTIES OF HYBRID ELECTRONIC COMPOSITES USING MACHINE LEARNING-ASSISTED HIGH-THROUGHPUT EXPERIMENTS
D BASH
2022
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