Search Results for author: Shijing Sun

Found 8 papers, 6 papers with code

Introducing flexible perovskites to the IoT world using photovoltaic-powered wireless tags

no code implementations1 Jul 2022 Sai Nithin Reddy Kantareddy, Rahul Bhattacharya, Sanjay E. Sarma, Ian Mathews, Janak Thapa, Liu Zhe, Shijing Sun, Ian Marius Peters, Tonio Buonassisi

Our evaluation of the prototypes suggests that: i) flexible PV cells are durable up to a bending radius of 5 mm with only a 20 % drop in relative efficiency; ii) RFID communication range increased by 5x, and meets the energy needs (10-350 microwatt) to enable self-powered wireless sensors; iii) perovskite powered wireless sensors enable many battery-less sensing applications (e. g., perishable good monitoring, warehouse automation)

Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains

1 code implementation23 May 2021 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

In the field of machine learning (ML) for materials optimization, active learning algorithms, such as Bayesian Optimization (BO), have been leveraged for guiding autonomous and high-throughput experimentation systems.

Active Learning Bayesian Optimisation +2

Bridging the gap between photovoltaics R&D and manufacturing with data-driven optimization

1 code implementation28 Apr 2020 Felipe Oviedo, Zekun Ren, Xue Hansong, Siyu Isaac Parker Tian, Kaicheng Zhang, Mariya Layurova, Thomas Heumueller, Ning li, Erik Birgersson, Shijing Sun, Benji Mayurama, Ian Marius Peters, Christoph J. Brabec, John Fisher III, Tonio Buonassisi

Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost.

Applied Physics

Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks

2 code implementations npj Computational Materials 2019 Felipe Oviedo, Zekun Ren, Shijing Sun, Charles Settens, Zhe Liu, Noor Titan Putri Hartono, Savitha Ramasamy, Brian L. DeCost, Siyu I. P. Tian, Giuseppe Romano, Aaron Gilad Kusne, Tonio Buonassisi

We overcome the scarce data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data.

BIG-bench Machine Learning Data Augmentation +6

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