activity
20182020
most citedAccelerating Photovoltaic Materials Development via High-Throughput Experiments and Machine-Learning-Assisted Diagnosis

340 citations · 561 across the 5 of their papers we have counts for

collaborators

5 papers

physics.app-ph2020★ 7 cited

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

Felipe Oviedo, Zekun Ren, Xue Hansong +12

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

eess.SP2019★ 76 cited

Perovskite PV-powered RFID: enabling low-cost self-powered IoT sensors

Sai Nithin R. Kantareddy, Ian Mathews, Shijing Sun +6

Photovoltaic (PV) cells have the potential to serve as on-board power sources for low-power IoT devices. Here, we explore the use of perovskite solar cells to power Radio Frequency…

physics.app-ph2019★ 134 cited

Self-powered sensors enabled by wide-bandgap perovskite indoor photovoltaic cells

Ian Mathews, Sai Nithin Reddy Kantareddy, Shijing Sun +7

We present a new approach to ubiquitous sensing for indoor applications, using high-efficiency and low-cost indoor perovksite photovoltaic cells as external power sources for backs…

physics.app-ph2019★ 4 cited

Embedding Physics Domain Knowledge into a Bayesian Network Enables Layer-by-Layer Process Innovation for Photovoltaics

Zekun Ren, Felipe Oviedo, Muang Thway +15

Process optimization of photovoltaic devices is a time-intensive, trial and error endeavor, without full transparency of the underlying physics, and with user-imposed constraints t…

physics.app-ph2018★ 340 cited

Accelerating Photovoltaic Materials Development via High-Throughput Experiments and Machine-Learning-Assisted Diagnosis

Shijing Sun, Noor T. P. Hartono, Zekun D. Ren +15

Accelerating the experimental cycle for new materials development is vital for addressing the grand energy challenges of the 21st century. We fabricate and characterize 75 unique h…