1 citations · 4 across the 8 of their papers we have counts for
8 papers
Emerging Non-Volatile Opto-electronic Resistive Memories for Next-Generation Photonic Integrated Circuits
Santosh Kumar, Mukesh Kumar, Eunso Shin +2
Photonic integrated circuits have emerged as a powerful platform for high speed communication, sensing, and information processing due to their large bandwidth, low latency, and in…
Design, Locomotion, and Control of Amphibious Robots: Recent Advances
Yi Jin, Chang Liu, Roger D. Quinn +2
Amphibious robots, operating seamlessly across land and water, are advancing applications in conservation, disaster response, and defense. Their performance depends on locomotion m…
Ultra-sensitive graphene-based electro-optic sensors for optically-multiplexed neural recording
Zabir Ahmed, Xiang Li, Kanika Sarna +3
Large-scale neural recording with high spatio-temporal resolution is essential for understanding information processing in brain, yet current neural interfaces fall far short of co…
Visible Imaging of Incoherent 1200-nm Light via Triplet--Triplet Annihilation Upconversion
Pournima Narayanan, Rabeeya Hamid, Linda Pucurimay +13
Upconversion of low-energy photons to higher-energy photons provides an opportunity to surpass traditional limitations in fields such as 3D printing, photovoltaics, and photocataly…
Scalable Etch-Free Transfer of Low-Dimensional Materials from Metal Films to Diverse Substrates
Kentaro Yumigeta, Muhammed Yusufoglu, Mamun Sarker +12
Low-dimensional materials hold great promises for exploring emergent physical phenomena, nanoelectronics, and quantum technologies. Their synthesis often depends on catalytic metal…
Towards chemical accuracy for chemi- and physisorption with an efficient density functional
Manish Kothakonda, Ruiqi Zhang, Jinliang Ning +4
Understanding molecular adsorption on surfaces underpins many problems in chemistry and materials science. Accurately and efficiently describing the adsorption has been a challengi…
Reduced Order Modeling of Partial Differential Equations on Parameter-Dependent Domains Using Deep Neural Networks
Martina Bukač, Iva Manojlović, Boris Muha +1
Partial differential equations (PDEs) are widely used for modeling various physical phenomena. These equations often depend on certain parameters, necessitating either the identifi…
Virtual Node Graph Neural Network for Full Phonon Prediction
Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Artittaya Boonkird +10
The structure-property relationship plays a central role in materials science. Understanding the structure-property relationship in solid-state materials is crucial for structure d…