63 citations · 352 across the 26 of their papers we have counts for
26 papers
Chip-Scale Aligned Chiral Carbon Nanotubes Exhibiting Giant Second Harmonic Generation
Rui Xu, Jacques Doumani, Viktor Labuntsov +16
Chiral carbon nanotubes (CNTs) are direct-gap semiconductors with optical properties governed by one-dimensional excitons with enormous oscillator strengths. Each species of chiral…
LightRidge: An End-to-end Agile Design Framework for Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Minhan Lou +3
To lower the barrier to diffractive optical neural networks (DONNs) design, exploration, and deployment, we propose LightRidge, the first end-to-end optical ML compilation framewor…
Rubik's Optical Neural Networks: Multi-task Learning with Physics-aware Rotation Architecture
Yingjie Li, Weilu Gao, Cunxi Yu
Recently, there are increasing efforts on advancing optical neural networks (ONNs), which bring significant advantages for machine learning (ML) in terms of power efficiency, paral…
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks
Shanglin Zhou, Yingjie Li, Minhan Lou +4
As a representative next-generation device/circuit technology beyond CMOS, diffractive optical neural networks (DONNs) have shown promising advantages over conventional deep neural…
Transition from Diffusive to Superdiffusive Transport in Carbon Nanotube Networks via Nematic Order Control
Michael Wais, Filchito Renee G. Bagsican, Natsumi Komatsu +8
The one-dimensional confinement of quasiparticles in individual carbon nanotubes (CNTs) leads to extremely anisotropic electronic and optical properties. In a macroscopic ensemble…
Scientific Computing with Diffractive Optical Neural Networks
Ruiyang Chen, Yingheng Tang, Jianzhu Ma +1
Diffractive optical neural networks (DONNs) have been emerging as a high-throughput and energy-efficient hardware platform to perform all-optical machine learning (ML) in machine v…
Controlled synthetic chirality in macroscopic assemblies of carbon nanotubes
Jacques Doumani, Minhan Lou, Oliver Dewey +9
There is an emerging recognition that successful utilization of chiral degrees of freedom can bring new scientific and technological opportunities to diverse research areas. Hence,…
Physics-aware Differentiable Discrete Codesign for Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Weilu Gao +1
Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring significant advantages in terms of power efficiency, parallelism, and computational speed…
Perfectly Perform Machine Learning Task with Imperfect Optical Hardware Accelerator
Jichao Fan, Yingheng Tang, Weilu Gao
Optical architectures have been emerging as an energy-efficient and high-throughput hardware platform to accelerate computationally intensive general matrix-matrix multiplications…
Device-system Co-design of Photonic Neuromorphic Processor using Reinforcement Learning
Yingheng Tang, Princess Tara Zamani, Ruiyang Chen +4
The incorporation of high-performance optoelectronic devices into photonic neuromorphic processors can substantially accelerate computationally intensive operations in machine lear…
Physics-aware Complex-valued Adversarial Machine Learning in Reconfigurable Diffractive All-optical Neural Network
Ruiyang Chen, Yingjie Li, Minhan Lou +5
Diffractive optical neural networks have shown promising advantages over electronic circuits for accelerating modern machine learning (ML) algorithms. However, it is challenging to…
Evidence for Phonon-Assisted Intertube Electronic Transport in an Armchair Carbon Nanotube Film
Davoud Adinehloo, Weilu Gao, Ali Mojibpour +2
The electrical conductivity of a macroscopic assembly of nanomaterials is determined through a complex interplay of electronic transport within and between constituent nano-objects…
Wafer-scale, full-coverage, acoustic self-limiting assembly of particles on flexible substrates
Liang Zhao, Bchara Sidnawi, Jichao Fan +6
Self-limiting assembly of particles represents the state-of-the-art controllability in nanomanufacturing processes where the assembly stops at a designated stage1,2, providing a de…
Physics-Guided and Physics-Explainable Recurrent Neural Network for Time Dynamics in Optical Resonances
Yingheng Tang, Jichao Fan, Xinwei Li +4
Understanding the time evolution of physical systems is crucial to revealing fundamental characteristics that are hidden in frequency domain. In optical science, high-quality reson…
Band Structure Dependent Electronic Localization in Macroscopic Films of Single-Chirality Single-Wall Carbon Nanotubes
Weilu Gao, Davoud Adinehloo, Ali Mojibpour +7
Significant understanding has been achieved over the last few decades regarding chirality-dependent properties of single-wall carbon nanotubes (SWCNTs), primarily through single-tu…
Real-time Multi-Task Diffractive Deep Neural Networks via Hardware-Software Co-design
Yingjie Li, Ruiyang Chen, Berardi Sensale Rodriguez +2
Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing…
Artificial Intelligence Accelerators based on Graphene Optoelectronic Devices
Weilu Gao, Cunxi Yu, Ruiyang Chen
Optical and optoelectronic approaches of performing matrix-vector multiplication (MVM) operations have shown the great promise of accelerating machine learning (ML) algorithms with…
Terahertz Excitonics in Carbon Nanotubes: Exciton Autoionization and Multiplication
Filchito Renee G. Bagsican, Michael Wais, Natsumi Komatsu +10
Excitons play major roles in optical processes in modern semiconductors, such as single-wall carbon nanotubes (SWCNTs), transition metal dichalcogenides, and 2D perovskite quantum…
Observation of Photoinduced Terahertz Gain in GaAs Quantum Wells: Evidence for Radiative Two-Exciton-to-Biexciton Scattering
X. Li, K. Yoshioka, Q. Zhang +9
We have observed photoinduced negative optical conductivity, or gain, in the terahertz frequency range in a GaAs multiple-quantum-well structure in a strong perpendicular magnetic…
Groove-Assisted Global Spontaneous Alignment of Carbon Nanotubes in Vacuum Filtration
Natsumi Komatsu, Motonori Nakamura, Saunab Ghosh +7
Ever since the discovery of carbon nanotubes (CNTs), it has long been a challenging goal to create macroscopically ordered assemblies, or crystals, of CNTs that preserve the one-di…
One-directional thermal transport in densely aligned single-wall carbon nanotube films
Shingi Yamaguchi, Issei Tsunekawa, Natsumi Komatsu +5
Individual carbon nanotubes (CNTs) possess extremely high thermal conductivities. However, the thermal conductivities and their anisotropy of macroscopic assemblies of CNTs have so…
Terahertz Faraday and Kerr rotation spectroscopy of BiSb films in high magnetic fields up to 30 Tesla
Xinwei Li, Katsumasa Yoshioka, Ming Xie +16
We report results of terahertz Faraday and Kerr rotation spectroscopy measurements on thin films of , an alloy system that exhibits a semimetal-to-top…
Macroscopically Aligned Carbon Nanotubes as a Refractory Platform for Hyperbolic Thermal Emitters
Weilu Gao, Chloe F. Doiron, Xinwei Li +2
Refractory nanophotonics, or nanophotonics at high temperatures, can revolutionize many applications, including data storage and waste heat recovery. In particular, nanophotonic de…
Science and applications of wafer-scale crystalline carbon nanotube films prepared through controlled vacuum filtration
Weilu Gao, Junichiro Kono
Carbon nanotubes (CNTs) make an ideal one-dimensional (1D) material platform for the exploration of exotic physical phenomena under extremely strong quantum confinement. The 1D cha…