Unveiling Efficient Acousto-Optic Modulation in Silicon Photonic Devices via Lithium Niobate Using Transfer Printing DOI
Siyu Xu, Weixin Liu, Xianhao Le

et al.

Nano Letters, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 20, 2024

Piezo-optomechanics presents a promising route to convert microwave signals the optical domain, implementing processing tasks that are challenging using conventional electronics. The surge of integrated photonics facilitates exploitation localized light-sound interactions toward new technological paradigms. However, efficient acousto-optic interaction has yet be fully exploited in silicon due absence piezoelectricity, despite its maturity photonic circuits. Here, we introduce distinctive scheme supplement devices through heterogeneous integration with lithium niobate (LN). Utilizing LN as an acoustic pump harness inherently exceptional photoelasticity silicon, demonstrate microwave-to-acoustic transduction, ultimately achieving modulation figure-of-merit

Language: Английский

Advances in MEMS, Optical MEMS, and Nanophotonics Technologies for Volatile Organic Compound Detection and Applications DOI Creative Commons

Dongxiao Li,

Hong Zhou, Zhihao Ren

et al.

Small Science, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Volatile organic compounds (VOCs) are a class of with high vapor pressure and low boiling points, widely present in both natural environments human activities. VOCs released from various sources not only contribute to environmental pollution but also pose threats ecosystems health. Moreover, some considered biomarkers exhaled breath can be utilized identify diseases. Therefore, monitoring controlling VOC emissions concentrations crucial for safeguarding the environment In recent years, significant advancements have been achieved micro‐electromechanical system (MEMS)‐based sensing optical technologies, offering new avenues detection. This article provides comprehensive overview research progress MEMS sensors, focusing on their mechanisms classifications. It then discusses role artificial intelligence enhancing identification quantification, as well trends toward sensor miniaturization intelligence. Furthermore, highlights diverse applications sensors medical diagnostics, agricultural food testing, Internet Things. Finally, it emphasizes opportunities challenges associated providing valuable insights practical applications.

Language: Английский

Citations

2
Advances in olfactory augmented virtual reality towards future metaverse applications DOI Creative Commons
Zixuan Zhang, Xinge Guo, Chengkuo Lee

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 31, 2024

Recent advances in virtual reality technologies accelerate the immersive interaction between human and augmented 3D worlds. Here, authors discuss olfactory feedback that facilitate with real objects evolution of wearable devices for VR/AR applications.

Language: Английский

Citations

11
Pressure calibration-free gas sensing based on transfer learning assisted wavelength modulation spectroscopy DOI
Huidi Zhang,

Zifei Li,

Huilin Chen

et al.

Optics & Laser Technology, Journal Year: 2025, Volume and Issue: 186, P. 112687 - 112687

Published: Feb. 26, 2025

Language: Английский

Citations

1
Artificial‐Intelligence‐Enhanced Mid‐infrared Lab‐on‐a‐Chip for Mixture Spectroscopy Analysis DOI Open Access

Jingkai Zhou,

Xinmiao Liu, Hong Zhou

et al.

Laser & Photonics Review, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 15, 2024

Abstract Bio/chemical mixture sensing in a water environment is of great importance applications. Relying on plentiful molecular fingerprints mid‐infrared (MIR) and high integration potential, nanophotonic waveguide‐based MIR lab‐on‐a‐chip (LoC) provides miniaturized versatile solution for specific label‐free bio/chemical detection. However, it still challenging to implement an LoC with on‐chip photodetection chemical water, due the strong absorption limited photodetector scheme, let alone spectral overlap issue analysis. Here, integrating zero‐bias graphene reported real‐time monitoring three analytes leveraging demonstrated. Besides, using machine learning, collected spectra ternary 27 mixing ratios are successfully classified accuracy 95.77%. Moreover, concentration prediction individual performed by developing convolution regression network spectrum decomposition: 83.33% single‐component predictions within 1 vol% error range, average root‐mean‐squared achieved. The offers new opportunities highly integrated intelligent systems various scenarios Internet Things era.

Language: Английский

Citations

5
Recent advances and trends in mid-infrared chem/bio sensors DOI Creative Commons
G. Flores-Rangel,

Lorena Diaz de León Martínez,

Lisa S. Walter

et al.

TrAC Trends in Analytical Chemistry, Journal Year: 2024, Volume and Issue: 180, P. 117916 - 117916

Published: Aug. 27, 2024

Language: Английский

Citations

5
Multimodal In‐Sensor Computing System Using Integrated Silicon Photonic Convolutional Processor DOI Creative Commons
Zian Xiao, Zhihao Ren, Yuzheng Zhuge

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 28, 2024

Abstract Photonic integrated circuits offer miniaturized solutions for multimodal spectroscopic sensory systems by leveraging the simultaneous interaction of light with temperature, chemicals, and biomolecules, among others. The data is complex has huge volume high redundancy, thus requiring communication bandwidth associated power consumption to transfer data. To circumvent this cost, photonic sensor processor are brought into intimacy propose a in‐sensor computing system using an silicon convolutional processor. A microring resonator crossbar array used as implement operation 5‐bit accuracy, validated through image edge detection tasks. Further integrating sensor, in situ processing demonstrated, achieving classification protein species different types concentrations at various temperatures. accuracy 97.58% across 45 classes achieved. demonstrates feasibility processors sensors enhance capability devices edge.

Language: Английский

Citations

5
Development of Photonic In-Sensor Computing Based on a Mid-Infrared Silicon Waveguide Platform DOI
Xinmiao Liu, Zixuan Zhang,

Jingkai Zhou

et al.

ACS Nano, Journal Year: 2024, Volume and Issue: 18(34), P. 22938 - 22948

Published: Aug. 12, 2024

Neuromorphic in-sensor computing has provided an energy-efficient solution to smart sensor design and on-chip data processing. In recent years, various free-space-configured optoelectronic chips have been demonstrated for neuromorphic vision However, waveguide-based with different modalities is still lacking. Here, by integrating a responsivity-tunable graphene photodetector onto the silicon waveguide, processing unit realized in mid-infrared wavelength range. The weighting operation achieved dynamically tuning bias of photodetector, which could reach 4 bit precision. Three neural network tasks are performed demonstrate capabilities our device. First, image preprocessing handwritten digits fashion product classification as general task. Next, resistive-type glove signals reversed applied input gesture recognition. Finally, spectroscopic binary gas mixture utilizing broadband performance device from 3.65 3.8 μm. By extending near-infrared mid-infrared, work shows capability waveguide-integrated tunable viable photonic computing. Furthermore, such be used large-scale integrated circuits at edge.

Language: Английский

Citations

4
Parts-per-Trillion-Level Acetone Gas Detection Using a Suspended Graphene/SiO2 SAW Breath and Skin Gas Sensor: Simulation and Experimental Study DOI
Hao‐Long Zhou, Sankar Ganesh Ramaraj, Md Shamim Sarker

et al.

ACS Sensors, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 13, 2025

Detection of parts-per-trillion (ppt)-level acetone gas molecules at room temperature using suspended graphene on SiO2 micropillars has rarely been achieved solid-state devices or surface acoustic wave (SAW) sensors. This paper presents the effect and as a guiding sensing layer to detect gas. The integration with introduces coupled resonance arising from interaction between mechanical vibrations micropillars. leads formation hybrid modes when natural frequencies align. coupling mechanism amplifies displacement energy Love propagating along sensor, enhancing its overall performance. Additionally, waves generates characteristic dips in transmission spectra. These correspond excitation specific flexural torsional within structure. A custom-fabricated SAW device, featuring diameter 4 μm heights 1.0 1.2 μm, demonstrated exceptionally high sensitivity toward concentration 500 ppt. Moreover, exhibited rapid response recovery times across wide range concentrations.

Language: Английский

Citations

0
Moving Toward Human‐Like Perception and Sensation Systems—From Integrated Intelligent Systems to Decentralized Smart Devices DOI Creative Commons
Zhongda Sun, Tianyiyi He, Zhihao Ren

et al.

Published: March 1, 2025

ABSTRACT Artificial Intelligence (AI) has shown the power to enhance functionality of sensors and enable intelligent human‐machine interfaces through machine learning‐based data analysis. However, good performance AI is always accompanied by a large amount high computational complexity. Though cloud computing appears be right solution this issue with advent 5G era, certain intelligence edge terminal also important make entire integrated system more efficient. The current development microelectronic, wearable, AI, neuromorphic technologies pave way realize advanced integrating silicon‐based high‐computing‐power chips anthropomorphic wearable sensory devices show potential achieve human‐like self‐sustainable decentralized next‐generation AI. Hence, in review, we systematically introduce related progress terms electronics that can mimic biological features humans' systems neuromorphic/in‐sensor technologies. Discussion on implementing perception sensation silicone‐based non‐silicone‐based functional units our perspectives are provided.

Language: Английский

Citations

0
Photonic Bayesian Neural Networks: Leveraging Programmable Noise for Robust and Uncertainty‐Aware Computing DOI Creative Commons
Yangyang Zhuge, Zhihao Ren, Zian Xiao

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: April 27, 2025

Abstract Photonic neural networks (PNNs) based on silicon photonic integrated circuits (Si‐PICs) offer significant advantages over microelectronic counterparts, including lower energy consumption, higher bandwidth, and faster computing speeds. However, the analog nature of optical signal in PNNs makes Si‐PIC solutions highly sensitive to device noise, especially when using fixed‐value deterministic models, which are not robust hardware fluctuation. Furthermore, current unable handle data uncertainty, a critical factor applications such as autonomous driving, medical diagnostics, financial forecasting. Herein, Bayesian network (PBNN) architecture that incorporates principles enhance robustness address uncertainty is proposed. In PBNN, noise leveraged through photonic‐noise‐based random number generators, combine Mach‐Zehnder interferometers micro‐ring resonators independently control output mean standard deviation. Based modelling with experimentally extracted data, PBNN achieves classification accuracy up 98% for handwritten digit recognition, matching full‐precision models conventional computers. Beyond classification, excels multimodal processing, regression, outlier detection. This scalable, energy‐efficient transforms into computational value, addressing limitations enabling uncertainty‐aware real‐world applications.

Language: Английский

Citations

0