Printed circuit boards (PCBs) are indispensable components that enable the functionality of modern electronics applications. Ranging from various densities and uniqueness by design, the attack surfaces of these devices are vast and complex. In secure/critical domains like medical, automotive, and defense, the authenticity of these devices is critical to mitigate losses in trust and security. Not only does their complexity and responsibility in a hardware system pose an issue, but the globalization of their supply chain further emphasizes the necessity of methods to validate their designs. In this paper, the authors propose a novel framework for furthering PCB trust by addressing pitfalls in verifying the connectivity design of PCBs. Incorporating data from both imaging modalities into a cohesive model framework aims to address the shortfalls of single-modality autonomous netlist approaches.
This study proposes a novel approach to streamline the manual identification and classification of 2D materials on-chip devices, crucial for rapid prototyping. Leveraging high-resolution imaging and smart stitching techniques, our method achieves a comprehensive representation of the material landscape. Advanced image processing algorithms, including mask-RCNN segmentation, extract key material attributes such as surface area and morphology. A tailored U-Net model is trained for precise material identification, encompassing parameters like composition and thickness. Performance evaluation involves state-of-the-art model architectures and hyperparameter optimization. By automating the material identification process and integrating with a sophisticated transfer system, manual intervention is minimized, expediting prototyping workflows. This framework not only enhances efficiency but also aligns with contemporary trends in materials science and machine learning research, fostering advancements in rapid prototyping capabilities.
Developing energy-efficient optical components for computing is crucial for AI-driven hardware technologies. While previous studies primarily focused on optimizing cache-level design and managing write-intensive memory addresses, the impact of clock frequency on the energy consumption of emerging memory technologies, such as PCM, remains underexplored. In this work, through comprehensive simulation-based analysis, we reveal the complex relationship between clock frequency and the energy efficiency of OPCM, SRAM, and DRAM. The proposed memory architecture has demonstrated the potential to reduce overall energy consumption by up to 75% for the MiBench benchmark suite, a widely used set of embedded systems and IoT workloads. This work contributes to the ongoing efforts to improve the energy efficiency of optical computing systems, a critical factor in realizing the full potential of these emerging technologies.
Recent advancements in optical communications have explored the use of spatially structured beams, especially orbital angular momentum (OAM) beams, to achieve high-capacity data transmission. Traditional electronic convolutional neural networks (CNNs), while effective, face significant challenges in demultiplexing OAM beams efficiently, notably their high power consumption and substantial computational time, which can limit realtime processing capabilities in high-speed optical communication systems. In this study, we propose a hybrid optical-electronic CNN that integrates Fourier optics convolution for intensity recognition-based demultiplexing of multiplexed OAM beams under simulated atmospheric turbulence. Experimental results showed that the proposed hybrid neural network system achieves a 69% demultiplexing accuracy under strong turbulence conditions while exhibiting a three times reduction in training time compared to all-electronic CNNs. This study underscores the potential of a hybrid optical-electronic neural network to enhance both performance and efficiency in OAM-based optical communication systems.
Here, we introduce an optical computing method using free-space optics and a 4f system to enhance and integrate data processing, encryption, and machine learning. We propose a Reconfigurable Complex Convolution Module (RCCM) which enables simultaneous amplitude and phase modulation of optical signals for complex convolution operations in the Fourier domain. Utilizing spatial light modulators and interferometric techniques based on the Michelson interferometer, the RCCM achieves precise control over light properties. The system demonstrates promising applications in optical hashing, data compression, and accelerating machine learning tasks, particularly for processing encrypted data. Experimental results show the RCCM’s ability to perform complex convolutions with high accuracy, though trade-offs between compression ratios and classification accuracy are observed. This research represents a significant advancement in optical computing, addressing challenges in data security, processing speed, and computational efficiency across various fields.
This study explores a novel photodetector based on the binary topological insulator bismuth selenide (Bi2Se3), leveraging its unique surface conduction properties and high surface-to-volume ratio. Unlike previous research focusing on heterojunctions, we investigate the intrinsic polarization selectivity of Bi2Se3. Our experimental results demonstrate a stable responsivity of 22.6 A/W under a -0.6 V bias voltage with 860 nm laser illumination and a polarization-sensitive switching of 10.9 dB. The device exhibits sensitivity across the near-infrared spectrum, showcasing its potential for applications in low-noise imaging, environmental monitoring, and optical communication. Additionally, the high polarization sensitivity paves the way for promising applications in non-destructive material assessment, hardware security enhancement, and secure communication systems.
This work presents the fabrication and experimental demonstration of heterogeneously integrated photodetectors using monolayer WS₂, aimed at advancing ultra-thin optoelectronic devices. By employing silicon nitride wafers with SiN/SiO₂ layers, precise device patterning was achieved through electron beam lithography and dry etching, followed by the integration of WS₂ flakes using a wet etching technique. The study focused on the device's broadband transmission properties, observing a significant shift in the exciton absorption wavelength (~10 nm) due to strain introduced during the integration process. This shift highlights the potential for manipulating optical properties through strain engineering. The devices exhibited high spectral responsivities at the WS₂ exciton wavelength, demonstrating their efficacy in the visible spectrum. These findings pave the way for future on-chip photonic devices operating at visible wavelengths, with promising applications in strainoptronics and other advanced optoelectronic systems.
Here, we present a vanadium carbide (V2C) mid-infrared (mid-IR) photodetector. Drop casting and spin coating a silicon substrate with a thin silicon oxide layer produced the V2C photodetector. Isopropyl alcohol and nitrogen gas drying increased material quality. E-beam lithography and metal deposition of Au/Ti contacts on V2C flakes carefully made electrical connections. Electrical bias and 2 μm laser light evaluated the V2C photodetector’s dark current and photocurrent responses. Photocurrent response changed dramatically, matching FTIR spectroscopy findings. V2C’s peak responsivity of 2.65 A/W demonstrated mid-IR photodetection. To test scalability, we created devices with 2-5 μm channels. For specialized sensing, photocurrent increases with channel length. Onchip waveguides and photonic circuits might use V2C photodetectors. V2C’s mid-IR photodetector exhibits its promise as a cutting-edge optoelectronics and integrated photonics material. This work expands mid-IR-sensing photodetector technology.
2D materials and specifically Transition Metal Dichalcogenides have received much attention as photoactive materials in photodetectors. These materials possess attractive properties, including a direct bandgap in the visible range and mechanical resilience to strain, making them an attractive material for flexible photodetectors. Here we demonstrate 4x4 pixel photodetector arrays on flexible and non-flexible substrates based on mechanically exfoliated flakes of MoS2. The arrays have a minimum pitch between array pixels of 9.5 µm in both vertical and horizontal directions. Demonstrating, to our knowledge, the densest 2D material based photodetector array to date.
As Internet-of-Things (IoT) devices continue to grow rapidly in number, developing energy-efficient memory solutions has become critically important. This paper introduces an innovative Phase Change Memory (PCM) architecture that can significantly reduce memory energy consumption in IoT devices. After highlighting the energy-inefficiency of current memory designs, we explore the possibilities of leveraging PCM. We demonstrate that the benefits of exploiting PCM are dependent on the working frequency of the CPU and show how PCM can surpass devices with SRAM and DRAM. As a replacement candidate for FLASH, PCM can also be utilized instead of SRAM and DRAM. We also demonstrate that based on the application we can also save more energy. Ongoing work focuses on deployment of this application dependency and enhancing energy efficiency of devices using PCM. Our PCM innovation enables improved functionality lifetimes for non-volatile IoT edge devices. This represents a major advance towards realizing widespread integration of photonics and electronics in IoT hardware.
Binarized neural networks offer substantial reductions in memory and computational requirements compared to full precision networks. However, conventional CMOS-based hardware implementations still face challenges with resilience for deployment in harsh environments like space. This paper proposes an optical XOR-based accelerator for binarized neural networks to enable low power and resilient operation. The optical logic gates rely on wavelength-specific intensity propagation rather than absolute intensity levels. This provides inherent robustness against fabrication process variations and high energy particle strikes. Simulations of an optical hardware prototype for XNOR-Net show the accelerator achieves 1.2 μs latency and 3.2 mW power. The binarized network maintained 2-4% accuracy degradation compared to the full precision baseline on MNIST and CIFAR-10. The proposed optical accelerator enables efficient and resilient deployment of binarized neural networks for harsh environment applications like spacecraft and satellites.
Here, we're pioneering a novel approach in photonics, targeting the development of ultra-low power communication systems and advanced sensing technologies. Central to our strategy is the implementation of a unique zig-zag structure, designed to achieve femtojoule (fJ) per bit communication efficiency. A key innovation in our approach is the integration of unidirectional coupling through on-chip isolation, seamlessly connecting a Transverse Coupled Cavity VCSEL (TCCVCSEL) to the modulator and then to a waveguide. This project has wide-ranging implications, extending beyond just creating new devices. It's geared towards establishing a robust III/V platform, serving as a cornerstone in the field of photonics and integrated circuit technology. Our work is poised to catalyze advancements in high-speed, low-power photonic systems, potentially setting new benchmarks in the industry.
Here we demonstrate Tungsten Disulfide (WS2) integrated silicon nitride photodetector, and we experimentally tested the responsivity of 0.32 A/W. The spectroscopic results using PL and Raman mapping were used to understand strain effect on excitonic bandgap by studying characteristics like excitons, trions, E12g, A1g and opto-electronic response. We show high potential for flexible sensors and high spectral resolution sensing.
This study aimed to develop and implement a novel data encryption method that utilizes a hybrid processor Photonic Tensor Core and chaotic oscillators to generate an "infinite key" suitable for use with common encryption algorithms. To demonstrate its effectiveness, we built a prototype consisting of a hybrid processor simulator, chaotic oscillators, a key generator, an encryption/decryption tool, and a graphical user interface. We tested and inspected the tool using custom scripts and a graphical user interface, which allows two separate users to compare their respective results. In upcoming studies, we plan to expand the tool to accommodate multiple participants and develop a hardware prototype.
The rapid development of nanophotonic technologies has put forward higher requirements for optoelectronic devices, including ultra-small footprints, high-speed operation, high efficiency, and low power consumption. Optoelectronics based on emerging materials can provide the material framework that can keep pace with future technological demands. Here we will share our latest innovations and device demonstrations of using low-dimensional materials towards discovering high-performance photodetector and electro-optic modulator performances. We will share the concept of strainoptronics enabling to engineer a plurality of material properties (bandgap, workfunction, mobility) and show how a Transition-Metal Dichalcogenides (TMDC)-based efficient photodetector can be realized using MoS2 on a Silicon photonic platform. Furthermore, using scaling-length-theory, we show our roadmap and results of high gain-bandwidth product photodetectors using a metal slot atop a silicon photonic waveguide towards optimizing the carrier-lifetime to transit time ratio. These devices were enabled by a novel 3D-like 2D material transfer system, which also enabled us to demonstrate a 2D material PN junction photodetector operating at zero bias, thus leading to extremely low dark currents and hence very efficient noise-equivalent powers. Finally, we show our latest work on ITO-thin film electro-optic modulators with 40 GHz 3dB roll-off, requiring just 200 meV of the drive voltage. Further development of the modulator platform shows the potential of a 100 GHz fast MZI modulator with a footprint that is 1,000 more compact than standard Silicon photonics and 10,000 more compact compared to Lithium Niobite.
KEYWORDS: Photodetectors, Heterojunctions, Sensors, Signal detection, Near infrared, Visible radiation, Three dimensional sensing, Signal to noise ratio, Remote sensing, Physics
Here, we demonstrate a 2D p–n van der Waals heterojunction photodetector constructed by vertically stacking p-type and n-type few-layer indium selenide (InSe) 2D flakes. This heterojunction charge-separation-based photodetector shows a three-fold enhancement in responsivity at near-infrared spectral region (980 nm) as compared to a photoconductor detector based on p- or n-only doped regions, respectively. We show, that this junction device exhibits self-powered photodetection operation and hence enables few pA-low dark currents, which is about 3-4 orders of magnitude more efficient than state-of-the-art foundry-based devices. Such capability opens doors for small signal-to-noise environments and low photon-count detectability without having to rely on external gain. We further demonstrate millisecond response rates in this sensitive zero-bias voltage regime.
Here we present our latest PIC-integrated TMD-based slot-enhanced photodetector. The
metallic slot enhances the light-matter-interaction and hence absorption into the semiconductor TMD layer.
Unlike Graphene detectors, this device based on a 1+eV wide Eg detector (MoTe2) shows a low dark-current
Of 100’s pA (i.e. 3 orders of magnitude lower than graphene). Utilizing the plasmonic slot allows to harness
scaling effects known from FETs, and reduce carrier transit times. Thus, we demonstrate 10GHz roll-offs
despite a rather low mobility. We further show that the short-channel allows for near-ballistic transport, and
more importantly high gain-bandwidth-products (GPB), which scales with the source-drain distance squared.
The combination of a TMD semiconductor with a slot for short transit times, enables we new class of
efficient yet compact PIC-integrated detectors offering high GBP.
In this work, we demonstrate a photodetector (PD) based on heterogeneous integration of Few-layer MoTe2 integrated on planarized and non-planarized Si waveguide operating at 1550 nm. Under a strong local tensile strain (4%), the bandgap of few layers MoTe2 shifts from 1 eV to 0.8 eV, enabling higher responsivity as compared to unstrained one.
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