Article
Nanoscience & Nanotechnology
Young-Gyun Kim, Younggyun Cho, Youngbok Lee, Kyoungdoug Min, Sung-Hoon Ahn
Summary: This study demonstrates the fabrication of high-performance gas sensors based on the surface property changes of a Fabry-Perot cavity. The proposed sensor rapidly responds to corrosive gases, showing significant color changes and absorption wavelength shifts, and can be mass-produced using conventional methods. The sensor's superior performance and productivity potential are verified through NO2 gas experiments, showcasing its applicability in urban areas and factories.
ACS APPLIED NANO MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Timm Swoboda, Nicolas Wainstein, Sanchit Deshmukh, Cagil Koroglu, Xing Gao, Mario Lanza, Hans Hilgenkamp, Eric Pop, Eilam Yalon, Miguel Munoz Rojo
Summary: Heat dissipation is a major concern for electronic devices, especially at the nanoscale. Scanning thermal microscopy (SThM) is a versatile tool for measuring device temperature with nanoscale resolution but quantifying thermal features is challenging. This study calibrates a thermo-resistive SThM probe using metal lines of different widths and evaluates its sensitivity under different conditions. The results provide new insights for accurately determining the temperature of scanned devices.
Article
Engineering, Electrical & Electronic
Lucjan Grzegorzewski, Robert Zierold, Robert H. Blick
Summary: In this study, a novel coupling-based sensor operating at 20 GHz was designed to increase the sensitivity for detecting nanoscale objects. The sensor's geometry was fine-tuned for an optimal coupling coefficient, and its performance was compared with that of conventional sensors. The exceptional sensitivity of the sensor was demonstrated through the in-flow detection of 200 nm-sized polystyrene beads, achieving a high signal-to-noise ratio.
IEEE SENSORS JOURNAL
(2023)
Article
Nanoscience & Nanotechnology
Stefan Nedelcu, Kishan Thodkar, Christofer Hierold
Summary: This article reports a customizable, portable, battery-operated, wireless platform for interfacing high-sensitivity nanoscale sensors, aiming to improve spatiotemporal measurement coverage of physical parameters. The platform has a wide current range and high versatility, suitable for signal acquisition from resistive nanosensors, with overall low power consumption, making it highly suitable for various sensing applications within the context of IoT.
MICROSYSTEMS & NANOENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Luis Costa, Zhongwen Zhan, Alireza Marandi
Summary: By using mode-walk-off interferometry, we have introduced a position-resolved sensing technique that can measure and localize physical changes in optical fibers without relying on round-trip time-of-flight measurements. This method overcomes the fundamental barriers of bidirectional propagation, making it compatible with fiber communication links containing non-reciprocal elements.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Artem Talantsev, Elvira Paz, Tim Bohnert, Andre Araujo, Ricardo Ferreira
Summary: An array of magnetic tunnel junctions in a Wheatstone bridge is used as a positioning sensor to detect spatial displacement of a magnetized object. The sensor signal is recorded to determine the effects of various parameters on sensor performance, and an optimized experimental configuration allows for detection of displacement steps as small as 10 nm.
Article
Engineering, Electrical & Electronic
Tim John Joseph, Venkataraman Kartik
Summary: This article presents a low-noise high-bandwidth GMR sensor-readout circuit for precise position sensing in applications like atomic force microscopy. The main challenge is the GMR sensor's high 1/f noise, which limits the achievable SNR. The article investigates the noise characteristics and effect on SNR, and presents a general process for designing the readout circuit. A resolution of 2.5nm over a bandwidth of 100kHz is demonstrated on an AFM nanopositioner, showing significant improvement compared to previous GMR sensor performance.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Heng Wang, Shuangyi Wang, Rajesh Rajamani
Summary: This paper proposes a new electromagnetic angular position sensing method using high-magnetic-permeability metal, which is non-contacting, non-intrusive, and can achieve accurate angle measurements with immunity to ferromagnetic disturbances.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Giuseppe Romano, Steven G. Johnson
Summary: In this study, a methodology for density-based topology optimization of non-Fourier thermal transport in nanostructures is introduced. It utilizes adjoint-based sensitivity analysis of the phonon Boltzmann transport equation (BTE) and a novel material interpolation technique called the transmission interpolation model (TIM). The approach is able to handle the interplay between real- and momentum-resolved material properties by parameterizing the material density with an interfacial transmission coefficient. This methodology allows for the systematic optimization of materials for heat management and conversion, as well as the design of devices where diffusive transport is not valid.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Chemistry, Analytical
Natanael Cuando-Espitia, Andres Camarillo-Aviles, Daniel A. May-Arrioja, Ivan Hernandez-Romano, Miguel Torres-Cisneros
Summary: This paper proposes a ratiometric fiber optic temperature sensor based on a highly coupled seven-core fiber (SCF), which is experimentally demonstrated. The sinusoidal spectral response of the SCF in transmission configuration is analyzed theoretically. The sensor consists of two SCF devices with anti-phase transmission spectra, and the devices are easily fabricated by splicing a 2 cm long SCF segment between two single-mode fibers (SMFs). The sensor shows robustness against light source fluctuations, with a standard deviation of 0.2% in the ratiometric measurements when the light source varies by 12%. Its low-cost detection system (two photodetectors) and wide temperature detection range (25 degrees C to 400 degrees C) make it a highly attractive and promising device for real industrial applications.
Article
Chemistry, Multidisciplinary
Bendix Ketelsen, Hendrik Schlicke, Verena R. Schulze, Sophia C. Bittinger, Shin-Da Wu, Shan-hui Hsu, Tobias Vossmeyer
Summary: Directional strain sensing is crucial for advanced sensor applications in the field of human-machine interfaces and healthcare. This study focuses on the angle dependent anisotropic strain sensitivity caused by charge carriers percolating through cross-linked gold nanoparticle networks, and utilizes these versatile materials to fabricate wearable triaxial pulse and gesture sensors. The anisotropic response of the materials is separated into geometric and piezoresistive contributions, indicating a slightly anisotropic behavior. The materials are patterned and embedded into a flexible silicone polymer for healthcare applications, with a wireless read-out demonstrating their potential for skin-wearable healthcare sensors.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Semih Taniker, Vincenzo Costanza, Paolo Celli, Chiara Daraio
Summary: We propose the realization of capacitive temperature sensors based on the concept of displacement amplification. Our design utilizes high CTE metallic layers and a low CTE dielectric layer to achieve large out-of-plane displacements and capacitive changes as the temperature increases.
IEEE SENSORS JOURNAL
(2022)
Article
Chemistry, Physical
Jinniu Zhang, Tingting Shao, Juntang Dong, Gang Li, Jia Liu, Yumeng Liu, Ruyi Yang, Jianzhi Gao, Lu Li, Yanmin Jia, Lizhai Zhang, Hongbing Lu
Summary: In this study, mesoporous PtO-WO3 nanofibers were constructed using a facile one-step electrospinning technique for highly sensitive and selective acetone sensing. The effective immobilization of well-dispersed PtO nanocatalysts within the mesoporous WO3 NFs allowed for efficient catalysis and gas diffusion, enhancing the interaction between active O2- and acetone molecules. The PtO-WO3 NFs exhibited significantly improved acetone sensing properties compared to pure WO3 NFs, with a 6.5-fold higher response to 100 ppm acetone at 260 degrees C. The mesoporous WO3 NFs with uniformly distributed PtO nanocatalysts showed great potential for detecting acetone.
JOURNAL OF ALLOYS AND COMPOUNDS
(2023)
Article
Physics, Applied
Ronald J. Warzoha, Adam A. Wilson, Brian F. Donovan, Andrew N. Smith, Nicholas Vu, Trent Perry, Longnan Li, Nenad Miljkovic, Elizabeth Getto
Summary: This study develops a numerical fitting routine to extract multiple thermal parameters using frequency-domain thermoreflectance for materials with non-standard geometries. The routine is validated and demonstrated to be effective in extracting thermal properties, especially for materials with arbitrary geometries.
JOURNAL OF APPLIED PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Tsan-Wen Lu, Zhen-Yu Wang, Kuang-Ming Lin, Po-Tsung Lee
Summary: This report introduces a 1D photonic crystal nanocavity with waveguide-like strain amplifiers for highly sensitive pressure and position optical sensors. It demonstrates the nanocavity's ability to detect minute position differences and the distinct behaviors in wavelength shifts when applying localized pressure. The feasibility of using the strain amplifier as an effective waveguide for extracting the sensing signal is also proposed and validated.
Review
Physics, Applied
Manuel Le Gallo, Abu Sebastian
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2020)
Article
Multidisciplinary Sciences
J. Feldmann, N. Youngblood, M. Karpov, H. Gehring, X. Li, M. Stappers, M. Le Gallo, X. Fu, A. Lukashchuk, A. S. Raja, J. Liu, C. D. Wright, A. Sebastian, T. J. Kippenberg, W. H. P. Pernice, H. Bhaskaran
Summary: With the advancement of technology, the demand for fast processing of large amounts of data is increasing, making highly parallelized, fast, and scalable hardware crucial. The integration of photonics can serve as the optical analogue of an application-specific integrated circuit, enabling photonic in-memory computing and efficient computational hardware.
Correction
Multidisciplinary Sciences
J. Feldmann, N. Youngblood, M. Karpov, H. Gehring, X. Li, M. Stappers, M. Le Gallo, X. Fu, A. Lukashchuk, A. S. Raja, J. Liu, C. D. Wright, A. Sebastian, T. J. Kippenberg, W. H. P. Pernice, H. Bhaskaran
Article
Engineering, Electrical & Electronic
Geethan Karunaratne, Manuel Le Gallo, Michael Hersche, Giovanni Cherubini, Luca Benini, Abu Sebastian, Abbas Rahimi
Summary: The emerging brain-inspired computing paradigm, hyperdimensional computing (HDC), offers a lightweight learning framework for various cognitive tasks compared to traditional deep learning methods. This study proposes an architecture for processing spatio-temporal (ST) signals within the HDC framework using in-memory compute arrays, achieving significant energy efficiency, area, and throughput gains while maintaining peak classification accuracy.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2021)
Article
Multidisciplinary Sciences
Geethan Karunaratne, Manuel Schmuck, Manuel Le Gallo, Giovanni Cherubini, Luca Benini, Abu Sebastian, Abbas Rahimi
Summary: The paper proposes a novel architecture that utilizes computational memory units to perform analog in-memory computation on high-dimensional vectors, enhancing neural networks with explicit memory and achieving accuracy matching 32-bit software equivalent.
NATURE COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Syed Ghazi Sarwat, Timothy M. Philip, Ching-Tzu Chen, Benedikt Kersting, Robert L. Bruce, Cheng-Wei Cheng, Ning Li, Nicole Saulnier, Matthew BrightSky, Abu Sebastian
Summary: Phase-change memory devices are utilized in in-memory computing to compute without needing to transfer data between memory and processing units. The projection of phase configurations onto stable elements within the device is a promising approach to address nonidealities. By investigating the projection mechanism in prominent phase-change memory device architectures, such as the mushroom-type phase-change memory, the key attributes and operational principles of nanoscale projected Ge2Sb2Te5 devices are understood.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Benedikt Kersting, Syed Ghazi Sarwat, Manuel Le Gallo, Kevin Brew, Sebastian Walfort, Nicole Saulnier, Martin Salinga, Abu Sebastian
Summary: Chalcogenide phase change materials are utilized for non-volatile, low-latency storage-class memory and new forms of computing, but face challenges with temporal drift in electrical resistance. Research shows that the efficacy of observation is influenced by the observable timescale, and experimental measurements of drift onset can be conducted using threshold-switching voltage. This additional feature of structural relaxation dynamics serves as a new benchmark for evaluating classical models explaining drift.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Computer Science, Hardware & Architecture
Martino Dazzi, Abu Sebastian, Thomas Parnell, Pier Andrea Francese, Luca Benini, Evangelos Eleftheriou
Summary: In-memory computing is a new computing paradigm that enables deep-learning inference with higher energy-efficiency and lower latency. Communication fabric is a key challenge in this paradigm, and we propose a graph-based communication structure suitable for convolutional neural networks, achieving efficient pipelined execution. Our proposed topology shows lower bandwidth requirements per communication channel compared to established communication topologies, and we demonstrate a hardware implementation mapping ResNet-32 onto an IMC core array interconnected via this communication fabric.
IEEE TRANSACTIONS ON COMPUTERS
(2021)
Article
Engineering, Electrical & Electronic
Riduan Khaddam-Aljameh, Michele Martemucci, Benedikt Kersting, Manuel Le Gallo, Robert L. Bruce, Matthew BrightSky, Abu Sebastian
Summary: By designing unit-cell arrays and implementing diagonal connections, we have successfully addressed challenges such as parallel writing and computational precision in memristive crossbar arrays.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Laric Bobzien, Ann-Katrin U. Michel, Nolan Lassaline, Carin R. Lightner, Alexander C. Hernandez Oendra, Sebastian Meyer, Iason Giannopoulos, Abu Sebastian, Samuel Bisig, Dmitry N. Chigrin, David J. Norris
2021 CONFERENCE ON LASERS AND ELECTRO-OPTICS EUROPE & EUROPEAN QUANTUM ELECTRONICS CONFERENCE (CLEO/EUROPE-EQEC)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Malte J. Rasch, Diego Moreda, Tayfun Gokmen, Manuel Le Gallo, Fabio Carta, Cindy Goldberg, Kaoutar El Maghraoui, Abu Sebastian, Vijay Narayanan
Summary: The IBM ANALOG HARDWARE ACCELERATION KIT is an open source toolkit for simulating analog crossbar arrays in a convenient fashion from within PYTORCH. The toolkit allows for extending network modules and composing arbitrary ANNs, configuring analog tiles to emulate various hardware characteristics and non-idealities, and utilizing advanced analog optimization algorithms. Additionally, it enables hardware-aware training features and provides statistical noise and drift models to evaluate the accuracy of chips targeting inference acceleration.
2021 IEEE 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Geethan Karunaratne, Abbas Rahimi, Manuel Le Gallo, Giovanni Cherubini, Abu Sebastian
2021 IEEE 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS)
(2021)
Proceedings Paper
Engineering, Electrical & Electronic
Michele Martemucci, Benedikt Kersting, Riduan Khaddam-Aljameh, Irem Boybat, S. R. Nandakumar, Urs Egger, Matthew Brightsky, Robert L. Bruce, Manuel Le Gallo, Abu Sebastian
Summary: The proposed weight mapping algorithm efficiently programs a synaptic unit composed of multiple phase change memory devices, showing resilience to device-level non-idealities and yield. The algorithm is experimentally validated on a prototype PCM unit cell fabricated in the 90nm CMOS technology node.
2021 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)
(2021)
Article
Mathematical & Computational Biology
Martino Dazzi, Abu Sebastian, Luca Benini, Evangelos Eleftheriou
Summary: In-memory computing (IMC) is a non-von Neumann paradigm that offers energy-efficient, high throughput hardware for deep learning applications. This approach requires a rethink of architectural design choices due to its different execution pattern compared to previous computational paradigms. When applied to Convolution Neural Networks (CNNs), IMC hardware can achieve throughput and latency beyond current state-of-the-art for image classification tasks.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2021)
Proceedings Paper
Engineering, Multidisciplinary
R. L. Bruce, S. Ghazi Sarwat, I Boybat, C-W Cheng, W. Kim, S. R. Nandakumar, C. Mackin, T. Philip, Z. Liu, K. Brew, N. Gong, I Ok, P. Adusumilli, K. Spoon, S. Ambrogio, B. Kersting, T. Bohnstingl, M. Le Gallo, A. Simon, N. Li, I Saraf, J-P Han, L. Gignac, J. M. Papalia, T. Yamashita, N. Saulnier, G. W. Burr, H. Tsai, A. Sebastian, V Narayanan, M. BrightSky
Summary: Phase change memory (PCM) is being considered for non-von Neumann accelerators for deep neural networks based on in-memory computing. Conductance drift and noise are key challenges for reliable storage of synaptic weights in such accelerators. The integration of a projection liner into multilevel mushroom-type PCM devices demonstrates mitigation of conductance drift and noise, with further improvement shown by combining with a low-drift phase-change material. Large-scale experiments confirm lower drift and device-to-device drift variability for devices with projection liner, crucial for in-memory computing accelerators.
2021 IEEE INTERNATIONAL RELIABILITY PHYSICS SYMPOSIUM (IRPS)
(2021)
