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This paper presents the concepts behind the BrainScales (BSS) accelerated analog neuromorphic computing architecture. It describes the second-generation BrainScales-2 (BSS-2) version and its most recent in-silico realization, the HICANN-X…
Molybdenum disulfide (MoS2) has drawn great interest for tunable photonics and optoelectronics advancement. Its solution processing, though scalable, results in randomly networked ensembles of discrete nanosheets with compromised properties…
Two-dimensional (2D) semiconductors have been proposed for heterogeneous integration with existing silicon technology; however, their chemical vapor deposition (CVD) growth temperatures are often too high. Here, we demonstrate direct CVD…
Blood oxygen saturation (SpO2) is a vital marker for healthcare monitoring. Traditional SpO2 estimation methods often rely on complex clinical calibration, making them unsuitable for low-power, wearable applications. In this paper, we…
With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the…
We present a scalable in-pixel processing architecture that can reduce the data throughput by 10X and consume less than 30 mW per megapixel at the imager frontend. Unlike the state-of-the-art (SOA) analog process-in-pixel (PIP) that…
Interconnectivity, fault tolerance, and dynamic evolution of the circuitry are long sought-after objectives of bio-inspired engineering. Here, we propose dendritic transistors composed of organic semiconductors as building blocks for…
Two-dimensional lateral heterojunctions are basic components for low-power and flexible optoelectronics. In contrast to monolayers, devices based on few-layer lateral heterostructures could offer superior performance due to their lower…
Copper nanowires are widely used as on-chip interconnects due to superior conductivity. However, with aggressive Cu interconnect scaling, the diffusive surface scattering of electrons drastically increases the electrical resistivity. In…
Long-range moire patterns in twisted WSe2 enable a built-in, moire-length-scale ferroelectric polarization that can be directly harnessed in electronic devices. Such a built-in ferroic landscape offers a compelling means to enable…
Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine…
Molecule-based devices are envisioned to complement silicon devices by providing new functions or already existing functions at a simpler process level and at a lower cost by virtue of their self-organization capabilities. Moreover, they…
Learning and logic are fundamental brain functions that make the individual to adapt to the environment, and such functions are established in human brain by modulating ionic fluxes in synapses. Nanoscale ionic/electronic devices with…
Photonic computing using chalcogenide phase-change materials (PCMs) is under active development for energy-efficient artificial intelligence (AI) applications. A key requirement is to enable as many optically programmable levels per device…
Van der Waals (vdW) heterostructures of two-dimensional (2D) materials have become a rich playground for the exploration of correlated quantum phases, and recent studies have begun to probe their non-equilibrium dynamics under femtosecond…
Two-dimensional (2D) layered materials-based field-effect transistors (FETs) are promising for ultimate scaled electron device applications because of the improved electrostatics to atomically thin body thickness. However, compared with the…
The new generation of two-dimensional (2D) materials has shown a broad range of applications for optical and electronic devices. Understanding the properties of these materials when integrated with the more traditional three-dimensional…
Aside from recent advances in artificial intelligence (AI) models, specialized AI hardware is crucial to address large volumes of unstructured and dynamic data. Hardware-based AI, built on conventional complementary metal-oxidesemiconductor…
Fluorescence microscopy is essential to study biological structures and dynamics. However, existing systems suffer from a tradeoff between field-of-view (FOV), resolution, and complexity, and thus cannot fulfill the emerging need of…
Twisted two-dimensional semiconductors generate a moir\'e landscape that confines excitons (bound electron-hole pairs) into programmable lattices, offering routes to efficient light sources, sensing, and room-temperature information…