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Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDs) are emerging as top candidates for post-silicon electronics. While most of 2D TMDs exhibit isotropic behavior, lowering the lattice symmetry could induce…
Memtranstor that correlates charge and magnetic flux via nonlinear magnetoelectric effects has a great potential in developing next-generation nonvolatile devices. In addition to multi-level nonvolatile memory, we demonstrate here that…
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…
We have calculated the key characteristics of associative (content-addressable) spatial-temporal memories based on neuromorphic networks with restricted connectivity - "CrossNets". Such networks may be naturally implemented in…
Neuromorphic computing circuits can be realized using memristors based on low-dimensional materials enabling enhanced metal diffusion for resistive switching. Here, we investigate memristive properties of vertically aligned MoS$_2$…
Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by…
A neuromorphic metasurface embodies mechanical intelligence by realizing physical neural architectures. It exploits guided wave scattering to conduct computations in an analog manner. Through multiple tuned waveguides, the neuromorphic…
This paper presents a novel framework for designing support vector machines (SVMs), which does not impose restriction on the SVM kernel to be positive-definite and allows the user to define memory constraint in terms of fixed template…
We propose and numerically simulate novel reconfigurable logic gates employing spin metal-oxide-semiconductor field-effect transistors (spin MOSFETs). The output characteristics of the spin MOSFETs depend on the relative magnetization…
Neuromorphic devices have gained significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential…
Two-dimensional (2D) semiconductors offer a promising prospect for high-performance and energy-efficient devices especially in the sub-10 nm regime. Inspired by the successful fabrication of 2D $\beta$-TeO$_2$ and the high on/off ratio and…
Integrating semiconducting and magnetic materials could combine transistor-like operation with nonvolatility and enable architectures such as logic-in-memory. Here, we employ correlated electrical transport and scanning nitrogen-vacancy…
The continued evolution of CMOS technology demands materials and architectures that emphasize low power consumption, particularly for computations involving large scale data processing and multivariable optimization. Ferroelectric materials…
The integration of the spin degree of freedom in charge-based electronic devices has revolutionised both sensing and memory capability in microelectronics. Further development in spintronic devices requires electrical manipulation of spin…
In this work we present an in-memory computing platform based on coupled VO2 oscillators fabricated in a crossbar configuration on silicon. Compared to existing platforms, the crossbar configuration promises significant improvements in…
Neuromorphic vision sensors require efficient real-time pattern recognition, yet conventional architectures struggle with energy and latency constraints. Here, we present a novel in-situ spatiotemporal sequence detector that leverages…
We propose a semi-suspended device structure and construct nanogapped, hysteresis-free field-effect transistors (FETs), based on the van der Waals stacking technique. The structure, which features a semi-suspended channel above a…
Van der Waals (vdW) semiconductors are attractive for highly scaled devices and heterogeneous integration since they can be isolated into self-passivated, two-dimensional (2D) layers that enable superior electrostatic control. These…
The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find…
The intrinsic spin-dependent transport properties of two types of lateral VS2|MoS2 heterojunctions are systematically investigated using first-principles calculations, and their various nanodevices with novel properties are designed. The…