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Physical models of Ge energy band structure and material loss were implemented in LASTIP(TM), a 2D simulation tool for edge emitting laser diodes. The model calculation is able to match experimental data available. Important design…

The continuous shift of computational bottlenecks to the memory access and data transfer, especially for AI applications, poses the urgent needs of re-engineering the computer architecture fundamentals. Many edge computing applications,…

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of…

We report novel graphene nanoribbon (GNR)/semiconductor nanowire (SNW) heterojunction light-emitting diodes (LEDs) for the first time. The GNR and SNW have a face-to-face contact structure, which has the merit of bigger active region. ZnO,…

A trend towards energy-efficiency, security and privacy has led to a recent focus on deploying DNNs on microcontrollers. However, limits on compute and memory resources restrict the size and the complexity of the ML models deployable in…

The activity and stability of a platinum nanoparticle (NP) is not only affected by its size but additionally depends on its shape. To this end, simulations can identify structure-property relationships to make a priori decisions on the most…

Graphene nano-ribbons, GNRs, are promising channel materials for next-generation ultra-miniaturised devices due to their exceptional electrical and thermal properties which arise from their atomic thickness, as well as their ability to have…

Radiation damage in structural materials is a major challenge for advanced nuclear energy systems, and niobium is of particular interest due to its high melting point, mechanical strength, and corrosion resistance. To better understand its…

Realizing today's cloud-level artificial intelligence functionalities directly on devices distributed at the edge of the internet calls for edge hardware capable of processing multiple modalities of sensory data (e.g. video, audio) at…

It is known that the figure of merit ($ZT$) of thin nanowires can be significantly enhanced at room temperature due to the reduction of phonon thermal conductance arising from the increase of boundary scattering of phonons. It is expected…

The AlGaAs material platform has been intensively used to develop nonlinear photonic devices on-a-chip, thanks to its superior nonlinear optical properties. We propose a new AlGaAs waveguide geometry, called half-core etched, which…

We present the design of ATJ graphite rods developed for ablation experiments under high heat flux (up to 50 MW/m2) in the lower divertor of the DIII-D tokamak [1], a magnetic plasma confinement device. This work is motivated by the need to…

Newest developments in nuclear fission and fusion technology as well as planned long-distance space missions demand novel materials to withstand harsh, irradiative environments. Radiation-induced hardening and embrittlement are a concern…

Carbon nanowall (CNW) is a two dimensional graphitic nanostructures with many potential applications like field emission, catalyst support for fuel cell and negative electrode for batteries. CNWs were grown here on Si substrates by plasma…

Finite state machines (FSMs) regulate sequential circuits, including access to sensitive information and privileged CPU states. Courtesy of contemporary research on laser attacks, laser-based fault injection (LFI) is becoming even more…

Resistive random-access memory (ReRAM)-based processing-in-memory (PIM) architecture is an attractive solution for training Graph Neural Networks (GNNs) on edge platforms. However, the immature fabrication process and limited write…

Tunneling field-effect transistors (FETs) have been intensely explored recently due to its potential to address power concerns in nanoelectronics. The recently discovered graphene nanoribbon (GNR) is ideal for tunneling FETs due to its…

Spiking Neural Networks (SNNs) can unleash the full power of analog Resistive Random Access Memories (RRAMs) based circuits for low power signal processing. Their inherent computational sparsity naturally results in energy efficiency…

Semiconductor nanowire field-effect transistors represent a promising platform for the development of room-temperature (RT) terahertz (THz) frequency light detectors due to the strong nonlinearity of their transfer characteristics and their…

In this era of machine learning models, their functionality is being threatened by adversarial attacks. In the face of this struggle for making artificial neural networks robust, finding a model, resilient to these attacks, is very…