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Phaseless Auxiliary-Field Quantum Monte Carlo (ph-AFQMC) has recently emerged as a promising method for the production of benchmark-level simulations of medium to large-sized molecules, due to its accuracy and favorable polynomial scaling…
This study presents a theoretical investigation of the physical mechanisms governing small signal capacitance in ferroelectrics, focusing on Hafnium Zirconium Oxide. Utilizing a time-dependent Ginzburg Landau formalism-based 2D multi-grain…
As computing power demands continue to grow, superconducting electronics present an opportunity to reduce power consumption by increasing the energy efficiency of digital logic and memory. A key milestone for scaling this technology is the…
The discovery of ferroelectric properties of binary oxides revitalized the interest in ferroelectrics and bridged the scaling gap between the state-of-the-art semiconductor technology and ferroelectric memories. However, before hitting the…
Superconductor electronics (SCE) is a promising complementary and beyond CMOS technology. However, despite its practical benefits, the realization of SCE logic faces a significant challenge due to the absence of dense and scalable…
Neuromorphic computing aims to mimic the architecture and the information processing mechanisms of the mammalian brain, appearing as the only avenue that offers significant energy savings compared to the standard digital computers.…
We study the structural and electronic properties of various hafnium sub-oxides HfzO from z = 9 to z = 0.5, by ab initio simulation using Density Functional Theory. The stability of these sub-oxides is studied against monoclinic HfO2. The…
The computational design of heteroatom-doped organic dyes for dye-sensitized solar cells (DSSCs) remains challenging, as predictive methods must accurately describe long-range charge-transfer (CT) excitations while remaining computationally…
Discotic liquid crystalline (DLC) charge transfer (CT) complexes combine visible light absorption and rapid charge transfer characteristics within the CT complex, being favorable properties for photovoltaic (PV) applications. We present a…
Analog in-memory computing is an emerging paradigm designed to efficiently accelerate deep neural network workloads. Recent advancements have focused on either inference or training acceleration. However, a unified analog in-memory…
This paper presents the design and analysis of a wearable CMOS biosensor with three different designs of energy-resolution scalable time-based resistance to digital converters (RDC), targeted towards either minimizing the energy/conversion…
Ferroelectric field-effect transistors (FeFET) with two-dimensional (2D) semiconductor channels are promising low-power, embedded non-volatile memory (NVM) candidates for next-generation in-memory computing. However, the performance of…
This paper proposes a novel integrated multiport bidirectional dc-dc converter to interface the battery, the ultra-capacitor, the fuel cell, or other energy sources with the dc-link capacitor of the hybrid energy systems such as the hybrid…
The Hartree-Fock (HF) approximation with the charge-density-wave (CDW) instability is used to study the ground-state phase diagram of the spinless Falicov-Kimball model (FKM) extended by $f$-$f$ hopping in two and three dimensions. It is…
Reversible hydrogen incorporation was recently attested [N. Lu, $\textit{et al.}$, Nature $\textbf{546}$, 124 (2017)] in ${\text{SrCo}\text{O}_{2.5}}$, the brownmillerite phase (BM) of strontium cobalt oxide (SCO), opening new avenues in…
Combinatorial optimization problems (COPs) are crucial in many applications but are computationally demanding. Traditional Ising annealers address COPs by directly converting them into Ising models (known as direct-E transformation) and…
Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability in aggressively scaled semiconductor devices. Compute-in-memory (CIM) architectures…
Carrier-envelope phase (CEP) detection of ultrashort optical pulses and low-energy waveform field sampling have recently been demonstrated using direct time-domain methods that exploit optical-field photoemission from plasmonic…
The growth in data generation necessitates efficient data processing technologies to address the von Neumann bottleneck in conventional computer architecture. Memory-driven computing, which integrates non-volatile memory (NVM) devices in a…
In this work, we introduce a non-volatile heterogeneous quantum dot (QD) III-V/Al2O3/Si distributed feedback (DFB) laser exhibiting optical memristive behavior. The device operates in the O-band (~1300 nm) with a threshold current density…