Related papers: A scheme for simulating multi-level phase change p…
This paper deals with the empirical validation of a building thermal model using a phase change material (PCM) in a complex roof. A mathematical model dedicated to phase change materials based on the heat apparent capacity method was…
In-memory computing (IMC) is an emerging non-von Neumann paradigm that leverages the intrinsic physics of memory devices to perform computations directly within the memory array. Among the various candidates, phase-change memory (PCM) has…
Chalcogenide phase-change materials (PCMs) show a significant contrast in optical reflectivity and electrical resistivity upon crystallization from the amorphous phase and are leading candidates for non-volatile photonic and electronic…
In this research, atomistic molecular dynamics simulations are combined with mesoscopic phase-field computational methods in order to investigate phase-transformation in polycrystalline Aluminum microstructure. In fact, microstructural…
Integrated photonic devices have become pivotal elements across most research fields that involve light-based applications. A particularly versatile category of this technology are programmable photonic integrated processors, which are…
Metasurfaces allow for the spatiotemporal variation of amplitude, phase, and polarization of optical wavefronts. Implementation of active tunability of metasurfaces promises compact flat optics capable of reconfigurable wavefront shaping.…
Chalcogenide material-based integrated photonic devices have garnered widespread attention due to their unique wideband transparency. Despite their recognized CMOS compatibility, the fabrication of these devices relies predominantly on…
Optical metasurfaces composed of metallic or dielectric scatterers (meta-atoms) promise a powerful way of tailoring light-matter interactions. Phase-change materials (PCMs) are prime candidates for non-volatile resonance tuning of…
Fast and reversible phase transitions in chalcogenide phase-change materials (PCMs), in particular, Ge-Sb-Te compounds, are not only of fundamental interests, but also make PCMs based random access memory (PRAM) a leading candidate for…
In this thesis, we propose to tackle this important issue by designing and realizing a novel nano-optical device based on the use of a photonic crystal (PC) structure to generate an efficient coupling between the external source and a NA.…
Chiral nanostructures offer the ability to respond to the vector nature of a light beam at the nanoscale. While naturally chiral materials offer a path towards scalability, engineered structures offer a path to wavelength tunability through…
Phase change materials (PCMs) are well-known for their reversible and rapid switching between crystalline and amorphous phases through thermal excitations mediated by strong electrical or laser pulses. This crystal-to-amorphous transition…
Modern-day computers use electrical signaling for processing and storing data which is bandwidth limited and power-hungry. These limitations are bypassed in the field of communications, where optical signaling is the norm. To exploit…
Phase change materials (PCMs) have gained a tremendous interest as a means to actively tune nanophotonic devices through the large optical modulation produced by their amorphous to crystalline reversible transition. Recently, materials such…
The emergent photoactive materials through photochemistry make it possible to directly convert photon energy to mechanical work. There is much recent work in developing appropriate materials and a promising new system is semi-crystalline…
Optical phase change materials (O-PCMs), a unique group of materials featuring drastic optical property contrast upon solid-state phase transition, have found widespread adoption in photonic switches and routers, reconfigurable meta-optics,…
In the present article, performance of a glazed photovoltaic thermal system integrated with phase change materials (GPVT/PCM) is numerically examined based on both energy and exergy viewpoints. The effect of PCM volumetric fraction and…
In this work, we develop a combined convolutional neural networks (CNNs) and finite element method (FEM) to examine the effective thermal properties of composite phase change materials (CPCMs) consisting of paraffin and copper foam. In this…
The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but…
Identifying thermodynamic signatures of electronic phases, such as superconductivity, is challenging in low-dimensional materials due to strong fluctuations and low probing volume. Spectroscopic methods are often used to identify new bulk…