Related papers: Prediction of Fluorescence Quantum Yields using th…
This work deals with the inference of catalytic recombination parameters from plasma wind tunnel experiments for reusable thermal protection materials. One of the critical factors affecting the performance of such materials is the…
Here is presented the calculation of the dynamic electrical conductivity of fully ionized, strongly coupled plasmas as a function of the external electric field frequency $\omega$. The calculations are based on the the formula for the…
Separated flow transition is a very popular phenomenon in gas turbines, especially low-pressure turbines (LPT). Low-fidelity simulations are often used for gas turbine design. However, they are unable to predict separated flow transition…
When measuring diameters of partially resolved sources often a technique called gaussian deconvolution is used. This technique yields a gaussian diameter which subsequently has to be multiplied with a conversion factor to obtain the true…
An extension to the classical FPV model is developed for transcritical real-fluid combustion simulations in the context of finite volume, fully compressible, explicit solvers. A double-flux model is developed for transcritical flows to…
Accurate phase diagram calculation from molecular dynamics requires systematic treatment and convergence of statistical averages. In this work we propose a Gaussian process regression based framework for reconstructing the free energy…
Finite-temperature calculations are relevant for rationalizing material properties yet they are computationally expensive because large system sizes or long simulation times are typically required. Circumventing the need for performing many…
We report in this paper electro-optical results on InGaN/GaN based green micro light-emitting diodes ({\mu}LEDs). Current light-voltage measurements reveal that the external quantum efficiency (EQE) behavior versus charge injection does not…
In industrial and environmental monitoring, achieving real-time and precise fluid flow measurement remains a critical challenge. This study applies linear quantization in FPGA-based soft sensors for fluid flow estimation, significantly…
We present the Empirical Dust Attenuation (EDA) framework -- a flexible prescription for assigning realistic dust attenuation to simulated galaxies based on their physical properties. We use the EDA to forward model synthetic observations…
Used extensively in sensing applications, the application of solution-state electrochemiluminescent devices (ECLDs) in lighting and displays has been constrained by their low luminance and short operational lifetime. Here, we report a…
Fluctuations in Lyman-$\alpha$ (Ly$\alpha$) forest transmission towards high-$z$ quasars are partially sourced from spatial fluctuations in the ultraviolet background (UVB), the level of which are set by the mean free path of ionizing…
Accurate determination of qubit parameters is critical for the successful implementation of quantum information and computation applications. In solid state systems, the parameters of individual qubits vary across the entire system,…
Donor-acceptor type compounds are an important category of organic materials that show properties suitable for light emission applications. To achieve a full understanding of the mechanism of thermally activated delayed fluorescence (TADF)…
We use first-principles calculations based on many-body perturbation theory to investigate the near-edge electronic and optical properties of \b{eta}-Ga2O3. The fundamental band gap is indirect, but the minimum direct gap is only 29 meV…
Biochemical signal transduction, a form of molecular communication, can be modeled using graphical Markov channels with input-modulated transition rates. Such channel models are strongly non-Gaussian. In this paper we use a linear noise…
The cumulant expansion is a powerful approach for including correlation effects in electronic structure calculations beyond the GW approximation. However, current implementations are incomplete since they ignore terms that lead to partial…
Machine learning models are exceptionally effective in capturing complex non-linear relationships of high-dimensional datasets and making accurate predictions. However, their intrinsic ``black-box'' nature makes it difficult to interpret…
We develop numerical methods for reaction-diffusion systems based on the equations of fluctuating hydrodynamics (FHD). While the FHD formulation is formally described by stochastic partial differential equations (SPDEs), it becomes similar…
A model recently proposed for the calculation of air-fluorescence yield excited by electrons is revisited. Improved energy distributions of secondary electrons and a more realistic Monte Carlo simulation including some additional processes…