相关论文: Deep Neural Network for Phonon-Assisted Optical Sp…
An array of DEPFET pixels is one of several concepts to implement an active pixel sensor. Similar to PNCCD and SDD detectors, the typically 0.45 mm thick silicon sensor is fully depleted by the principle of sideward depletion. They have…
We present a comprehensive first-principles investigation of the structural, electronic, optical, and thermodynamic properties of BeX compounds (X = S, Se, Te) under hydrostatic pressures ranging from 0 to 10 GPa. Calculations were…
While using first-principles-based Boltzmann transport equation approach to predict the thermal conductivity of crystalline semiconductor materials has been a routine, the validity of the approach is seldom tested for high-temperature…
A machine-learning non-contact method to determine the temperature of a laser gain medium via its laser emission with a trained few-layer neural net model is presented. The training of the feed-forward Neural Network (NN) enables the…
The discovery of superconductivity at 203K in SH$_3$ is an important step toward higher values of $T_c$. Predictions based on state-of-the-art DFT for the electronic structure, including one preceding experimental confirmation, showed the…
We report on the realization of a high sensitivity RF noise measurement scheme to study small current fluctuations of mesoscopic systems at milliKelvin temperatures. The setup relies on the combination of an interferometric ampli- fication…
A deep neural network (DNN) model consisting of two hidden layers was proposed for predicting the immediate environments of specific atoms based on X-ray absorption near-edge spectra (XANES). The output layer of the DNN can be adjusted to…
The frequency-dependent optical spectrum is pivotal for a broad range of applications, from material characterization to optoelectronics and energy harvesting. Data-driven surrogate models, trained on density functional theory (DFT) data,…
We compute the transient dynamics of phonons in contact with high energy "hot" charge carriers in 12 polar and non-polar semiconductors, using a first-principles Boltzmann transport framework. For most materials, we find that the decay in…
The ability to control and modify infrared excitations in condensed matter is of both fundamental and application interests. Here we explore a system supporting low-energy excitations, in particular, mid-infrared localized plasmon modes and…
X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be…
Long-lived, high-frequency phonons are valuable for applications ranging from optomechanics to emerging quantum systems. For scientific as well as technological impact, we seek high-performance oscillators that offer a path towards…
The process of obtaining high-resolution images from single or multiple low-resolution images of the same scene is of great interest for real-world image and signal processing applications. This study is about exploring the potential usage…
We present a deep learning approach using an optical neural network to predict the fundamental modal indices $n_{\rm{eff}}$ in a silicon (Si) channel waveguide. We use three inputs, e.g., two geometric parameters and one material property,…
Interfaces impede heat flow in micro/nanostructured systems. Conventional theories for interfacial thermal transport were derived based on bulk phonon properties of the materials making up the interface without explicitly considering the…
Using transient absorption (TA) microscopy as a hot electron thermometer we show disorder-assisted acoustic-phonon supercollisions (SCs) best describes the rate-limiting relaxation step in graphene over a wide range of lattice temperatures…
Ab initio simulations are capable of providing detailed information of material behavior at the nanoscale. Simulating experimentally relevant situations is, however, often computationally intense. Using hybrid approaches between ab initio…
We present a measurement of phonon propagation in a silicon wafer utilizing an array of frequency-multiplexed superconducting resonators coupled to a single transmission line. The electronic readout permits fully synchronous array sampling…
Understanding the coordinated activity underlying brain computations requires large-scale, simultaneous recordings from distributed neuronal structures at a cellular-level resolution. One major hurdle to design high-bandwidth,…
At Argonne National Laboratory, we are developing hard X-ray (2 to 20 keV) Transition Edge Sensor (TES) arrays for beamline science. The significantly improved energy resolution provided by superconducting detectors compared to…