Effect of Electron-Phonon Coupling on Thermal Transport across Metal-Nonmetal Interface - A Second Look

The effect of electron-phonon (e-ph) coupling on thermal transport across metal-nonmetal interfaces is yet to be completely understood. In this paper, we use a series of molecular dynamics (MD) simulations with e-ph coupling effect included by Langevin dynamics to calculate the thermal conductance at a model metal-nonmetal interface. It is found that while e-ph coupling can present additional thermal resistance on top of the phonon-phonon thermal resistance, it can also make the phonon-phonon thermal conductance larger than the pure phonon transport case. This is because the e-ph interaction can disturb the phonon subsystem and enhance the energy communication between different phonon modes inside the metal. This facilitates redistributing phonon energy into modes that can more easily transfer energy across the interfaces. Compared to the pure phonon thermal conduction, the total thermal conductance with e-ph coupling effect can become either smaller or larger depending on the coupling factor. This result helps clarify the role of e-ph coupling in thermal transport across metal-nonmetal interface

Reference-less complex wavefields characterization with a high-resolution wavefront sensor

Wavefront sensing is a widely-used non-interferometric, single-shot, and quantitative technique providing the spatial-phase of a beam. The phase is obtained by integrating the measured wavefront gradient. Complex and random wavefields intrinsically contain a high density of singular phase structures (optical vortices) associated with non-conservative gradients making this integration step especially delicate. Here, using a high-resolution wavefront sensor, we demonstrate experimentally a systematic approach for achieving the complete and quantitative reconstruction of complex wavefronts. Based on the Stokes' theorem, we propose an image segmentation algorithm to provide an accurate determination of the charge and location of optical vortices. This technique is expected to benefit to several fields requiring complex media characterization.Comment: 7 page

Chemostratigraphy, Mineral Distributions and Water Chemistry Analysis of the Green River Formation, Piceance Basin, Northwestern Colorado

The Eocene Green River Formation (GRF) in the Piceance Basin of Colorado is estimated to contain the largest oil shale deposits in the world and is a well-documented example of a lacustrine depositional system. In addition, the quantities of mineral resources in the oil shale, like nahcolite (NaHCO3) and dawsonite (NaAl(CO3)(OH)2) deposits, are of potential economic value. Detailed geochemical and mineralogical analysis across the basin can be critical to understanding the depositional environment, sedimentary processes and water-chemistry evolution in the basin. Quantitative geochemical data for the GRF were collected by Inductively Coupled Plasma Optical Emission Spectroscopy and Mass Spectrometry (ICP-OES-MS) as part of this study. The basin margin was represented by samples from the Douglas Pass area and the basin center area was characterized by samples of cores from the Shell 23X-2 and John Savage 24-1 wells at the U.S. Geological Survey Core Research Center. Outcrop and core samples were taken based on observed changes of sedimentary structures and lithofacies from the full stratigraphic sections. Major elements and element groups, (Si, Al, K, Ti), (Ca, Mg), Na, and P were used as proxies for clastic influx, carbonate precipitation, salinity and paleo-productivity, respectively. Trace metal elements (As, Mo, U, Cu, Zn) were used primarily to characterize the redox conditions of Lake Uinta. The changes of these major & trace elements in different lake stages, indicate the variations of the sedimentary components and processes in the lake development. The distinctions between the basin margin and the basin center, in terms of clastic input, salinity, carbonate, paleo-productivity, redox condition and total organic carbon (TOC), support the model of a permanently stratified lake through most of the depositional interval. The detailed geochemistry from this study indicates that Na became elevated earlier in portions of the basin margin than in the deeper basin. II During the early stage of lake expansion, the salinity may have been elevated first in the shallow basin margin, because of more efficient evaporation, which then elevated salinity in the basin center through transport of saline density currents. Period IV transition metal elements show only local occurrence of high enrichment, but analysis of Fe/Al ratios suggests that the low enrichments may be related to source rocks depleted in mafic constituents. Hierarchical clustering analysis (HCA) on these major & trace elements generated 5 chemofacies when integrating all datasets, which represent 1) carbonate facies (high Ca, Mg, Sr and Mn); 2) siliciclastic facies (high Si, Al, K, Ti, Zr, Nb, and P); 3) high TOC with high redox proxies (S, As, Mo, and Cu, etc); 4) saline facies (high Na); 5) mixed carbonate and siliciclastic facies (moderate-high in Ca, Mg, Sr, Mn and Si, K). The chemofacies derived from geochemical data further clarify the depositional environment and sedimentary processes across the basin and provide new perspective on the evolutionary history of the lake. The general coherency of period IV transition metal enrichments/depletions in most chemofacies suggests that, despite lower overall abundances, these elements do reflect the influence of redox conditions in the basin center and the basin margin. In addition, the distributions of key minerals in the GRF of the Piceance Basin reflect spatial and temporal variations in water chemistry in the paleolake. Mineral stability diagrams generated by thermodynamic modeling constrain the water chemistry under which those minerals were formed. The important minerals identified in the system include analcime, illite, dawsonite, nahcolite and albite/K-feldspar. Based on the mineral stability diagrams, the water chemistry can be defined in terms of silica activity, alkalinity, salinity and CO2 concentration. The Na concentration from the dawsonite and nahcolite stability field can reach 58,000 ppm under hypersaline conditions

Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning

Evaluation of a document summarization system has been a critical factor to impact the success of the summarization task. Previous approaches, such as ROUGE, mainly consider the informativeness of the assessed summary and require human-generated references for each test summary. In this work, we propose to evaluate the summary qualities without reference summaries by unsupervised contrastive learning. Specifically, we design a new metric which covers both linguistic qualities and semantic informativeness based on BERT. To learn the metric, for each summary, we construct different types of negative samples with respect to different aspects of the summary qualities, and train our model with a ranking loss. Experiments on Newsroom and CNN/Daily Mail demonstrate that our new evaluation method outperforms other metrics even without reference summaries. Furthermore, we show that our method is general and transferable across datasets.Comment: Long Paper in EMNLP 202

MMP-DCD-CV based Sparse Channel Estimation Algorithm for Underwater Acoustic Transform Domain Communication System

In this paper, we propose a computationally efficient multipath matching pursuit (MMP) channel estimation algorithm for underwater acoustic (UWA) transform domain communication systems (TDCSs). The algorithm, referred to as the MMP-DCD-CV algorithm, is based on the dichotomous coordinate descent (DCD) iterations and cross validation (CV). The MMP-DCD-CV sparse channel estimator in each iteration searches for multiple promising path candidates most relevant to a residual vector and chooses the best candidate. The DCD iterations are used to solve the corresponding least squares problem with low complexity and numerical stability. The CV provides a stopping criterion of the algorithm without a priori information on the channel sparsity and noise level and examines whether the algorithm overfits its data, thus improving the estimation accuracy. The performance of the proposed algorithm is evaluated under simulated sparse UWA channels. The numerical results show that the algorithm achieves better performance than the original MMP algorithm, has lower complexity, and does not require prior knowledge on the channel sparsity and noise level. We also propose an UWA TDCS with sparse channel estimation based on the proposed MMP-DCD-CV algorithm. The proposed UWA communication system is tested by the Waymark simulator, providing the virtual signal transmission in the UWA channel, with a measured Sound Speed Profile and bathymetry. Numerical results demonstrate that the UWA TDCS with the proposed sparse channel estimator offers considerable improvement in system performance compared to other TDCS schemes