Performance Analysis of Micro-Raman Spectroscopy Models for Thermal Conductivity Calculation

Micro-Raman spectroscopy has been preferred recently to measure the thermal conductivity of thin-films due to its nondestructive and non-contact nature. However, the thermal size effects originating from both localized heat generation from Raman laser and phonon scattering at boundaries may cause erroneous estimation of the thermal conductivities with the current approach. In this study, the gray phonon Boltzmann transport equation (BTE) is solved to improve the results of micro-Raman thermal conductivity measurements. Due to the frequency independence of single phonon mode in the gray BTE model, our method stays ahead of most theoretical methods in calculation time while giving adequate agreement with the literature data. The improved thermal conductivities are evaluated at various laser powers and focal lengths. Subsequently, the values of thermal conductivities are compared with a simple slab model in which the deduction of thermal conductivity in sub-micron thicknesses is calculated using reduced heat flux through the slab resulting from phonon directional energy densities. The results show that subsequent errors are present in measuring the thermal conductivity of relatively thick, thin films with this technique which are noticed by comparing with the simple slab model. Finally, a virtual micro-Raman thermography experiment is developed, and its validity is verified by the same slab model.

DFT Insights into the Hydrodenitrogenation and Ring-Opening of Indole on an M (M = Ni, Pt, Ni–Pt) Slab Model

Density functional theory (DFT) calculation has been used to study the hydrodenitrogenation (HDN) and ring-opening of indole on an M (M = Ni, Pt, Ni–Pt) slab surface. The possible reaction pathway of indole hydrogenation has been investigated in order to reveal the bimetallic synergistic effects of an M slab surface. Compared to the mechanism of indole hydrogenation on an M slab surface, it was found that a PtNi(111) surface favors indole hydrogenation. According to the results of DFT calculation, it suggests that the bimetallic effect of the M surface plays an important role in indole hydrogenation.

Designing a PID controller for slab temperature control system

The problem of heating slab is a very important and highly applicable problem in the material processing industry. This paper presents a method to design a PID controller according to the characteristic polynomial method to control the temperature for slab based on the transfer function model. The parameters of the PID controller are determined based on the parameters of the slab model, the heating furnace model, the converter model. The simulation results show that: the PID controller is capable of controlling the temperature of the slab to the desired temperature without over-adjusting.

Dielectric sea-ice properties examined by GNSS reflectometry: Findings of the MOSAiC expedition

<p>The dielectric properties of sea ice differ significantly from the open-water surface when we consider the L-band frequency range of GNSS signals. In contrast to water, the signal’s penetration into sea ice can reach several decimeters depending on properties like salinity, temperature and thickness. Exploiting these different dielectric properties is a key to use GNSS for sea-ice remote sensing. For this purpose, GNSS reflectometry measurements have been conducted over the Arctic Ocean during the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). A combined receiver setup was used that allows the here described reflectometry study and another study for atmosphere sounding. The setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted during nine months of the expedition with the Arctic sea ice.</p><p>Here, an initial study is presented that focuses on the expedition’s first leg in autumn 2019 when the ship started drifting at about 85°N to 87°N in the Siberian Sector of the Arctic. Profiles of sea-ice reflectivity are derived with daily resolution considering reflection data recorded at left-handed (LH) and right-handed (RH) circular polarization. Respective model predictions of reflectivity are assuming a sea-ice bulk medium or a sea-ice slab. The later allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm the reflectivity contrast (about 10 dB) between sea ice and water. The particularly low level of LH reflectivity in the late observation period (December 2019) indicates the presence of low-saline multiyear (MY) ice. A bias due to snow accumulating on the ice surface may occur. A snow-extended reflection model, driven by additional snow data, can help in future for clarification.</p><p>Anomalies of observed reflectivity with respect to bulk model predictions are especially obvious at lowest elevation angles. According to the model, the slope of profiles at low elevations is about 1.0 to 1.2 dB/°. The observation shows significantly lower values (< 0.5 dB/°) including negative slopes. A comparison of LH results with the ice slab model provides clarification. The anomalies are induced by signal penetration leading to interference pattern of reflections from the ice’s surface and bottom. Slope retrievals quantify the anomaly and allow a coarse estimation of the mean sea-ice temperature (about -10°C in December 2019) based on the slab model predictions. Further investigations are needed to better understand sea-ice reflectivity at RH polarization. RH profiles show a response to sea ice and features at low elevation angles that cannot be explained by current reflection models.</p><p>As a conclusion, GNSS reflectometry is sensitive to dielectric sea-ice properties. Estimates of ice type/salinity and temperature are reported based on LH observation data. These findings will be exploited to further strengthen the application of GNSS signals for sea-ice remote sensing. Future studies on GNSS observations from ships and satellites are anticipated.</p>

Slab segmentation and continental collision: reconstructing slab deformation in South-East Iran during the closure of Neotethys.

<p>As the Arabian continent converged with Eurasia during the closure of Neotethys, the subducting slab of oceanic lithosphere deformed and tore into segments. In the Makran subduction zone, ongoing rollback and extension within a convergent setting was accommodated by subduction zone bounding strike-slip systems. A 3D slab model for the subducted lithosphere in the Makran region was constructed using <em>eQuakes</em> and <em>SKUA-GOCAD</em>, based on the UU-P07 tomographic velocity model, and the available records of modern seismic activity. Seismotectonic analysis suggests remnants of subducted slab within the adjacent collision zone influence active tectonics. Slab floating and analysis of the morphology of the model suggests potential sites of slab tearing, which are evaluated against the record of regional magmatism. The slab model also allows for the examination of proposed models for subduction against the magnitude and location of reconstructed lithosphere.</p>

Experimental Tests of the Vector II Slab in Field Conditions, Slab and Strip Model

Vector II slab was tested on a natural scale (a slab with a dimension of 6.30 × 6.30 m) and a strip 6.30 m long and 1.20 m wide. The Vector II slab is built by precast panel 60 cm wide, 4 cm thick and 14-20 cm thick concrete overtopping on the construction site. The main purpose of the slab tests on a natural scale was to observe the “faulting” effect and temporary deflections. During the tests, the displacements in the area of the panel joints in the middle of the slab span were recorded. The maximum difference in displacement between adjacent panels of the slab model was 0.16 mm, and the vertical displacement was 1.9 mm. The strip model had no cracks that could indicate a interface cracks between the precast element and the concrete overlay. After completion of the field tests, the load was left on the slab model to verify long-term effects.

Many Mixture Components, Oh My: Extending the Spike and Slab to Bayesian Hypothesis Testing with Multinoulli Indicators

Bayesian analysis has become increasingly popular in the social-behavioral sciences. Because hypothesis testing has an important place on the mantel of psychological inquiry, an active area of research has been developing Bayesian analogs for commonly used frequentist tests.However, a major hurdle to this endeavour is computing the necessary ingredients, that is the marginal likelihood, resulting in the use of inflexible analytic solutions or approaches that avoid its computation altogether. In a similar spirit, I extend the spike and slab model, widely considered the gold standard for variable selection, to allow for flexible hypothesis testing. This is accomplished by employing multinoulli indicator variables, as opposed to Bernoulli, which results in a general solution for testing any number of hypotheses that correspond to components of a mixture prior distribution. In a motivating example, I first describe the qualitative relation of the proposed methodology to a popular Bayesian $t$-test, including extensions for one-sided and interval hypothesis tests. With the foundation laid, I proceed to a more complex example wherein themultinoulli spike and slab is used to model a correlation matrix, with the goal of testing joint hypotheses. This example investigated the associations among experimental effects from three cognitive inhibition tasks ($N = 121$), where the theoretical expectation is that they will be positively correlated. To the contrary, the results revealed that the null model of no associations better predicted the observed data than the positive effects model.The important topics of model selection and Bayesian model averaging are also discussed. I end with ideas to further extend the multinoulli spike and slab model. In addition, detailed {\tt R} code is provided that can serve as the building block for developing custom Bayesian models.