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The kinematic Sunyaev--Zel'dovich (kSZ) effect induces a non-zero density-density-temperature bispectrum, which we can use to reconstruct the large-scale velocity field from a combination of cosmic microwave background (CMB) and galaxy density measurements, in a procedure known as ``kSZ velocity reconstruction''. This method has been forecast to constrain large-scale modes with future galaxy and CMB surveys, improving their measurement beyond what is possible with the galaxy surveys alone. Such measurements will enable tighter constraints on large-scale signals such as primordial non-Gaussianity, deviations from homogeneity, and modified gravity. In this work, we demonstrate a statistically significant measurement of kSZ velocity reconstruction for the first time, by applying quadratic estimators to the combination of the ACT DR6 CMB+kSZ map and the DESI LRG galaxies (with photometric redshifts) in order to reconstruct the velocity field. We do so using a formalism appropriate for the 2-dimensional projected galaxy fields that we use, which naturally incorporates the curved-sky effects important on the largest scales. We find evidence for the signal by cross-correlating with an external estimate of the velocity field from the spectroscopic BOSS survey and rejecting the null (no-kSZ) hypothesis at $3.8\sigma$. Our work presents a first step towards the use of this observable for cosmological analyses., Comment: 16 pages (main)+5 pages (Appendix); 13 figures (main) + 8 figures (appendix)

The U.S. Bureau of Labor Statistics projects that by the year 2029, the United States will lose a million jobs in the office and administrative support occupations because technology, automation, and artificial intelligence (AI) have the potential to substitute or replace the office and administrative functions performed by office workers. Despite the potential impact AI will have on office work and the important role office workers play in the American economy, we have limited knowledge of the state of the art research in office work at the intersection of emerging artificial intelligence technologies. In this study, we conducted a bibliometric analysis of the scholarly literature at the intersection of office work and artificial intelligence. We extracted literature sources from Compendex and Scopus databases and used VOSviewer for visualizing and quantifying our bibliometric analyses. Our findings from keywords analysis indicate that office automation, humans, human-computer interaction, and artificial intelligence occurred more frequently in the scholarly literature and had high link strengths. Keyword clusters from co-occurrence analysis indicate that intelligent buildings, robotics, and the internet of things are emerging topics in the office work domain. The two clusters related to ergonomics, worker characteristics, human performance, and safety indicate the types of human factors concerns that are more widely studied in office work settings. In summary, our findings on the state-of-the-art research in office work indicate that more studies have been conducted on smart buildings, robotics, and technology development for office work, compared to studies on office workers and their professional development., Comment: This work is being submitted to the IEEE for possible publication

Spatial variations in the cosmic electron density after reionization generate cosmic microwave background anisotropies via Thomson scattering, a process known as the ``patchy screening" effect. In this paper, we propose a new estimator for the patchy screening effect that is designed to mitigate biases from the dominant foreground signals. We use it to measure the cross-correlation between \textit{unWISE} galaxies and patchy screening, the latter measured by the Atacama Cosmology Telescope and \textit{Planck} satellite. We report the first detection of the patchy screening effect, with the statistical significance of the cross-correlation exceeding $7\sigma$. This measurement directly probes the distribution of electrons around these galaxies and provides strong evidence that gas is more extended than the underlying dark matter. By comparing our measurements to electron profiles extracted from simulations, we demonstrate the power of these observations to constrain galaxy evolution models. Requiring only the 2D positions of objects and no individual redshifts or velocity estimates, this approach is complementary to existing gas probes, such as those based on the kinetic Sunyaev-Zeldovich effect., Comment: See Schutt et al for a detailed comparison of patchy screening estimators. 17 pages with 8 figures

We systematically demonstrate the temperature-dependent thermal transport properties in crystalline Ge$_2$Sb$_2$Te$_5$via first-principles density functional theory-informed linearized Boltzmann transport equation. The investigation, covering a wide temperature range (30 K-600 K), reports the emergence of an unusual optical phonon-dominated thermal transport in crystalline Ge$_2$Sb$_2$Te$_5$. Further, a significant contribution of four-phonon scattering is recorded which markedly alters the lattice thermal conductivity. Therefore, the combined effect of cubic and quartic phonon anharmonicity is seen to navigate the underlying physical mechanism and open up intriguing phononic interactions in Ge$_2$Sb$_2$Te$_5$ at high temperature. Irrespective of three and four-phonon processes, Umklapp is seen to prevail over normal scattering events. Consequently, four-phonon scattering is found to notably reduce the lattice thermal conductivity of Ge$_2$Sb$_2$Te$_5$ to 28 $\%$ at room temperature and 42 $\%$ at higher temperature. This quartic anharmonicity further manifests in the breakdown of T$^{-1}$ scaling of thermal conductivity and challenges the idea of a universal lower bound to phononic thermal diffusivity at high temperature. The faster decay of thermal diffusivity compared to T$^{-1}$ is rationalized encompassing the quartic anharmonicity via a modified time scale. These results invoke better understanding and precision to the theoretical prediction of thermal transport properties of Ge$_2$Sb$_2$Te$_5$. Concomitantly, this also triggers the possibility to explore the manifestations of the lower bound of thermal diffusivity in materials possessing pronounced four-phonon scattering.

class_sz is a versatile and robust code in C and Python that can compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks (https://github.com/CLASS-SZ/notebooks). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage., Comment: to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

Observations of the millimeter sky contain valuable information on a number of signals, including the blackbody cosmic microwave background (CMB), Galactic emissions, and the Compton-$y$ distortion due to the thermal Sunyaev-Zel'dovich (tSZ) effect. Extracting new insight into cosmological and astrophysical questions often requires combining multi-wavelength observations to spectrally isolate one component. In this work, we present a new arcminute-resolution Compton-$y$ map, which traces out the line-of-sight-integrated electron pressure, as well as maps of the CMB in intensity and E-mode polarization, across a third of the sky (around 13,000 sq.~deg.). We produce these through a joint analysis of data from the Atacama Cosmology Telescope (ACT) Data Release 4 and 6 at frequencies of roughly 93, 148, and 225 GHz, together with data from the \textit{Planck} satellite at frequencies between 30 GHz and 545 GHz. We present detailed verification of an internal linear combination pipeline implemented in a needlet frame that allows us to efficiently suppress Galactic contamination and account for spatial variations in the ACT instrument noise. These maps provide a significant advance, in noise levels and resolution, over the existing \textit{Planck} component-separated maps and will enable a host of science goals including studies of cluster and galaxy astrophysics, inferences of the cosmic velocity field, primordial non-Gaussianity searches, and gravitational lensing reconstruction of the CMB., Comment: The Compton-y map and associated products will be made publicly available upon publication of the paper. The CMB T and E mode maps will be made available when the DR6 maps are made public

We present cosmological constraints from a gravitational lensing mass map covering 9400 sq. deg. reconstructed from CMB measurements made by the Atacama Cosmology Telescope (ACT) from 2017 to 2021. In combination with BAO measurements (from SDSS and 6dF), we obtain the amplitude of matter fluctuations $\sigma_8 = 0.819 \pm 0.015$ at 1.8% precision, $S_8\equiv\sigma_8({\Omega_{\rm m}}/0.3)^{0.5}=0.840\pm0.028$ and the Hubble constant $H_0= (68.3 \pm 1.1)\, \text{km}\,\text{s}^{-1}\,\text{Mpc}^{-1}$ at 1.6% precision. A joint constraint with CMB lensing measured by the Planck satellite yields even more precise values: $\sigma_8 = 0.812 \pm 0.013$, $S_8\equiv\sigma_8({\Omega_{\rm m}}/0.3)^{0.5}=0.831\pm0.023$ and $H_0= (68.1 \pm 1.0)\, \text{km}\,\text{s}^{-1}\,\text{Mpc}^{-1}$. These measurements agree well with $\Lambda$CDM-model extrapolations from the CMB anisotropies measured by Planck. To compare these constraints to those from the KiDS, DES, and HSC galaxy surveys, we revisit those data sets with a uniform set of assumptions, and find $S_8$ from all three surveys are lower than that from ACT+Planck lensing by varying levels ranging from 1.7-2.1$\sigma$. These results motivate further measurements and comparison, not just between the CMB anisotropies and galaxy lensing, but also between CMB lensing probing $z\sim 0.5-5$ on mostly-linear scales and galaxy lensing at $z\sim 0.5$ on smaller scales. We combine our CMB lensing measurements with CMB anisotropies to constrain extensions of $\Lambda$CDM, limiting the sum of the neutrino masses to $\sum m_{\nu} < 0.13$ eV (95% c.l.), for example. Our results provide independent confirmation that the universe is spatially flat, conforms with general relativity, and is described remarkably well by the $\Lambda$CDM model, while paving a promising path for neutrino physics with gravitational lensing from upcoming ground-based CMB surveys., Comment: 32 pages, 17 figures, replaced with version accepted in ApJ (Feb 2024). Cosmological likelihood data and mass maps are public here: https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html ; likelihood software is here: https://github.com/ACTCollaboration/act_dr6_lenslike . Also see companion papers Qu et al and MacCrann et al

We present new measurements of cosmic microwave background (CMB) lensing over $9400$ sq. deg. of the sky. These lensing measurements are derived from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) CMB dataset, which consists of five seasons of ACT CMB temperature and polarization observations. We determine the amplitude of the CMB lensing power spectrum at $2.3\%$ precision ($43\sigma$ significance) using a novel pipeline that minimizes sensitivity to foregrounds and to noise properties. To ensure our results are robust, we analyze an extensive set of null tests, consistency tests, and systematic error estimates and employ a blinded analysis framework. The baseline spectrum is well fit by a lensing amplitude of $A_{\mathrm{lens}}=1.013\pm0.023$ relative to the Planck 2018 CMB power spectra best-fit $\Lambda$CDM model and $A_{\mathrm{lens}}=1.005\pm0.023$ relative to the $\text{ACT DR4} + \text{WMAP}$ best-fit model. From our lensing power spectrum measurement, we derive constraints on the parameter combination $S^{\mathrm{CMBL}}_8 \equiv \sigma_8 \left({\Omega_m}/{0.3}\right)^{0.25}$ of $S^{\mathrm{CMBL}}_8= 0.818\pm0.022$ from ACT DR6 CMB lensing alone and $S^{\mathrm{CMBL}}_8= 0.813\pm0.018$ when combining ACT DR6 and Planck NPIPE CMB lensing power spectra. These results are in excellent agreement with $\Lambda$CDM model constraints from Planck or $\text{ACT DR4} + \text{WMAP}$ CMB power spectrum measurements. Our lensing measurements from redshifts $z\sim0.5$--$5$ are thus fully consistent with $\Lambda$CDM structure growth predictions based on CMB anisotropies probing primarily $z\sim1100$. We find no evidence for a suppression of the amplitude of cosmic structure at low redshifts, Comment: 45+22 pages, 50 figures. v2 matches with published version in ApJ. Cosmological likelihood data and lensing maps are here: https://lambda.gsfc.nasa.gov/product/act/actadv_prod_table.html ; likelihood software is here: https://github.com/ACTCollaboration/act_dr6_lenslike . Also see companion papers Madhavacheril et al and MacCrann et al

Extracting the CMB blackbody temperature power spectrum -- which is dominated by the primary CMB signal and the kinematic Sunyaev-Zel'dovich (kSZ) effect -- from mm-wave sky maps requires cleaning other sky components. In this work, we develop new methods to use large-scale structure (LSS) tracers to remove cosmic infrared background (CIB) and thermal Sunyaev-Zel'dovich (tSZ) contamination in such measurements. Our methods rely on the fact that LSS tracers are correlated with the CIB and tSZ signals, but their two-point correlations with the CMB and kSZ signals vanish on small scales, thus leaving the CMB blackbody power spectrum unbiased after cleaning. We develop methods analogous to delensing ($\textit{de-CIB}$ or $\textit{de-(CIB+tSZ)}$) to clean CIB and tSZ contaminants using these tracers. We compare these methods to internal linear combination (ILC) methods, including novel approaches that incorporate the tracer maps in the ILC procedure itself, without requiring exact assumptions about the CIB SED. As a concrete example, we use the $\textit{unWISE}$ galaxy samples as tracers. We provide calculations for a combined Simons Observatory and $\textit{Planck}$-like experiment, with our simulated sky model comprising eight frequencies from 93 to 353 GHz. Using $\textit{unWISE}$ tracers, improvements with our methods over current approaches are already non-negligible: we find improvements up to 20% in the kSZ power spectrum signal-to-noise ratio (SNR) when applying the de-CIB method to a tSZ-deprojected ILC map. These gains could be more significant when using additional LSS tracers from current surveys, and will become even larger with future LSS surveys, with improvements in the kSZ power spectrum SNR up to 50%. For the total CMB blackbody power spectrum, these improvements stand at 4% and 7%, respectively. Our code is publicly available at https://github.com/olakusiak/deCIBing., Comment: 23+29 pages, 6+18 figures; matches the version accepted for publication in PRD; code is available at https://github.com/olakusiak/deCIBing

The kinetic Sunyaev-Zel'dovich (kSZ) effect, i.e., the Doppler boost of cosmic microwave background (CMB) photons caused by their scattering off free electrons in galaxy clusters and groups with non-zero bulk velocity, is a powerful window on baryons in the universe. We present the first halo-model computation of the cross-power spectrum of the ``projected-field'' kSZ signal with large-scale structure (LSS) tracers. We compare and validate our calculations against previous studies, which relied on $N$-body-calibrated effective formulas rather than the halo model. We forecast results for CMB maps from the Atacama Cosmology Telescope (AdvACT), Simons Observatory (SO), and CMB-S4, and LSS survey data from the Dark Energy Survey, the Vera C.~Rubin Observatory (VRO), and \textit{Euclid}. In cross-correlation with galaxy number density, for AdvACT $\times$ \textit{unWISE} we forecast an 18$\sigma$ projected-field kSZ detection using data already in hand. Combining SO CMB maps and \textit{unWISE} galaxy catalogs, we expect a $62\sigma$ detection, yielding precise measurements of the gas density profile radial slopes. Additionally, we forecast first detections of the kSZ -- galaxy weak lensing cross-correlation with AdvACT $\times$ VRO/\textit{Euclid} (at 6$\sigma$) and of the kSZ -- CMB weak lensing cross-correlation with SO (at 16$\sigma$). Finally, $\approx 10-20$\% precision measurements of the shape of the gas density profile should be possible with CMB-S4 kSZ -- CMB lensing cross-correlation without using any external datasets.

Phonon hydrodynamics is an exotic phonon transport phenomenon that challenges the conventional understanding of diffusive phonon scattering in crystalline solids. It features a peculiar collective motion of phonons with various unconventional properties resembling fluid hydrodynamics, facilitating non Fourier heat transport. Hence, it opens up several new avenues to enrich the knowledge and implementations on phonon physics, phonon engineering, and micro and nanoelectronic device technologies. This review aims at covering a comprehensive development as well as the recent advancements in this field via experiments, analytical methods, and state-of-the-art numerical techniques. The evolution of the topic has been realized using both phenomenological and material science perspectives. Further, the discussions related to the factors that influence such peculiar motion, illustrate the capability of phonon hydrodynamics to be implemented in various applications. A plethora of new ideas can emerge from the topic considering both the physics and the material science axes, navigating towards a promising outlook in the research areas around phonon transport in non-metallic solids.

Large rotating machines, e.g., compressors, steam turbines, gas turbines, are critical equipment in many process industries such as energy, chemical, and power generation. Due to high rotating speed and tremendous momentum of the rotor, the centrifugal force may lead to flying apart of the rotor parts, which brings a great threat to the operation safety. Early detection and prediction of potential failures could prevent the catastrophic plant downtime and economic loss. In this paper, we divide the operational states of a rotating machine into normal, risky, and high-risk ones based on the time to the moment of failure. Then a cascade classifying algorithm is proposed to predict the states in two steps, first we judge whether the machine is in normal or abnormal condition; for time periods which are predicted as abnormal we further classify them into risky or high-risk states. Moreover, traditional classification model evaluation metrics, such as confusion matrix, true-false accuracy, are static and neglect the online prediction dynamics and uneven wrong-prediction prices. An Online Prediction Ability Index (OPAI) is proposed to select prediction models with consistent online predictions and smaller close-to-downtime prediction errors. Real-world data sets and computational experiments are used to verify the effectiveness of proposed methods.

We present the first detailed analysis of the connection between galaxies and their dark matter halos for the unWISE galaxy catalog -- a full-sky, infrared-selected sample built from WISE data, containing over 500 million galaxies. Using unWISE galaxy-galaxy auto-correlation and Planck CMB lensing-galaxy cross-correlation measurements down to 10 arcmin angular scales, we constrain the halo occupation distribution (HOD), a model describing how central and satellite galaxies are distributed within dark matter halos, for three unWISE} galaxy samples at mean redshifts $\bar{z} \approx 0.6$, $1.1$, and $1.5$. We constrain the characteristic minimum halo mass to host a central galaxy, $M_\mathrm{min}^\mathrm{HOD} = 1.83^{+0.41}_{-1.63} \times 10^{12} M_\odot/h$, $5.22^{+0.34}_{-4.80} \times 10^{12} M_\odot/h$, $6.60 ^{+0.30}_{-1.11} \times 10^{13} M_\odot/h$ for the unWISE samples at $\bar{z}\approx 0.6$, $1.1$, and $1.5$, respectively. We find that all three samples are dominated by central galaxies, rather than satellites. Using our constrained HOD models, we infer the effective linear galaxy bias for each unWISE sample, and find that it does not evolve as steeply with redshift as found in previous perturbation-theory-based analyses of these galaxies. We discuss possible sources of systematic uncertainty in our results, the most significant of which is the uncertainty on the galaxy redshift distribution. Our HOD constraints provide a detailed, quantitative understanding of how the unWISE galaxies populate the underlying dark matter halo distribution. These constraints will have a direct impact on future studies employing the unWISE galaxies as a cosmological and astrophysical probe, including measurements of ionized gas thermodynamics and dark matter profiles via Sunyaev-Zel'dovich and lensing cross-correlations.

The traditional production paradigm of large batch production does not offer flexibility towards satisfying the requirements of individual customers. A new generation of smart factories is expected to support new multi-variety and small-batch customized production modes. For that, Artificial Intelligence (AI) is enabling higher value-added manufacturing by accelerating the integration of manufacturing and information communication technologies, including computing, communication, and control. The characteristics of a customized smart factory are to include self-perception, operations optimization, dynamic reconfiguration, and intelligent decision-making. The AI technologies will allow manufacturing systems to perceive the environment, adapt to external needs, and extract the processed knowledge, including business models, such as intelligent production, networked collaboration, and extended service models. This paper focuses on the implementation of AI in customized manufacturing (CM). The architecture of an AI-driven customized smart factory is presented. Details of intelligent manufacturing devices, intelligent information interaction, and the construction of a flexible manufacturing line are showcased. The state-of-the-art AI technologies of potential use in CM, i.e., machine learning, multi-agent systems, Internet of Things, big data, and cloud-edge computing are surveyed. The AI-enabled technologies in a customized smart factory are validated with a case study of customized packaging. The experimental results have demonstrated that the AI-assisted CM offers the possibility of higher production flexibility and efficiency. Challenges and solutions related to AI in CM are also discussed., Comment: 21 pages, 12 figures

We study the effect of characteristic size variation on the phonon thermal transport in crystalline GeTe for a wide range of temperatures using the first-principles density-functional method coupled with the kinetic collective model approach. The characteristic size dependence of phonon thermal transport reveals an intriguing collective phonon transport regime, located in between the ballistic and the diffusive transport regimes. Therefore, systematic investigations have been carried out to describe the signatures of phonon hydrodynamics via the competitive effects between grain size and temperature. A characteristic nonlocal length associated with phonon hydrodynamics and a heat wave propagation length has been extracted. The connections between phonon hydrodynamics and these length scales are discussed in terms of the Knudsen number. Further, the scaling relation of thermal conductivity as a function of characteristic size in the intermediate size range emerges as a crucial indicator of the strength of the hydrodynamic behavior. A ratio concerning normal and resistive scattering rates has been employed to understand these different scaling relations, which seems to control the strength and prominent visibility of the collective phonon transport in GeTe. This systematic investigation emphasizes the importance of the competitive effects between temperature and characteristic size on phonon hydrodynamics in GeTe, which can lead to a better understanding of the generic behavior and consequences of the phonon hydrodynamics and its controlling parameters in low-thermal conductivity materials.

Wind farm needs prediction models for predictive maintenance. There is a need to predict values of non-observable parameters beyond ranges reflected in available data. A prediction model developed for one machine many not perform well in another similar machine. This is usually due to lack of generalizability of data-driven models. To increase generalizability of predictive models, this research integrates the data mining with first-principle knowledge. Physics-based principles are combined with machine learning algorithms through feature engineering, strong rules and divide-and-conquer. The proposed synergy concept is illustrated with the wind turbine blade icing prediction and achieves significant prediction accuracy across different turbines. The proposed process is widely accepted by wind energy predictive maintenance practitioners because of its simplicity and efficiency. Furthermore, this paper demonstrates the importance of embedding physical principles within the machine learning process, and also highlight an important point that the need for more complex machine learning algorithms in industrial big data mining is often much less than it is in other applications, making it essential to incorporate physics and follow Less is More philosophy., Comment: 9 pages, 10 figures

The kinematic Sunyaev-Zel'dovich (kSZ) effect -- the Doppler boosting of cosmic microwave background (CMB) photons scattering off free electrons with non-zero line-of-sight velocity -- is an excellent probe of the distribution of baryons in the Universe. In this paper, we measure the kSZ effect due to ionized gas traced by infrared-selected galaxies from the \emph{unWISE} catalog. We employ the "projected-field" kSZ estimator, which does not require spectroscopic galaxy redshifts. To suppress non-kSZ foreground signals associated with the galaxies (e.g., dust emission and thermal SZ), this estimator requires cleaned CMB maps, which we obtain from \emph{Planck} and \emph{WMAP} data. Using a new "asymmetric" estimator that combines different foreground-cleaned CMB maps to maximize the signal-to-noise, we measure the kSZ$^2$-galaxy cross-power spectrum for three subsamples of the \emph{unWISE} galaxy catalog, which peak at mean redshifts $z \approx$ 0.6, 1.1, and 1.5, have average halo mass $\sim 1$-$5\times 10^{13}$ $h^{-1} M_{\odot}$, and in total contain over 500 million galaxies. After marginalizing over CMB lensing contributions, we measure the amplitude of the kSZ signal $A_{\rm kSZ^2} = 0.42 \pm 0.31(stat.) \pm 0.14(sys.)$, $5.02 \pm 1.01(stat.) \pm 0.47(sys.)$, and $8.23 \pm 3.23(stat.) \pm 1.60(sys.)$, for the three subsamples, where $A_{\rm kSZ^2} = 1$ corresponds to our fiducial model. The combined kSZ detection S/N $>$ 5. We discuss possible explanations for the excess kSZ signal associated with the $z \approx 1.1$ sample, and show that foreground contamination in the CMB maps is very unlikely to be the cause. Our measurements illustrate clearly that no baryons are missing on large scales at low redshifts., Comment: Matches the version accepted for publication in PRD (https://journals.aps.org/prd/accepted/d907bQ13Oae1fd21e4ff4f13177300acb1c23e88e)

This paper deals with the solution of delay differential equations describing evolution of dislocation density in metallic materials. Hardening, restoration, and recrystallization characterizing the evolution of dislocation populations provide the essential equation of the model. The last term transforms ordinary differential equation (ODE) into delay differential equation (DDE) with strong (in general, H\"older) nonlinearity. We prove upper error bounds for the explicit Euler method, under the assumption that the right-hand side function is H\"older continuous and monotone which allows us to compare accuracy of other numerical methods in our model (e.g. Runge-Kutta), in particular when explicit formulas for solutions are not known. Finally, we test the above results in simulations of real industrial process.

A first-principles density functional method along with the direct solution of linearized Boltzmann transport equations are employed to systematically analyze the low-temperature thermal transport in crystalline GeTe. The extensive thermal transport simulations, ranging from room temperature to cryogenic temperatures, reveal the emergence of a phonon hydrodynamic regime in GeTe at low temperature. The reduction of grain boundary scattering is found to play a crucial role along with the divergent trend of umklapp and normal scattering at low temperatures in accommodating the hydrodynamic regime. Average scattering rates for normal, umklapp, and other resistive processes are distinguished for a wide range (4-300 K) of temperatures and used for identifying various phonon transport regimes. Therefore, the variations of lattice thermal conductivity, phonon propagation length, and thermal diffusivity with temperature, related to these transport regimes (ballistic, hydrodynamic, and kinetic), have been thoroughly investigated. The modewise decomposition of lattice thermal conductivity and the distinction of thermal diffusivity according to different scattering processes reveal rich information on the dominant phonon modes and phonon scattering processes in GeTe at low temperature. Further, the kinetic-collective model is used to elucidate the hydrodynamic behavior of phonon scattering through the relative study of collective and kinetic contributions to the thermal transport properties. In this context, the Knudsen number is estimated through the characteristic nonlocal length and the grain size, which further quantifies the consistent hydrodynamic behavior of phonon thermal transport for GeTe. Finally, phonon-vacancy scattering for GeTe is realized, and vacancies are found strongly to influence the hydrodynamic window while incorporating the other resistive scattering mechanisms.

Thermal transport properties bear a pivotal role in influencing the performance of phase change memory (PCM) devices, in which the PCM operation involves fast and reversible phase change between amorphous and crystalline phases. In this paper, we present a systematic experimental and theoretical study on the thermal conductivity of GeTe at high temperatures involving fast change from amorphous to crystalline phase upon heating. Modulated photothermal radiometry (MPTR) is used to experimentally determine thermal conductivity of GeTe at high temperatures in both amorphous and crystalline phases. Thermal boundary resistances are accurately taken into account for experimental consideration. To develop a concrete understanding of the underlying physical mechanism, rigorous and in-depth theoretical exercises are carried out. For this, first-principles density functional methods and linearized Boltzmann transport equations (LBTE) are employed using both direct and relaxation time based approach (RTA) and compared with that of the phenomenological Slack model. The amorphous phase experimental data has been described using the minimal thermal conductivity model with sufficient precision. The theoretical estimation involving direct solution and RTA method are found to retrieve well the trend of the experimental thermal conductivity for crystalline GeTe at high temperatures despite being slightly overestimated and underestimated, respectively, compared to the experimental data. A rough estimate of vacancy contribution has been found to modify the direct solution in such a way that it agrees excellently with the experiment. Umklapp scattering has been determined as the significant phonon-phonon scattering process. Umklapp scattering parameter has been identified for GeTe for the whole temperature range which can uniquely determine and compare Umklapp scattering processes for different materials

Dust particles from high latitudes have a potentially large local, regional, and global significance to climate and the environment as short-lived climate forcers, air pollutants, and nutrient sources. Identifying the locations of local dust sources and their emission, transport, and deposition processes is important for understanding the multiple impacts of high-latitude dust (HLD) on the Earth’s systems. Here, we identify, describe, and quantify the source intensity (SI) values, which show the potential of soil surfaces for dust emission scaled to values 0 to 1 concerning globally best productive sources, using the Global Sand and Dust Storms Source Base Map (G-SDS-SBM). This includes 64 HLD sources in our collection for the northern (Alaska, Canada, Denmark, Greenland, Iceland, Svalbard, Sweden, and Russia) and southern (Antarctica and Patagonia) high latitudes. Activity from most of these HLD sources shows seasonal character. It is estimated that high-latitude land areas with higher (SI ≥ 0.5), very high (SI ≥ 0.7), and the highest potential (SI ≥ 0.9) for dust emission cover > 1 670 000 km2 , > 560 000 km2 , and > 240 000 km2 , respectively. In the Arctic HLD region (≥ 60◦ N), land area with SI ≥ 0.5 is 5.5 % (1 035 059 km2), area with SI ≥ 0.7 is 2.3 % (440 804 km2), and area with SI ≥ 0.9 is 1.1 % (208 701 km2). Minimum SI values in the northern HLD region are about 3 orders of magnitude smaller, indicating that the dust sources of this region greatly depend on weather conditions. Our spatial dust source distribution analysis modeling results showed evidence supporting a northern HLD belt, defined as the area north of 50◦ N, with a “transitional HLD-source area” extending at latitudes 50–58◦ N in Eurasia and 50–55◦ N in Canada and a “cold HLD-source area” including areas north of 60◦ N in Eurasia and north of 58◦ N in Canada, with currently “no dust source” area between the HLD and low-latitude dust (LLD) dust belt, except for British Columbia. Using the global atmospheric transport model SILAM, we estimated that 1.0 % of the global dust emission originated from the high-latitude regions. About 57 % of the dust deposition in snow- and ice-covered Arctic regions was from HLD sources. In the southern HLD region, soil surface conditions are favorable for dust emission during the whole year. Climate change can cause a decrease in the duration of snow cover, retreat of glaciers, and an increase in drought, heatwave intensity, and frequency, leading to the increasing frequency of topsoil conditions favorable for dust emission, which increases the probability of dust storms. Our study provides a step forward to improve the representation of HLD in models and to monitor, quantify, and assess the environmental and climate significance of HLD.

Particle-size distribution of lunar dust simulant is evaluated using scanning electron spectroscopy in order to consider approaches to evaluating risk to individual mechanical components operating on the lunar surface. Assessing component risk and risk-mitigation during actual operations will require noninvasive continuous data gathering on numerous parameters. Those data sets would best be evaluated using data-mining algorithms to assess risk, and recovery from risk, of individual mechanical components in real-time.