Explore the vast range of titles available.

Micro-thermoelectric coolers are emerging as a promising solution for high-density cooling applications in confined spaces. Unlike thin-film micro-thermoelectric coolers with high cooling flux at the expense of cooling temperature difference due to very short thermoelectric legs, thick-film micro-thermoelectric coolers can achieve better comprehensive cooling performance. However, they still face significant challenges in both material preparation and device integration. Herein, we propose a design strategy which combines Bi 2 Te 3 -based thick film prepared by powder direct molding with micro-thermoelectric cooler integrated via phase-change batch transfer. Accurate thickness control and relatively high thermoelectric performance can be achieved for the thick film, and the high-density-integrated thick-film micro-thermoelectric cooler exhibits excellent performance with maximum cooling temperature difference of 40.6 K and maximum cooling flux of 56.5 W·cm −2 at room temperature. The micro-thermoelectric cooler also shows high temperature control accuracy (0.01 K) and reliability (over 30000 cooling cycles). Moreover, the device demonstrates remarkable capacity in power generation with normalized power density up to 214.0 μW · cm −2  · K −2 . This study provides a general and scalable route for developing high-performance thick-film micro-thermoelectric cooler, benefiting widespread applications in thermal management of microsystems. The micro-thermoelectric coolers face challenges in high-performance material preparation and high-density device integration. Here, the authors combine Bi 2 Te 3 -based film prepared by powder direct molding with micro-thermoelectric cooler integrated via phase-change batch transfer.

Coulomb drag refers to the phenomenon in which a charge current in one electronic circuit induces a responsive current in a neighbouring circuit solely through Coulomb interactions. For conventional interactions between electrons, the induced drag current in the passive layer is orders of magnitude weaker than the active current due to the strong dielectric screening effect between them. Here we show a Coulomb drag effect between an active normal conductor and a passive superconductor of Josephson junction arrays, where the passive current is of the same order as the active one. The drag force originates from the interactions between the substantially enhanced dynamical quantum fluctuations of the superconducting phases in the passive layer and normal electrons in the active layer. We demonstrate this effect in devices composed of monolayer graphene and LaAlO3/SrTiO3 heterointerface. The estimated passive-to-active ratio can reach about 0.3 at the optimal gate voltage and the temperature dependence follows that of the typical Josephson energy between superconducting puddles. From an engineering perspective, our device may work as a current or voltage transformer, and the drag mechanism lays the foundation for synchronizing Josephson-junction-array-based terahertz radiators.Transport measurements between a normal conductor and superconductor show that in this case, the Coulomb drag response can be much larger than that between two normal conductors.

Coulomb drag refers to the phenomenon that a charge current in one electronic circuit induces a responsive current in a neighboring circuit solely through Coulomb interactions. For conventional interactions between fermionic particles such as electrons, the as-induced drag current in the passive layer is orders of magnitude weaker than the active current due to strong dielectric screening effect between the two. Here we propose a 'super' Coulomb drag effect between an active normal conductor and a passive superconductor of Josephson junction arrays, whereby the passive current can greatly exceed the active. The drag force originates from the interactions between the substantially enhanced dynamical quantum fluctuations of the superconducting phases in the passive layer and the normal electrons in the active layer. We demonstrate this effect in the devices composed of monolayer graphene and LaAlO3/SrTiO3 heterointerface, an inherently non-uniform superconductor described by Josephson junction arrays. Remarkable drag signal is observed in the superconducting transition regime of the LaAlO3/SrTiO3 interface, with its sign independent of the carrier type in the graphene layer. The estimated passive-to-active ratio can reach about 0.3 at the optimal gate voltage and the temperature dependence follows that of the typical Josephson energy between superconducting puddles. Strikingly, the ratio ought to be as large as 10^5 at zero temperature by theoretical extrapolation. From engineering perspective, our device may work as current or voltage transformers, and the drag mechanism lays the foundation for synchronizing Josephson-junction-array-based terahertz radiators.

Background Observational studies have revealed that type 2 diabetes (T2D) is associated with an increased risk of peripheral artery disease (PAD). However, whether the two diseases share a genetic basis and whether the relationship is causal remain unclear. It is also unclear as to whether these relationships differ between ethnic groups. Methods By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D (European-based: N case = 21,926, N control = 342,747; East Asian-based: N case = 36,614, N control = 155,150) and PAD (European-based: N case = 5673, N control = 359,551; East Asian-based: N case = 3593, N control = 208,860), we explored the genetic correlation and putative causal relationship between T2D and PAD in both Europeans and East Asians using linkage disequilibrium score regression and seven Mendelian randomization (MR) models. We also performed multi-trait analysis of GWAS and two gene-based analyses to reveal candidate variants and risk genes involved in the shared genetic basis between T2D and PAD. Results We observed a strong genetic correlation ( r g ) between T2D and PAD in both Europeans ( r g = 0.51; p -value = 9.34 × 10 −15 ) and East Asians ( r g = 0.46; p -value = 1.67 × 10 −12 ). The MR analyses provided consistent evidence for a causal effect of T2D on PAD in both ethnicities (odds ratio [OR] = 1.05 to 1.28 for Europeans and 1.15 to 1.27 for East Asians) but not PAD on T2D. This putative causal effect was not influenced by total cholesterol, body mass index, systolic blood pressure, or smoking initiation according to multivariable MR analysis, and the genetic overlap between T2D and PAD was further explored employing an independent European sample through polygenic risk score regression. Multi-trait analysis of GWAS revealed two novel European-specific single nucleotide polymorphisms (rs927742 and rs1734409) associated with the shared genetic basis of T2D and PAD. Gene-based analyses consistently identified one gene ANKFY1 and gene-gene interactions (e.g., STARD10 [European-specific] to AP3S2 [East Asian-specific]; KCNJ11 [European-specific] to KCNQ1 [East Asian-specific]) associated with the trans-ethnic genetic overlap between T2D and PAD, reflecting a common genetic basis for the co-occurrence of T2D and PAD in both Europeans and East Asians. Conclusions Our study provides the first evidence for a genetically causal effect of T2D on PAD in both Europeans and East Asians. Several candidate variants and risk genes were identified as being associated with this genetic overlap. Our findings emphasize the importance of monitoring PAD status in T2D patients and suggest new genetic biomarkers for screening PAD risk among patients with T2D.

Biogenic compounds are important materials for drug discovery and chemical biology. In this work, we report a quasi-biogenic molecule generator (QBMG) to compose virtual quasi-biogenic compound libraries by means of gated recurrent unit recurrent neural networks. The library includes stereo-chemical properties, which are crucial features of natural products. QMBG can reproduce the property distribution of the underlying training set, while being able to generate realistic, novel molecules outside of the training set. Furthermore, these compounds are associated with known bioactivities. A focused compound library based on a given chemotype/scaffold can also be generated by this approach combining transfer learning technology. This approach can be used to generate virtual compound libraries for pharmaceutical lead identification and optimization.

In this work, merged and alternating droplets generated in a microfluidic double T-junction are investigated using experiments and numerical simulations. The double T-junction is constructed by symmetrically inserting two capillaries into a microfluidic chip at specific positions. We explore the effects of the two-phase flow rate fraction, capillary tip distance (30 μm, 60 μm, and 200 μm), and fluid properties on droplet formation phenomena. Detailed observations reveal four distinct regimes during the dynamic evolution of the two-phase interface morphology: merged state, stable alternating droplets, droplet pairs, and jetting. Two phase diagrams are obtained to demonstrate that interfacial tension and dispersed phase viscosity significantly influence these regimes. Moreover, we find that as the flow rate fraction increases from 0.054 to 0.286, the length of generated droplets increases from 156 to 789 μm; we provide a theoretical prediction formula for dimensionless droplet length accordingly. Additionally, our simulations show fluctuating pressure in dispersed flows throughout the process of droplet generation. The simulated pressure in the dispersed flows fluctuates during the droplet generation process. The understanding of the underlying physics of the capillary-based double T-junction contributes valuable insights for various related applications.HighlightsAn easy capillary-based double T-junction for droplet generation.Merged and alternating droplets are generated.Four regimes are observed as the merged, stable alternating droplet, droplet pairs, and jetting.Effects of two-phase flow rates, capillary tip distances, and fluid properties are investigated.

Yutu-2 rover conducted an exciting expedition on the 41st lunar day to investigate a fin-shaped rock at Longji site (45.44°S, 177.56°E) by extending its locomotion margin on perilous peaks. The varied locomotion encountered, especially multi-form wheel slippage, during the journey to the target rock, established unique conditions for a fin-grained lunar regolith analysis regarding bearing, shear and lateral properties based on terramechanics. Here, we show a tri-aspect characterization of lunar regolith and infer the rock’s origin using a digital twin. We estimate internal friction angle within 21.5°−42.0° and associated cohesion of 520-3154 Pa in the Chang’E-4 operational site. These findings suggest shear characteristics similar to Apollo 12 mission samples but notably higher cohesion compared to regolith investigated on most nearside lunar missions. We estimate external friction angle in lateral properties to be within 8.3°−16.5°, which fills the gaps of the lateral property estimation of the lunar farside regolith and serves as a foundational parameter for subsequent engineering verifications. Our in-situ spectral investigations of the target rock unveil its composition of iron/magnesium-rich low-calcium pyroxene, linking it to the Zhinyu crater (45.34°S, 176.15°E) ejecta. Our results indicate that the combination of in-situ measurements with robotics technology in planetary exploration reveal the possibility of additional source regions contributing to the local materials at the Chang’E-4 site, implying a more complicated geological history in the vicinity. Digital twins can be used to support planetary operations and analysis. Here, the authors show tri-aspect characterization of lunar far side regolith and investigate the origin of a fin-shaped rock via digital twin of Yutu-2 rover.

Background This study aimed to investigate the impacts of guar gum and cellulose as the source of dietary fiber during gestation on the reproductive performance of sows. Methods A total of 210 sows (parities 3–6) were randomly allocated into six diets ( n  = 35) throughout gestation to feed graded levels of dietary fiber (DF), including a corn-soybean meal-based control diet with no wheat bran inclusion (CON, 12.5% DF), a wheat bran-rich diet (DF1, 17.4% DF), and another 4 diets (DF2, 17.7% DF; DF3, 18.1% DF; DF4, 18.4% DF; DF5, 18.8% DF) in which wheat bran were equally substituted by 1%, 2%, 3% and 4% purified FIBER MIX (guar gum and cellulose, 1:4). All sows received similar DE and other nutrients throughout gestation. Results DF treatment during gestation resulted in normal fecal score (1 to 5 with 1 = dry and 5 = watery) in sows compared with those received the CON diet ( P  <  0.05). The number of total born piglets had a tendency to be affected by dietary treatment ( P  = 0.07), and correlation analysis revealed a linear response of total born to dietary fiber levels during gestation ( P <  0.01). Sows received the DF2, DF3, and DF5 diets during gestation had a greater ADFI during lactation compared with those in the CON group ( P <  0.05) without affecting the daily body weight gain of suckling piglets. Gut microbiota compositions were dramatically changed by the gestation stage and some of those were changed by DF inclusion. Fecal acetate, propionate, and butyrate of sows were markedly increased in late gestation, and butyrate contents in feces of gestating sows were significantly affected by DF levels ( P <  0.01). Serum concentrations of pro-inflammatory TNF-α were decreased and anti-inflammatory IL-10 was increased on day 30 of gestation by DF levels ( P <  0.05). Conclusions In summary, increasing dietary fiber levels by guar gum and cellulose during gestation improved the reproductive performance of sows, which might be related to changes in immunity and gut microbiota of sows.

A cooling tower is an important guarantee for the proper operation of a solar system. To ensure proper operation of the system and to maintain high-efficiency points, the cooling tower must operate year-round. However, freezing is a common problem that degrades the performance of cooling towers in winter. For example, the air inlet forms hanging ice, which clogs the air path, and the coil in closed cooling towers freezes and cracks, leading to water leakage in the internal circulation. This has become an intractable problem that affects the safety and performance of cooling systems in winter. To address this problem, three methods of freeze protection for cooling towers are studied: (a) the dry and wet mixing operation method—the method of selecting heat exchangers under dry operation at different environments and inlet water temperatures is presented. The numerical experiment shows that the dry and wet mixing operation method can effectively avoid ice hanging on the air inlet. (b) The engineering plastic capillary mats method—its freeze protection characteristics, thermal performance, and economics are studied, and the experiment result is that polyethylene (PE) can meet the demands of freeze protection. (c) The antifreeze fluid method—the cooling capacity of the closed cooling towers with different concentrations of glycol antifreeze fluid is numerically studied by analyzing the heat transfer coefficient ratio, the air volume ratio, the heat dissipation ratio, and the flow rate ratio. The addition of glycol will reduce the cooling capacity of the closed cooling tower.

As one of the major forms of geological disaster, landslides cause huge casualties and economic losses in China every year. Given the importance of landslide prediction, it is a challenging task due to difficulties in efficiently leveraging the spatial–temporal information for enhanced prediction. This paper presents a novel spatial–temporal enhanced CNN-GRU model to improve landslide predictions with the following contributions. First, this paper explicitly models the spatial correlation in the dataset and constructs a spatial–temporal time-sequence deformation prediction model that greatly improves landslide predictions. This model integrates the spatial correlation of monitoring points into time-series deformation prediction to improve the prediction of landslide deformation trends. Second, we develop a complete data processing pipeline involving SBAS-InSAR, time-series data preprocessing, spatial–temporal homogeneous point selection and weighting, as well as CNN-GRU model training. The pipeline is tailor-designed to leverage the spatial–temporal correlation in the data to enhance the prediction performance. Third, we apply the proposed model to monitor landslide deformation around Woda Village, Chamdo City, Tibet. The results show that the root mean square error (RMSE) of the monitoring points in the landslide area is reduced by about 20.9% and the number of points with an RMSE of less than 3 mm is increased by 12.9%, leading to a significant improvement in prediction accuracy.