Liquid metal heat sink for laptop computers

With the rapid miniaturization of the electronic systems, heat generation in the components becomes a major concern for thermal management. The high density of heat generation can be a bottleneck to attain higher performance and reliability of computers. Because conventional cooling methods such as finned heat sink are often incapable of providing adequate cooling for sophisticated electronic systems, new systems like heat pipes or liquid cooling systems are being studied. This work focused on the novel design of a liquid metal and heat sink cooling loop targeted for laptop computer thermal management. The liquid metal was driven by an electromechanical pump, offering no moving parts and quiet operation. To better understand the design process, theoretical analysis for fluid flow and heat transfer performance of liquid metal and heat sink are conducted. Furthermore, in order to demonstrate the feasibility of this new concept, a series of experiments on the fabricated module under different heater powers and pump power are performed. A thermal resistance value of 0.53 ?/W was experimentally determined, making the performance similar to competing technologies. Performance was impeded by a low pump efficiency, a known impediment with electromagnetic pumps

Prominent Size Effects without a Depolarization Field Observed in Ultrathin Ferroelectric Oxide Membranes

The increasing miniaturization of electronics requires a better understanding of material properties at the nanoscale. Many studies have shown that there is a ferroelectric size limit in oxides, below which the ferroelectricity will be strongly suppressed due to the depolarization field, and whether such a limit still exists in the absence of the depolarization field remains unclear. Here, by applying uniaxial strain, we obtain pure in-plane polarized ferroelectricity in ultrathin SrTiO3 membranes, providing a clean system with high tunability to explore ferroelectric size effects especially the thickness-dependent ferroelectric instability with no depolarization field. Surprisingly, the domain size, ferroelectric transition temperature, and critical strain for room-temperature ferroelectricity all exhibit significant thickness dependence. These results indicate that the stability of ferroelectricity is suppressed (enhanced) by increasing the surface or bulk ratio (strain), which can be explained by considering the thickness-dependent dipole-dipole interactions within the transverse Ising model. Our study provides new insights into ferroelectric size effects and sheds light on the applications of ferroelectric thin films in nanoelectronics

A Non‐Pt Electronically Coupled Semiconductor Heterojunction for Enhanced Oxygen Reduction Electrocatalytic Property

Hybrid faceted‐Ag3PO4/cube‐Cu2O composite materials have been fabricated and employed as oxygen reduction electrocatalysts for proton exchange membrane fuel cells (PEMFCs). The charge separation effect via the formation of PN junction has been demonstrated to boost the electrocatalysis toward oxygen reduction reaction. The as‐prepared rhombic dodecahedron‐Ag3PO4/cube‐Cu2O/C hybrid catalyst shows a mass‐specific activity of 109.80 mA/mgAg, which is about 6.4 times that of pure rhombic dodecahedron‐Ag3PO4/C catalyst (17.20 mA/mgAg). The density functional theory (DFT) calculation based on the density of states (DOS) further proved the optimal tunable effect, which is in pace with demonstration of electron transfer direction revealed by X‐ray photoelectron spectroscopy (XPS) analysis. Our work establishes a theoretical and practical basis for the rational design of newly non‐Pt hybrid catalysts, moreover, advances the future efficient application of PEMFCs.A cost effective electronically coupled semiconductor heterojunction between facet‐Ag3PO4 and Cu2O cube is reported. Its high electrocatalytic activity towards oxygen reduction reaction (ORR) indicates that electron distribution can be controlled through the interfacial engineering between Ag3PO4 and Cu2O. This paves way to rationally design new non‐Pt hybrid catalysts, and moreover advances the future efficient applications of proton exchange membrane fuel cells (PEMFCs).Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149290/1/slct201900615.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149290/2/slct201900615-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149290/3/slct201900615_am.pd

Feasibility Analysis and Application of Reinforcement Learning Algorithm Based on Dynamic Parameter Adjustment

Reinforcement learning, as a branch of machine learning, has been gradually applied in the control field. However, in the practical application of the algorithm, the hyperparametric approach to network settings for deep reinforcement learning still follows the empirical attempts of traditional machine learning (supervised learning and unsupervised learning). This method ignores part of the information generated by agents exploring the environment contained in the updating of the reinforcement learning value function, which will affect the performance of the convergence and cumulative return of reinforcement learning. The reinforcement learning algorithm based on dynamic parameter adjustment is a new method for setting learning rate parameters of deep reinforcement learning. Based on the traditional method of setting parameters for reinforcement learning, this method analyzes the advantages of different learning rates at different stages of reinforcement learning and dynamically adjusts the learning rates in combination with the temporal-difference (TD) error values to achieve the advantages of different learning rates in different stages to improve the rationality of the algorithm in practical application. At the same time, by combining the Robbins–Monro approximation algorithm and deep reinforcement learning algorithm, it is proved that the algorithm of dynamic regulation learning rate can theoretically meet the convergence requirements of the intelligent control algorithm. In the experiment, the effect of this method is analyzed through the continuous control scenario in the standard experimental environment of ”Car-on-The-Hill” of reinforcement learning, and it is verified that the new method can achieve better results than the traditional reinforcement learning in practical application. According to the model characteristics of the deep reinforcement learning, a more suitable setting method for the learning rate of the deep reinforcement learning network proposed. At the same time, the feasibility of the method has been proved both in theory and in the application. Therefore, the method of setting the learning rate parameter is worthy of further development and research

Generation of Quiescent Cardiac Fibroblasts From Human Induced Pluripotent Stem Cells for In Vitro Modeling of Cardiac Fibrosis.

RationaleActivated fibroblasts are the major cell type that secretes excessive extracellular matrix in response to injury, contributing to pathological fibrosis and leading to organ failure. Effective anti-fibrotic therapeutic solutions, however, are not available due to the poorly defined characteristics and unavailability of tissue-specific fibroblasts. Recent advances in single-cell RNA-sequencing fill such gaps of knowledge by enabling delineation of the developmental trajectories and identification of regulatory pathways of tissue-specific fibroblasts among different organs.ObjectiveThis study aims to define the transcriptome profiles of tissue-specific fibroblasts using recently reported mouse single-cell RNA-sequencing atlas and to develop a robust chemically defined protocol to derive cardiac fibroblasts (CFs) from human induced pluripotent stem cells for in vitro modeling of cardiac fibrosis and drug screening.Methods and resultsBy analyzing the single-cell transcriptome profiles of fibroblasts from 10 selected mouse tissues, we identified distinct tissue-specific signature genes, including transcription factors that define the identities of fibroblasts in the heart, lungs, trachea, and bladder. We also determined that CFs in large are of the epicardial lineage. We thus developed a robust chemically defined protocol that generates CFs from human induced pluripotent stem cells. Functional studies confirmed that iPSC-derived CFs preserved a quiescent phenotype and highly resembled primary CFs at the transcriptional, cellular, and functional levels. We demonstrated that this cell-based platform is sensitive to both pro- and anti-fibrosis drugs. Finally, we showed that crosstalk between human induced pluripotent stem cell-derived cardiomyocytes and CFs via the atrial/brain natriuretic peptide-natriuretic peptide receptor-1 pathway is implicated in suppressing fibrogenesis.ConclusionsThis study uncovers unique gene signatures that define tissue-specific identities of fibroblasts. The bona fide quiescent CFs derived from human induced pluripotent stem cells can serve as a faithful in vitro platform to better understand the underlying mechanisms of cardiac fibrosis and to screen anti-fibrotic drugs

Generation of Quiescent Cardiac Fibroblasts From Human Induced Pluripotent Stem Cells for In Vitro Modeling of Cardiac Fibrosis.

RationaleActivated fibroblasts are the major cell type that secretes excessive extracellular matrix in response to injury, contributing to pathological fibrosis and leading to organ failure. Effective anti-fibrotic therapeutic solutions, however, are not available due to the poorly defined characteristics and unavailability of tissue-specific fibroblasts. Recent advances in single-cell RNA-sequencing fill such gaps of knowledge by enabling delineation of the developmental trajectories and identification of regulatory pathways of tissue-specific fibroblasts among different organs.ObjectiveThis study aims to define the transcriptome profiles of tissue-specific fibroblasts using recently reported mouse single-cell RNA-sequencing atlas and to develop a robust chemically defined protocol to derive cardiac fibroblasts (CFs) from human induced pluripotent stem cells for in vitro modeling of cardiac fibrosis and drug screening.Methods and resultsBy analyzing the single-cell transcriptome profiles of fibroblasts from 10 selected mouse tissues, we identified distinct tissue-specific signature genes, including transcription factors that define the identities of fibroblasts in the heart, lungs, trachea, and bladder. We also determined that CFs in large are of the epicardial lineage. We thus developed a robust chemically defined protocol that generates CFs from human induced pluripotent stem cells. Functional studies confirmed that iPSC-derived CFs preserved a quiescent phenotype and highly resembled primary CFs at the transcriptional, cellular, and functional levels. We demonstrated that this cell-based platform is sensitive to both pro- and anti-fibrosis drugs. Finally, we showed that crosstalk between human induced pluripotent stem cell-derived cardiomyocytes and CFs via the atrial/brain natriuretic peptide-natriuretic peptide receptor-1 pathway is implicated in suppressing fibrogenesis.ConclusionsThis study uncovers unique gene signatures that define tissue-specific identities of fibroblasts. The bona fide quiescent CFs derived from human induced pluripotent stem cells can serve as a faithful in vitro platform to better understand the underlying mechanisms of cardiac fibrosis and to screen anti-fibrotic drugs

Performance Assessment of a Concrete Gravity Dam at Shenwo Reservoir of China Using Deterministic and Probabilistic Methods

NSFC [51261120376, 11102174, 51281220267]; Open Research Fund Program of State key Laboratory of Hydroscience and Engineering [sklhse-2013-C-02]; Administration department of Shenwo ReservoirThis paper performs degradation assessment and safety evaluation of a concrete gravity dam at Shenwo reservoir in Liaoning province of China by using two methods, i.e. deterministic method and probabilistic method, respectively. The deterministic responses of representative sluice piers are computed through static pushover and dynamic analyses. The probabilistic uncertainty analysis, including time invariant and time variant reliability analyses, is based on finite element (FE) reliability theory. For time invariant case, the material and loading parameters are considered as random variables, including elastic modulus, Poisson's ratio, mass density and pushover forces. For time variant case, the earthquake history is simulated by using random process, and the first-order reliability method (FORM) approximation combined with Koo's analytical solution is used to compute the mean upcrossing rate for given performance functions, through which the failure probabilities are calculated. Based on the analysis results using these two methods, the safety and reliability of the dam is assessed. Furthermore, the performance assessments of the dam in its current state are compared with those in the original state (i.e. when the dam was built) to quantify its performance degradation. Finally, the assessment results of using the deterministic and probabilistic methods are compared, and the discrepancies between them are quanti fied and explained. The computation is based on a general FE analysis platform for earthquake engineering simulation, OpenSees

Dual-functional application of a metal-organic framework in high-performance all-solid-state lithium metal batteries

Lithium metal batteries (LMBs) are one of the most promising candidates for next-generation high energy density batteries. However, the commercialization of LMBs is greatly hindered by several serious problems, including uncontrolled growth of Li dendrites, almost infinite expansion of electrode volume, and the erosion of electrode materials by liquid electrolytes. The present work addresses these issues by proposing a bifunctional Sn metal–organic framework (MOF) that acts as both a precursor of lithiophilic promoter for Li metal anode and an inert filler for polyethylene oxide (PEO)-based solid state electrolyte (SSE). As a result of excellent lithiophilicity, the SnO2 nanoparticles on carbon derived from Sn-MOF are applied to prepare a composite Li metal anode via molten Li infusion method to obtain excellent interfacial stability and long-term cycling performance. On the other hand, Sn-MOF is added to PEO-based SSE as an inert filler to obtain a composite SSE with a favorable ionic conductivity, outstanding Li+ transference number, and wide electrochemical window. The insight into the mechanism of Sn-MOF to improve the ionic conductivity of PEO-based electrolyte has been revealed by combined experimental analysis and first-principles calculations. An all-solid-state flexible LMB employing the optimal composite anode and SSE is demonstrated to attain an impressive electrochemical performance and the capability of powering actual devices.Web of Science475art. no. 14615

The Evaluation of Muller Weiss Diseased and Normal Feet on a Three-Dimensional Foot Model

Category: Hindfoot; Midfoot/Forefoot Introduction/Purpose: The deformities associated with Müller Weis Disease (MWD) have not been well understood which inevitably impacts clinical and surgical decision making. Despite most previous studies characterizing MWD as a paradoxical flatfoot deformity, ie, a flat arch and a varus heel, some studies have treated MWD as a flatfoot deformity by performing a medializing calcaneus osteotomy, and others as an arthritic disorder treated with hind foot arthrodesis but without correcting the deformity. This study used an automatic 3D segmentation program to create an average 3D foot model for both normal controls and a large group of MWD feet, to demonstrate the deformity pattern, and to provide surgeons with a foundation for detailed alignment evaluation and surgical planning. Methods: Weight bearing Scans of 55 health feet without deformities, trauma and surgical histories, and 69 MWD feet were included in this study. The Bonelogic program (Disior, Paragon 28,) was used to automatically segment the bones and 3D information of each foot in the same group was pooled to create an average foot model for both the controls and the MWD feet. Videos were created using all feet in both groups to demonstrate the deformity patterns ranging from normal feet transitioning to MWD feet. Since current axial and angular metrics for alignment evaluation using traditional 2D imaging cannot be extrapolated to 3D this study was kept as a descriptive paper, and no traditional metrics were analyzed and reported. Results: Compared to the average normal foot, the MWD foot model demonstrated the following features: narrowing on the lateral pole and dorsal side of the navicular, lateral rotation and slight dorsal lifting of the talar head and medial rotation of the navicular, a varus heel with more opening in the sinus tarsi, proximal shift of the calcaneal tuberosity, a flat medial arch with subsidence at the talonavicular joint, decreased adduction of the forefoot, medial translation of the cuboid at the calcaneocuboid articulation, and a shortened 1st metatarsal. All of the above changes were consistently demonstrated in video one (a comparison between the two foot models), and video two (a comparison of the peritalar joint alignment between the two groups). Conclusion: The foot models were built up with pixels, with each pixel carrying its own 3D information in space allowing exploration of real 3D alignment evaluation tools. The MWD foot model clearly demonstrated and validated the deformity patterns originally described by Maceira, and subsequently by other authors using both radiographs and WBCT scans. This model facilitates evaluation of alignment from the hindfoot to the forefoot, as well as advanced 3D analysis to assess the morphology of the bones and joints and can be the foundation for surgical planning and predication of outcomes

Hollow Alveolus-Like Nanovesicle Assembly with Metal-Encapsulated Hollow Zeolite Nanocrystals

Inspired by the vesicular structure of alveolus which has a porous nanovesicle structure facilitating the transport of oxygen and carbon dioxide, we designed a hollow nanovesicle assembly with metal-encapsulated hollow zeolite that would enhance diffusion of reactants/products and inhibit sintering and leaching of active metals. This zeolitic nanovesicle has been successfully synthesized by a strategy which involves a one-pot hydrothermal synthesis of hollow assembly of metal-containing solid zeolite crystals without a structural template and a selective desilication-recrystallization accompanied by leaching-hydrolysis to convert the metal-containing solid crystals into metal-encapsulated hollow crystals. We demonstrate the strategy in synthesizing a hollow nanovesicle assembly of Fe₂O₃-encapsulated hollow crystals of ZSM-5 zeolite. This material possesses a microporous (0.4–0.6 nm) wall of hollow crystals and a mesoporous (5–17 nm) shell of nanovesicle with macropores (about 350 nm) in the core. This hierarchical structure enables excellent Fe₂O₃ dispersion (3–4 nm) and resistance to sintering even at 800 °C; facilitates the transport of reactant/products; and exhibits superior activity and resistance to leaching in phenol degradation. Hollow nanovesicle assembly of Fe-Pt bimetal-encapsulated hollow ZSM-5 crystals was also prepared