Printability disparities in heterogeneous material combinations via laser directed energy deposition:a comparative study

Additive manufacturing provides achievability for the fabrication of bimetallic and multi-material structures;however,the material compatibility and bondability directly affect the parts’formability and final quality.It is essential to understand the underlying printability of different material combinations based on an adapted process.Here,the printability disparities of two common and attractive material combinations(nickel-and iron-based alloys)are evaluated at the macro and micro levels via laser directed energy deposition(DED).The deposition processes were captured using in situ high-speed imaging,and the dissimilarities in melt pool features and track morphology were quantitatively investigated within specific process windows.Moreover,the microstructure diversity of the tracks and blocks processed with varied material pairs was comparatively elaborated and,complemented with the informative multi-physics modeling,the presented non-uniformity in mechanical properties(microhardness)among the heterogeneous material pairs was rationalized.The differences in melt flow induced by the unlike thermophysical properties of the material pairs and the resulting element intermixing and localized re-alloying during solidification dominate the presented dissimilarity in printability among the material combinations.This work provides an in-depth understanding of the phenomenological differences in the deposition of dissimilar materials and aims to guide more reliable DED forming of bimetallic parts.

The dynamic evolution of aggregated lithium dendrites in lithium metal batteries

Lithium(Li)metal anodes promise an ultrahigh theoretical energy density and low redox potential,thus being the critical energy material for next-generation batteries.Unfortunately,the formation of Li dendrites in Li metal anodes remarkably hinders the practical applications of Li metal anodes.Herein,the dynamic evolution of discrete Li dendrites and aggregated Li dendrites with increasing current densities is visualized by in-situ optical microscopy in conjunction with ex-situ scanning electron microscopy.As revealed by the phase field simulations,the formation of aggregated Li dendrites under high current density is attributed to the locally concentrated electric field rather than the depletion of Li ions.More specifically,the locally concentrated electric field stems from the spatial inhomogeneity on the Li metal surface and will be further enhanced with increasing current densities.Adjusting the above two factors with the help of the constructed phase field model is able to regulate the electrodeposited morphology from aggregated Li dendrites to discrete Li dendrites,and ultimately columnar Li morphology.The methodology and mechanistic understanding established herein give a significant step toward the practical applications of Li metal anodes.

The chemical origin of temperature-dependent lithium-ion concerted diffusion in sulfide solid electrolyte Li_(10)GeP_(2)S_(12)

Solid-state batteries have received increasing attention in scientific and industrial communities,which benefits from the intrinsically safe solid electrolytes(SEs).Although much effort has been devoted to designing SEs with high ionic conductivities,it is extremely difficult to fully understand the ionic diffusion mechanisms in SEs through conventional experimental and theoretical methods.Herein,the temperature-dependent concerted diffusion mechanism of ions in SEs is explored through machinelearning molecular dynamics,taking Li_(10)GeP_(2)S_(12) as a prototype.Weaker diffusion anisotropy,more disordered Li distributions,and shorter residence time are observed at a higher temperature.Arrhenius-type temperature dependence is maintained within a wide temperature range,which is attributed to the linear temperature dependence of jump frequencies of various concerted diffusion modes.These results provide a theoretical framework to understand the ionic diffusion mechanisms in SEs and deepen the understanding of the chemical origin of temperature-dependent concerted diffusions in SEs.

浅谈守恒定律在分析化学教学中的应用

守恒是自然界普遍遵循的定律,在分析化学中也涉及到许多守恒定律,如物料守恒、电荷守恒、质子守恒、电子守恒等。在分析化学教学中,守恒定律不仅用于许多公式的推导,还能用来解决复杂的计算问题。笔者在长期的教学实践中发现运用守恒定律来解决问题,不仅能帮助学生了解公式的来龙去脉,还有助于帮助学生从宏观全局考虑问题,将复杂的过程简单化,而不必在过程细节上纠缠。

Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm

Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images(WSIs).Methods We retrospectively collected 1,250 gastric biopsy specimens(1,128 gastritis,122 normal mucosa)from PLA General Hospital.The deep learning algorithm based on DeepLab v3(ResNet-50)architecture was trained and validated using 1,008 WSIs and 100 WSIs,respectively.The diagnostic performance of the algorithm was tested on an independent test set of 142 WSIs,with the pathologists’consensus diagnosis as the gold standard.Results The receiver operating characteristic(ROC)curves were generated for chronic superficial gastritis(CSuG),chronic active gastritis(CAcG),and chronic atrophic gastritis(CAtG)in the test set,respectively.The areas under the ROC curves(AUCs)of the algorithm for CSuG,CAcG,and CAtG were 0.882,0.905 and 0.910,respectively.The sensitivity and specificity of the deep learning algorithm for the classification of CSuG,CAcG,and CAtG were 0.790 and 1.000(accuracy 0.880),0.985 and 0.829(accuracy 0.901),0.952 and 0.992(accuracy 0.986),respectively.The overall predicted accuracy for three different types of gastritis was 0.867.By flagging the suspicious regions identified by the algorithm in WSI,a more transparent and interpretable diagnosis can be generated.Conclusion The deep learning algorithm achieved high accuracy for chronic gastritis classification using WSIs.By pre-highlighting the different gastritis regions,it might be used as an auxiliary diagnostic tool to improve the work efficiency of pathologists.

饲粮中添加金盏菊提取物对肉鸡生长性能、色素沉积、抗氧化能力及肉品质的影响

本试验旨在研究饲粮中添加金盏菊提取物对肉鸡生长性能、色素沉积、抗氧化能力及肉品质的影响。320只1日龄的AA肉鸡随机分为5个处理组,每个处理组8个重复,每个重复8只鸡。对照组饲喂基础饲粮,其他处理组在基础饲粮中分别添加0.075%,0.15%,0.30%和0.60%金盏菊提取物(相对应的叶黄素浓度分为15、30、60及120 mg/kg)。结果显示,金盏菊提取物可以显著增加肉鸡小腿、喙、皮肤和肌肉的黄色水平以及腿肌的红度线性效应,P<0.01)。金盏菊提取物可以显著增加肉鸡肝脏和腿肌中总抗氧化能力和超氧化物歧化酶的活性(线性效应,P<0.01)。金盏菊提取物显著地降低肉鸡腿肌的滴水损失和剪切力(线性效应,P<0.01)。金盏菊提取物对于肉鸡的生长性能并无显著影响。根据试验结果我们得出结论,肉鸡饲粮中添加金盏菊提取物能够显著增加屠体的黄色水平,提高抗氧化能力和改善肉品质。

Super-exchange effect induced by early 3d metal doping on NiFe_(2)O_(4)(001)surface for oxygen evolution reaction

Understanding the intrinsic activity of oxygen evolution reaction(OER) is crucial for catalyst design.To date,different metal-doping strategies have been developed to achieve this,but the involving mechanisms remain unclear.Here,the electronic structure of the transition metal-doped NiFe_(2)O_(4)(001) surface is scrutinized for OER intrinsic activity using density functional theory calculations.Five 3d-orbital filling metals(Ti,V,Cr,Mn,and Co) are introduced as dopants onto A-and B-layers of the NiFe_(2)O_(4)(001) surface,and variation of oxidation states over Fe sites is observed on B-layer.Analyzing the magnetic moment and charge transfer of surface cation sites reveals that the variation of Fe oxidation states originates from the super-exchange effect and is influenced by the t2g-electron configuration of 3d metal dopants.This trend governs the generation of highly-active Fe3+sites on the B-layer,the adsorption strength of OER intermediates,i.e.,*O and*OH,and therefore the intrinsic activity.The finding of super-exchange mechanism induced by 3d early metal doping offers insights into electronic structure tailoring strategies for improving the intrinsic activity of OER electrocatalysts.

Fabricating a PVDF skin for PEO-based SPE to stabilize the interface both at cathode and anode for Li-ion batteries

Poly(ethylene oxide)(PEO)-based solid polymer electrolyte is always the most promising candidate for preparing thinner, lighter and safer lithium-ion batteries. However, the lithium dendrites growth of lithium anode and the high-voltage oxidation of cathode are easy to cause the PEO-based battery failure.The way to deal with the different challenges on both sides of the anode and cathode is pursued all the time. In this study, we reported a new strategy to construct the PVDF/PEO/PVDF three-layer structure for solid polymer electrolyte(marked as PVDF@PEO) using PVDF as the functional “skin”. The PVDF@PEO electrolyte can effectively prevent from the lithium dendrites, and shows a stable cycling life over1000 h in the Li/PVDF@PEO/Li cell. In addition, the PVDF@PEO electrolyte exhibits higher oxidation resistance and can be matched with high-voltage LiCoO_(2) cathode. The Li/PVDF@PEO/LiCoO_(2) cell delivered a specific capacity of about 150 m Ah g^(-1) over 150 cycles and maintained good cycling stability. Our research provides insights that the polymer electrolytes constructed with PVDF functional “skin” can simultaneously meet the challenges of both anode and cathode in solid-state lithium-ion batteries(SSLIBs).

Thermoelectric characteristics of semiconductor minerals in earth's deep crust and their seismogenic significance

Geo-electric anomalies are generated during the process of stress accumulation and release associated with earthquakes.However,the mechanism of these anomalies remains equivocal.Based on the analysis of thermoelectric characteristics of semiconductor minerals of the earth’s deep crust such as graphite,ferrosilicon alloy,magnetite etc.,we perform finite element analysis to evaluate the principles governing the thermoelectric power generated by minerals and rocks.The results show that graphite,ferrosilicon alloy and magnetite all exhibit Seebeck effect and can be superimposed.And the thermo-electric field can be enhanced with the activation temperature increases,the content of thermoelectric minerals increases,the size of aggregates increases,and the spacing of thermoelectric minerals grains decreases.Seismogenic processes would generate a similar thermal gradient.The natural semiconductor minerals in this thermal field show a thermoelectric effect,forming a thermoelectric field that interferes with the background electric field.This study indicates that thermoelectric effect may have an important influence on the formation of geoelectric field.

固态电解质Li_(3)PS_(4)晶相结构转变

硫化物Li_(3)PS_(4)是重要的含硫快离子导体,锂离子电导率高,机械性能优异,化学兼容性好,属于全固态电池中一类重要的固态电解质.Li_(3)PS_(4)具有多种晶体结构(玻璃态、α相、β相、γ相),而晶体结构对于材料离子电导率有决定性的影响,因此探究不同Li_(3)PS_(4)晶体结构的合成条件及其转变过程对固态电解质的应用有重要意义.本文通过原位变温Raman和室温X射线衍射(XRD)分析发现,通过球磨法所得glass-Li_(3)PS_(4)在首次升温过程中(240℃)优先转变为亚稳态的β-Li_(3)PS_(4),此时冷却到室温能保持β相结构,并具有较高的离子电导率(0.65 mS cm^(-1)).当烧结温度继续升高(>480℃),β相会转变为离子电导率更高但热力学不稳定的α-Li_(3)PS_(4),在后续的降温过程中,α相会直接转变为热力学更稳定但离子电导率差的γ-Li_(3)PS_(4).此外,γ-Li_(3)PS_(4)和β-Li_(3)PS_(4)具有一定的结构记忆效应,即使经历二次低温烧结后(240℃)也能维持其固有的结构.以上结果表明,首次烧结温度对于Li_(3)PS_(4)材料的结构和离子电导率具有重要的影响,合理控制烧结温度能够成功制备出具有更高离子电导率的β-Li_(3)PS_(4)固态电解质.此外,所制备的β-Li_(3)PS_(4)固态电解质对锂表现出相对优异的界面性能.

Emerging role of deep learning-based artificial intelligence in tumor pathology

The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence(AI),especially deep learning(DL)-based AI,in tumor pathology.The DL-based algorithms have been developed to conduct all kinds of work involved in tumor pathology,including tumor diagnosis,subtyping,grading,staging,and prognostic prediction,as well as the identification of pathological features,biomarkers and genetic changes.The applications of AI in pathology not only contribute to improve diagnostic accuracy and objectivity but also reduce the workload of pathologists and subsequently enable them to spend additional time on high-level decision-making tasks.In addition,AI is useful for pathologists to meet the requirements of precision oncology.However,there are still some challenges relating to the implementation of AI,including the issues of algorithm validation and interpretability,computing systems,the unbelieving attitude of pathologists,clinicians and patients,as well as regulators and reimbursements.Herein,we present an overview on how AI-based approaches could be integrated into the workflow of pathologists and discuss the challenges and perspectives of the implementation of AI in tumor pathology.

High piezoelectricity and low strain hysteresis in PMN-PT-based piezoelectric ceramics

High piezoelectric properties and low strain hysteresis(H)are both equally necessary for practical applications in precisely controlled piezoelectric devices and systems.Unlike most of previous reports,where enhanced piezoelectric performance is typically accompanied by large hysteresis in lead-/lead-free-based ceramics,in this work,we report a reconstructed relaxor ferroelectric composition in 0.68Pb(Mg_(1/3)Nb_(2/3))O3-0.32PbTiO_(3)(0.68PMN-0.32PT)ceramics through the introduction of(Bi_(0.5)Na_(0.5))ZrO(BNZ)to simultaneously achieve low strain hysteresis(~7.68%),superior piezoelectricity(~1040 pC·N^(-l)),and an electric field induced strain of 0.175%.Our work not only paves the way to simultaneously large piezoelectricity and negligible strain hysteresis in ceramic systems,but also lays the foundation for the further development of novel functional materials.

Catalytic activity of flame-synthesized Pd/TiO2 for the methane oxidation following hydrogen pretreatments

A nanocatalyst composed of 10wt% Pd supported on TiO2 was synthesized using one-step flame spray pyrolysis with a highly-quenched premixed stagnation flame.The as-prepared nanoparticles,having a mean diameter of approximately 10nm,were then subjected to isothermal oxidation and reduction in a fixed bed reactor.The potential roles of Pd and PdO as well as possible synergistic effects between these two active species were explored during methane conversion.The lowest light-off temperature T20 was obtained at a Pd ratio of 53% and this result can be reasonably explained based on a surface Pd-PdO site pair mechanism.Additionally,differences in the hysteresis behavior during methane oxidation were noted throughout a heating-cooling cycle over the temperature range of 200-600℃,such that the degree of hysteresis was strongly correlated with the Pd ratio.

Boosting the capability of Li_(2)C_(2)O_(4)as cathode pre-lithiation additive for lithium-ion batteries

Li_(2)C_(2)O_(4),with a high theoretical capacity of 525 mAh·g^(−1)and good air stability,is regarded as a more attractive cathode prelithiation additive in contrast to the reported typical inorganic pre-lithiation compounds which are quite air sensitive.However,its obtained capacity is much lower than the theoretical value and its delithiation potential(>4.7 V)is too high to match with the most commercial cathode materials,which greatly impedes its practical application.Herein,we greatly improve the pre-lithiation performance of Li_(2)C_(2)O_(4)as cathode additive with fulfilled capacity at a much-reduced delithiation voltage,enabling its wide applicability for typical commercial cathodes.We increase the capacity of Li_(2)C_(2)O_(4)from 436 to 525 mAh·g^(−1)by reducing its particle size.Through optimizing the types of conductive additives,introducing nano-morphological NiO,MnO2,etc.as catalysts,and innovatively designing a bilayer electrode,the delithiation potential of Li_(2)C_(2)O_(4)is successfully reduced from 4.778 to 4.288 V.We systematically study different particle size,conductive additives,and catalysts on the delithiation behavior of Li_(2)C_(2)O_(4).Finally,it is applied to pre-lithiate the hard carbon anode,and it is found that Li_(2)C_(2)O_(4)could effectively increase the capacity of the full cell from 79.0 to 140.0 mAh·g^(−1)in the first cycle.In conclusion,our study proves that improving the reactivity is an effective strategy to boost the pre-lithiation of Li_(2)C_(2)O_(4).

The crystallographic texture and dependent mechanical properties of the CrCoNi medium-entropy alloy by laser remelting strategy

Laser remelting(LR)has attracted widespread attention in recent years as an effective method to reduce internal defects and improve the surface quality of additively manufactured(AM)parts.In the present study,three different LR inter-layer scanning strategies(LR0,LR90 and LR45)and their effects on the porosity,microstructure,crystallographic texture and related mechanical properties of parts have been studied.Optical microscope,X-ray diffraction,and scanning electron microscope were used as characterization tools.In the LR90 sample,it shows obvious{111}<110>texture and strong<111>preferred orientation along the scanning direction(SD),while the 0°offset and the 45°rotation of LR scanning strategy form a finer microstructure and weak crystallographic texture.Meanwhile,the mechanical properties of the LR sample are improved compared with the sample only by laser metal deposition(LMD),and a combination of higher strength and optimal uniform elongation is obtained in the LR45 sample.The overall results show that a reasonable LR scanning strategy can reduce the anisotropy of AM parts and improve their mechanical properties.

Sequence homolog-based molecular engineering for shifting the enzymatic pH optimum

Cell-free synthetic biology system organizes multiple enzymes(parts)from different sources to implement unnatural catalytic functions.Highly adaption between the catalytic parts is crucial for building up efficient artificial biosynthetic systems.Protein engineering is a powerful technology to tailor various enzymatic properties including catalytic efficiency,substrate specificity,temperature adaptation and even achieve new catalytic functions.However,altering enzymatic pH optimum still remains a challenging task.In this study,we proposed a novel sequence homolog-based protein engineering strategy for shifting the enzymatic pH optimum based on statistical analyses of sequence-function relationship data of enzyme family.By two statistical procedures,artificial neural networks(ANNs)and least absolute shrinkage and selection operator(Lasso),five amino acids in GH11 xylanase family were identified to be related to the evolution of enzymatic pH optimum.Site-directed mutagenesis of a thermophilic xylanase from Caldicellulosiruptor bescii revealed that four out of five mutations could alter the enzymatic pH optima toward acidic condition without compromising the catalytic activity and thermostability.Combination of the positive mutants resulted in the best mutant M31 that decreased its pH optimum for 1.5 units and showed increased catalytic activity at pH<5.0 compared to the wild-type enzyme.Structure analysis revealed that all the mutations are distant from the active center,which may be difficult to be identified by conventional rational design strategy.Interestingly,the four mutation sites are clustered at a certain region of the enzyme,suggesting a potential“hot zone”for regulating the pH optima of xylanases.This study provides an efficient method of modulating enzymatic pH optima based on statistical sequence analyses,which can facilitate the design and optimization of suitable catalytic parts for the construction of complicated cell-free synthetic biology systems.

Lower bound of local quantum uncertainty for high-dimensional bipartite quantum systems

Quantum correlations are of fundamental importance in quantum phenomena and studies related to quantum information processing. The measurement of quantum correlations is a central challenge. A recently proposed measure of quantum correlations,local quantum uncertainty(LQU), satisfies all the physical requirements as a measure of quantum correlations. This study derives a closed-form lower bound of the LQU for arbitrary-dimensional bipartite quantum states using operator relaxation. We also compared the lower bound with the optimized LQU for several typical sets of quantum states. The results show that the lower bound is near to the optimized LQU for three-dimensional bipartite quantum systems.