Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Predicting the probability distribution of Martian rocks mechanical property based on microscale rock mechanical experiments and accurate grain-based modeling

The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.

An MPI parallel DEM-IMB-LBM framework for simulating fluid-solid interaction problems

The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive computational costs.To overcome this limitation,a message passing interface(MPI)parallel DEM-IMB-LBM framework is proposed aimed at enhancing computation efficiency.This framework utilises a static domain decomposition scheme,with the entire computation domain being decomposed into multiple subdomains according to predefined processors.A detailed parallel strategy is employed for both contact detection and hydrodynamic force calculation.In particular,a particle ID re-numbering scheme is proposed to handle particle transitions across sub-domain interfaces.Two benchmarks are conducted to validate the accuracy and overall performance of the proposed framework.Subsequently,the framework is applied to simulate scenarios involving multi-particle sedimentation and submarine landslides.The numerical examples effectively demonstrate the robustness and applicability of the MPI parallel DEM-IMB-LBM framework.

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth.Resolving this issue will be key to achieving high-performance lithium metal batteries(LMBs).Herein,we construct a lithium nitrate(LiNO_(3))-implanted electroactiveβphase polyvinylidene fluoride-co-hexafluoropropylene(PVDF-HFP)crystalline polymorph layer(PHL).The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels.These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes,decreasing the growth of lithium dendrites.The stretched molecular channels can also accelerate the transport of Li ions.The combined effects enable a high Coulombic efficiency of 97.0%for 250 cycles in lithium(Li)||copper(Cu)cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm^(-2)with ultrahigh Li utilization of 50%.Furthermore,the full cell coupled with PHL-Cu@Li anode and Li Fe PO_(4) cathode exhibits long-term cycle stability with high-capacity retention of 95.9%after 900 cycles.Impressively,the full cell paired with LiNi_(0.87)Co_(0.1)Mn_(0.03)O_(2)maintains a discharge capacity of 170.0 mAh g^(-1)with a capacity retention of 84.3%after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83.This facile strategy will widen the potential application of LiNO_(3)in ester-based electrolyte for practical high-voltage LMBs.

A particle-resolved heat-particle-fluid coupling model by DEM-IMB-LBM

Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level.In this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles.The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows.To facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice units.Then,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled technique.To further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are performed.Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.

Valorization of Camellia oleifera oil processing byproducts to value-added chemicals and biobased materials: A critical review

The C.oleifera oil processing industry generates large amounts of solid wastes,including C.oleifera shell(COS)and C.oleifera cake(COC).Distinct from generally acknowledged lignocellulosic biomass(corn stover,bamboo,birch,etc.),Camellia wastes contain diverse bioactive substances in addition to the abundant lignocellulosic components,and thus,the biorefinery utilization of C.oleifera processing byproducts involves complicated processing technologies.This reviewfirst summarizes various technologies for extracting and converting the main components in C.oleifera oil processing byproducts into value-added chemicals and biobased materials,as well as their potential applications.Microwave,ultrasound,and Soxhlet extractions are compared for the extraction of functional bioactive components(tannin,flavonoid,saponin,etc.),while solvothermal conversion and pyrolysis are discussed for the conversion of lignocellulosic components into value-added chemicals.The application areas of these chemicals according to their properties are introduced in detail,including utilizing antioxidant and anti-in-flammatory properties of the bioactive substances for the specific application,as well as drop-in chemicals for the substitution of unrenewable fossil fuel-derived products.In addition to chemical production,biochar fabricated from COS and its applications in thefields of adsorption,supercapacitor,soil remediation and wood composites are comprehensively reviewed and discussed.Finally,based on the compositions and structural characteristics of C.oleifera byproducts,the development of full-component valorization strategies and the expansion of the appli-cationfields are proposed.

Deformable Catalytic Material Derived from Mechanical Flexibility for Hydrogen Evolution Reaction

Deformable catalytic material with excellent flexible structure is a new type of catalyst that has been applied in various chemical reactions,especially electrocatalytic hydrogen evolution reaction(HER).In recent years,deformable catalysts for HER have made great progress and would become a research hotspot.The catalytic activities of deformable catalysts could be adjustable by the strain engineering and surface reconfiguration.The surface curvature of flexible catalytic materials is closely related to the electrocatalytic HER properties.Here,firstly,we systematically summarized self-adaptive catalytic performance of deformable catalysts and various micro–nanostructures evolution in catalytic HER process.Secondly,a series of strategies to design highly active catalysts based on the mechanical flexibility of lowdimensional nanomaterials were summarized.Last but not least,we presented the challenges and prospects of the study of flexible and deformable micro–nanostructures of electrocatalysts,which would further deepen the understanding of catalytic mechanisms of deformable HER catalyst.

Dynamics and synchronization in a memristor-coupled discrete heterogeneous neuron network considering noise

Research on discrete memristor-based neural networks has received much attention.However,current research mainly focuses on memristor–based discrete homogeneous neuron networks,while memristor-coupled discrete heterogeneous neuron networks are rarely reported.In this study,a new four-stable discrete locally active memristor is proposed and its nonvolatile and locally active properties are verified by its power-off plot and DC V–I diagram.Based on two-dimensional(2D)discrete Izhikevich neuron and 2D discrete Chialvo neuron,a heterogeneous discrete neuron network is constructed by using the proposed discrete memristor as a coupling synapse connecting the two heterogeneous neurons.Considering the coupling strength as the control parameter,chaotic firing,periodic firing,and hyperchaotic firing patterns are revealed.In particular,multiple coexisting firing patterns are observed,which are induced by different initial values of the memristor.Phase synchronization between the two heterogeneous neurons is discussed and it is found that they can achieve perfect synchronous at large coupling strength.Furthermore,the effect of Gaussian white noise on synchronization behaviors is also explored.We demonstrate that the presence of noise not only leads to the transition of firing patterns,but also achieves the phase synchronization between two heterogeneous neurons under low coupling strength.

金属螯合蛋白异源表达提高E.coli对镉的生物吸附能力:修复潜力和潜在机制

镉(Cd)作为一种生物非必需的有毒重金属,通过自然排放或人类活动进入环境,对人类健康构成威胁。在微生物中高效表达金属螯合蛋白(MCP)可以增强生物对Cd的吸附能力。本研究构建了mcp基因编码的MCP的异源表达体系(GEM01),探究了其对Cd的吸附效果和潜在机制。结果表明,Cd^(2+)调控GEM01中mcp基因丰度,mcp基因的表达增加了Cd^(2+)的生物吸附能力(8.09 mg/g,比对照组高2.32倍)。在GEM01自溶过程中Cd^(2+)的保留率为87.87%。荧光光谱和分子动力学模拟表明了Cd^(2+)与MCP之间存在较强的相互作用且Cd^(2+)影响了MCP的二级结构。FT-IR证明了MCP中的官能团(如羧基、甲基和亚甲基)参与了MCP与Cd^(2+)的相互作用。分子对接进一步表明MCP蛋白表面的一些极性和亲水残基(如天冬酰胺、谷氨酰胺、丝氨酸和组氨酸)通过静电引力与Cd^(2+)结合。本研究为MCP介导的Cd^(2+)生物修复提供了新的见解,为微生物修复重金属污染提供了基因资源。

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other.The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity.In this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored.We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis changed.The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the neurons.In addition,by increasing the coupling strength of memristor synapses,synchronization performance is promoted.The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

Dynamical behavior of memristor-coupled heterogeneous discrete neural networks with synaptic crosstalk

Synaptic crosstalk is a prevalent phenomenon among neuronal synapses,playing a crucial role in the transmission of neural signals.Therefore,considering synaptic crosstalk behavior and investigating the dynamical behavior of discrete neural networks are highly necessary.In this paper,we propose a heterogeneous discrete neural network(HDNN)consisting of a three-dimensional KTz discrete neuron and a Chialvo discrete neuron.These two neurons are coupled mutually by two discrete memristors and the synaptic crosstalk is considered.The impact of crosstalk strength on the firing behavior of the HDNN is explored through bifurcation diagrams and Lyapunov exponents.It is observed that the HDNN exhibits different coexisting attractors under varying crosstalk strengths.Furthermore,the influence of different crosstalk strengths on the synchronized firing of the HDNN is investigated,revealing a gradual attainment of phase synchronization between the two discrete neurons as the crosstalk strength decreases.

Multiple mixed state variable incremental integration for reconstructing extreme multistability in a novel memristive hyperchaotic jerk system with multiple cubic nonlinearity

Memristor-based chaotic systems with infinite equilibria are interesting because they generate extreme multistability.Their initial state-dependent dynamics can be explained in a reduced-dimension model by converting the incremental integration of the state variables into system parameters.However,this approach cannot solve memristive systems in the presence of nonlinear terms other than the memristor term.In addition,the converted state variables may suffer from a degree of divergence.To allow simpler mechanistic analysis and physical implementation of extreme multistability phenomena,this paper uses a multiple mixed state variable incremental integration(MMSVII)method,which successfully reconstructs a four-dimensional hyperchaotic jerk system with multiple cubic nonlinearities except for the memristor term in a three-dimensional model using a clever linear state variable mapping that eliminates the divergence of the state variables.Finally,the simulation circuit of the reduced-dimension system is constructed using Multisim simulation software and the simulation results are consistent with the MATLAB numerical simulation results.The results show that the method of MMSVII proposed in this paper is useful for analyzing extreme multistable systems with multiple higher-order nonlinear terms.

磁性石化污泥生物炭对土壤镉污染修复研究

生物炭普遍被认为是一种很有前途的土壤修复材料,特别是因为它能够通过吸附作用而降低土壤中镉(Cd)的生物有效性。然而,长期修复过程中可能会导致Cd从稳定状态释放出来,这使得生物炭作为Cd吸附剂的回收逐渐得到关注。本研究旨在利用含铁石油污泥一步合成磁性生物炭,研究其对Cd的吸附效率、钝化机理及其在土壤中的应用效果。结果表明,通过缺氧热解可直接将石化污泥废弃物资源化成磁性生物炭(PSMBCs),且PSMBCs在水/土壤中具有良好的回收性能。具体来说,由于其具有表面矿化和阳离子-π配位作用,本研究制备的PSMBCs对Cd的吸附能力为18.4~29.8 mg/g。在水稻泥土中施用1.5%PSMBCs 30 d后,生物有效态Cd含量降低85%,且伴随着土壤pH值和溶解有机质的增加。此外,生物炭浸出液对小麦根系伸长无毒性影响。因此,本研究为石化污泥的资源化处理及其对Cd污染土壤的修复提供了技术参考。

Recent progress in ternary mixed matrix membranes for CO_(2) separation

Mixed matrix membranes(MMMs)could combine the advantages of both polymeric membranes and porousfillers,making them an effective alternative to conventional polymer membranes.However,interfacial incompatibility issues,such as the presence of interfacial voids,hardening of polymer chains,and blockage of micropores by polymers between common MMMsfillers and the polymer matrix,currently limit the gas sep-aration performance of MMMs.Ternary phase MMMs(consisting of afiller,an additive,and a matrix)made by adding a third compound,usually functionalized additives,can overcome the structural problems of binary phase MMMs and positively impact membrane separation performance.This review introduces the structure and fabrication processes for ternary MMMs,categorizes various nanofillers and the third component,and summarizes and analyzes in detail the CO_(2) separation performance of newly developed ternary MMMs based on both rubbery and glassy polymers.Based on this separation data,the challenges of ternary MMMs are also discussed.Finally,future directions for ternary MMMs are proposed.

Optical spectrum of ferrovalley materials:A case study of Janus H-VSSe

As opposed to the prototypical MoS2 with centroasymmetry,Janus ferrovalley materials such as H-VSSe are less symmetric with the mirror symmetry and time reversal symmetry broken,and hence possess spontaneous valley polarization and strong ferroelasticity.The optical transition is an important means to excite the valley carriers.We investigate the optical spectrum of H-VSSe by using the many-body perturbation-based GW approach and solving the Bethe–Salpeter equation(BSE)to include the electron–hole interactions.It is found that after the GW correction,the band gaps of the quasiparticle bands are much larger than those obtained by the normal density functional theory.The system is ferromagnetic and the valley gaps become non-degenerate due to spin–orbit coupling(SOC).The position of the lowest BSE peak is much lower than the quasiparticle band gap,indicating that the excitonic effect is large.The peak is split into two peaks by the SOC.The binding energy difference between these two BSE peaks is about the same as the difference between the inequivalent valley gaps.Our results show that in Janus H-VSSe the two lowest exciton peaks are from the two inequivalent valleys with different gaps,in contrast to the A and B exciton peaks of MoS2 which are from the same valley.

Stable and reversible zinc metal anode with fluorinated graphite nanosheets surface coating

A highly stable zinc metal anode modified with a fluorinated graphite nanosheets(FGNSs)coating was designed.The porous structure of the coating layer effectively hinders lateral mass transfer of Zn ions and suppresses dendrite growth.Moreover,the high electronegativity exhibited by fluorine atoms creates an almost superhydrophobic solid-liquid interface,thereby reducing the interaction between solvent water and the zinc substrate.Consequently,this leads to a significant inhibition of hydrogen evolution corrosion and other side reactions.The modified anode demonstrates exceptional cycling stability,as symmetric cells exhibit sustained cycling for over 1400 h at a current density of 5 mA/cm^(2).Moreover,the full cells with NH_(4)V_(4)O_(10)cathode exhibit an impressive capacity retention rate of 92.2%after undergoing 1000 cycles.

用于钎焊C/C复合材料的稀土改性还原氧化石墨烯增强AgCuTi复合钎料

为了解决钎焊接头中脆性化合物的形成问题,我们设计了一种创新性的稀土改性还原氧化石墨烯增强AgCuTi复合钎料,进而获得了以Ag-Cu共晶为主要组织且脆性化合物生成量合适的钎焊接头。对比分析了有无稀土Ce改性的复合钎料的成分和显微组织,结果表明,经Ce改性后的还原氧化石墨烯在钎料中更加均匀分散。比较了分别采用有无Ce改性的钎料钎焊C/C复合材料-C/C复合材料接头的界面微观结构,并研究了石墨烯含量对接头组织和性能的影响。结果表明,由于经Ce改性的钎料中的还原氧化石墨烯分散性更好,从而细化了焊缝组织,且物相分布更均匀,使得接头的剪切强度明显提高。当石墨烯含量为0.5 wt.%时,使用Ce改性的钎料所得钎焊接头的平均剪切强度最高,为31.82 MPa,提高了50%。

镍/钼复合中间层钎焊连接C/C复合材料和304不锈钢

本文使用在BNi-2或AgCuTi箔片钎料中添加金属中间层(Ni、Mo或Ni/Mo)的方法有效提高了C/C复合材料和304不锈钢真空钎焊接头的强度,并先后对接头的微观结构、连接机理和力学性能进行分析。分析表明,BNi-2+Ni/Mo接头的微观结构包括Cr_(3)C_(2)、Ni(s,s)、Cr_xNi_(y)+MoNi_(4)、MoNi_(4)+Cr_(x)M_(y)和Ni(s,s)+Cr-Fe;AgCuTi+Ni/Mo接头的界面则由TiC、Ag(s,s)+Cu(s,s)、Ni、Ag(s,s)+Cu(s,s)+MoTi、Mo和MoTi+Cu(s,s)+Ag(s,s)构成。有限元模拟结果表明,AgCuTi钎料加持下的镍/钼复合中间层能够有效缓解C/C母材与焊缝界面间的残余应力。室温下BNi-2+Ni/Mo、AgCuTi+Ni、AgCuTi+Mo和AgCuTi+Ni/Mo钎焊接头的平均剪切强度分别为2.57 MPa、10.91 MPa、23.81 MPa和26.77 MPa,有效验证了有限元结果的可靠性。

GLOBAL UNIQUE SOLUTIONS FOR THE INCOMPRESSIBLE MHD EQUATIONS WITH VARIABLE DENSITY AND ELECTRICAL CONDUCTIVITY

We study the global unique solutions to the 2-D inhomogeneous incompressible MHD equations,with the initial data(u0,B0)being located in the critical Besov space■and the initial densityρ0 being close to a positive constant.By using weighted global estimates,maximal regularity estimates in the Lorentz space for the Stokes system,and the Lagrangian approach,we show that the 2-D MHD equations have a unique global solution.

CFD-PBM coupled modeling of the liquid-liquid dispersion characteristics and structure optimization for Kenics static mixer

Kenics static mixers(KSM)are extensively used in industrial mixing-reaction processes by virtue of high mixing efficiency,low power homogenization and easy continuous production.Resolving liquid droplet size and its distribution and thus revealing the dispersion characteristics are of great significance for structural optimization and process intensification in the KSM.In this work,a computational fluid dynamics-population balance model(CFD-PBM)coupled method is employed to systematically investigate the effects of operating conditions and structural parameters of KSM on droplet size and its distribution,to further reveal the liquid-liquid dispersion characteristics.Results indicate that higher Reynolds numbers or higher dispersed phase volume fractions increase energy dissipation,reducing Sauter mean diameter(SMD)of dispersed phase droplets and with a shift in droplet size distribution(DSD)towards smaller size.Smaller aspect ratios,greater blade twist and assembly angles amplify shear rate,leading to smaller droplet size and a narrower DSD in the smaller range.The degree of impact exerted by the aspect ratio is notably greater.Notably,mixing elements with different spin enhance shear and stretching efficiency.Compared to the same spin,SMD becomes 3.7-5.8 times smaller in the smaller size range with a significantly narrower distribution.Taking into account the pressure drop and efficiency in a comprehensive manner,optimized structural parameters for the mixing element encompass an aspect ratio of 1-1.5,a blade twist angle of 180°,an assembly angle of 90°,and interlaced assembly of adjacent elements with different spin.This work provides vital theoretical underpinning and future reference for enhancing KSM performance.