Bio-inspired synthesis of nanomaterials and smart structures for electrochemical energy storage and conversion

Traditional synthetic methodologies are confronted with great challenges to fabricate complex nanomaterials with delicate design,high efficiency and excellent sustainability.During the past decade,bio-inspired synthesis has been extensively applied as an effective and efficient strategy for the fabrication of nanomaterials and nanostructures.Mimicking electrode materials at nanoscale in the aspect of either structure or functionality has been receiving surging interest because of their incomparable advantages and outperforming properties.In this review,we summarize the recent progresses on bio-inspired synthesis of nanomaterials and smart structures in the field of energy storage and conversion.Firstly,an overall introduction of bio-inspired synthetic strategies will be presented,with focus on the biotemplates and bio-resources.Following that,a library of complex mimicking structures featured by high-order,hierarchical porosity,or bionic function are introduced,with discussion on their chemical and physical properties associated with the structure.The enhanced electrochemical properties such as energy density,cycling stability,etc.in different electrochemical systems will be also discussed.At last,we will expand the perspectives regarding the advantages and limitations of bioinspired strategy and possible solutions in the future.

Synthesis of Multi-component Mass-exchange Networks

This paper presents a superstructure-based formulation for the synthesis of mass-exchange networks (MENs) considering multiple components. The superstructure is simplified by directly using the mass separation agents (MSA) from their sources, and therefore the automatic synthesis of the multi-component system involved in the MENs can be achieved without choosing a 'key-component' either for the whole process or the mass exchangers. A mathematical model is proposed to carry out the optimization process. The concentrations, flow rates, matches and unit operation displayed in the obtained network constitute the exact representation of the mass exchange process in terms of all species in the system. An example is used to illustrate and demonstrate the application of the proposed method.

Preparation of PVC/PVP composite polymer membranes via phase inversion process for water treatment purposes

In this work, new composite membranes were successfully prepared via phase inversion technique using polyvinyl chloride(PVC) and polyvinylpyrrolidone(PVP) as polymers and tetrahydrofuran(THF) and N-methyl-2-pyrrolidone(NMP) as solvents. The prepared membranes have been characterized by scanning electron microscope(SEM), and fourier transforms infrared spectroscopy(FTIR). The scanning electron microscope results prove that the prepared membranes are smooth and their pores are distributed throughout the whole surface and bulk body of the membrane without any visible cracks. The stress–strain mechanical test showed an excellent mechanical behavior enhanced by the presence of PVP in the prepared membranes. The membranes performance results showed that the salt rejection reached 98% with a high flux. This, in turn, makes the prepared membranes can be applied for sea and brackish water treatment through membrane distillation technology.

Machine learning for molecular thermodynamics

Thermodynamic properties of complex systems play an essential role in developing chemical engineering processes.It remains a challenge to predict the thermodynamic properties of complex systems in a wide range and describe the behavior of ions and molecules in complex systems.Machine learning emerges as a powerful tool to resolve this issue because it can describe complex relationships beyond the capacity of traditional mathematical functions.This minireview will summarize some fundamental concepts of machine learning methods and their applications in three aspects of the molecular thermodynamics using several examples.The first aspect is to apply machine learning methods to predict the thermodynamic properties of a broad spectrum of systems based on known data.The second aspect is to integer machine learning and molecular simulations to accelerate the discovery of materials.The third aspect is to develop machine learning force field that can eliminate the barrier between quantum mechanics and all-atom molecular dynamics simulations.The applications in these three aspects illustrate the potential of machine learning in molecular thermodynamics of chemical engineering.We will also discuss the perspective of the broad applications of machine learning in chemical engineering.

The corrosion of AA2037 aluminum alloy in alkaline aqueous solution studied using slow positron beam spectroscopy

Corrosion behavior of AA2037 T8 Al alloy in a1 M Na OH aqueous solution was investigated using slow positron beam, together with microscopy techniques and electrochemical tests. The alloy was homogenized at 510℃ for 2 h and 30 s, respectively, before final peak aging, so that one Sample A had more dispersoids than Sample B after homogenization. It was found that S parameter of the Doppler-broadened annihilation was significantly decreased near the surface in both samples in the alkaline solution. With increasing the dissolution time,Sample A showed a slower decrease rate than Sample B,which might imply that the preexistence of more dispersoids might hinder the corrosion process in Sample A.Scanning electron microscopy and atomic force microscopy observations found that the surfaces of both samples were uniformly thinned due to intense chemical dissolution by the attack of OH-. With increasing the dissolution time,Sample B was corroded more substantially and produced more and larger pits in a short dissolution time than Sample A. Furthermore, polarization curves showed that Sample A had a lower corrosion current and corrosion rate than Sample B, which revealed that the presence of the dispersoids was responsible for the better corrosion resistance in the alloy.

颗粒内传质参数作为工具用于催化剂颗粒的设计(英文)

A chromatographic method and a dynamic Wicke-Kallenbach method (DMWK) were used to determine the diffusion characteristics of two industrial copper containing catalysts. The first catalyst was used in nitrobenzene hydrogenation to aniline and the second was used in a low temperature water-gas shift reaction. Experimental results show that application of these two methods leads to similar results. Experimental data obtained allow for monitoring changes in the texture of the catalyst grains and intraparticle diffusivity of gaseous reagents at different states of the catalyst activity and use, which can be used as criteria for designing optimal industrial catalyst pellets.

Metastable hybridized structure transformation in amorphous carbon films during friction-A study combining experiments and MD simulation

Amorphous carbon films have attracted substantial interest due to their exceptional mechanical and tribological properties.Previous studies revealed that the amorphous carbon films exhibited lower coefficient of friction(COF)because of the transformation in bond structure from sp^(3)-C to sp^(2)-C during friction processes.However,the mechanism for such a transformation during friction is not well understood.This study is conducted to get an insight into the metastable transformation in amorphous carbon film during friction by means of experiments and molecular dynamics(MD)simulation.Relevant wear tests showed that wear of the film changed from an abrasive wear mode to a mixture of abrasion and adhesive wear,resulting in a decrease in growth rate of the wear rate after the running-in stage.It is worth noting that the sp^(3)-C atoms were increased during the running-in stage when the films contained lower sp^(3)/sp^(2) ratios.However,the formed sp^(3)-C atoms could only be short-lived and gradually transformed to sp^(2)-C atoms with the graphitization generated on the wearing surface of the films.The radial distribution function and translational order parameter indicated that the films'high sp^(3)/sp^(2) ratio led to an increased sp^(2)-C proportion on the wear scar after friction,which caused an increased structural ordering.

Microstructure evolution and mechanical property of Cu-15Ni-8Sn-0.2Nb alloy during aging treatment

Aging treatment of Cu-based alloys is essential to enhance their strength that is desirable for their extensive engineering applications in electrical industry,whereas the underlying mechanism of strengthening is essential for massive manufacturing of these alloys.Here,the microstructure evolution of a supersaturated solid solution Cu-15Ni-8Sn-0.2Nb alloy aged at 400℃for different time was characterized at atomic scale using state-of-the-art transmission electron microscopy(TEM)and the corresponding mechanical property was also measured.The results reveal that the modulated structure,DO_(22)/L1_(2)ordering,and discontinuous precipitation(DP)appeared in the advances of aging time.At the early stage of aging treatment,component modulation waves and satellite spots appeared from spinodal decomposition and the modulation wavelength was identified in the range of 1-7 nm.Subsequently the modulated structures formed-poor-rich solute regions,of which DO22ordering was present in the Ni-poor region while L1_(2)ordering appeared in the Ni-rich region.The sequence of ordering precipitates was further verified by density functional theory(DFT)simulations.Furthermore,orientation relationships and interfacial structures between DO_(22),L1_(2)phases and the parent matrix were determined.The measured hardness of alloy reached a maximum value of 335 HV after aging for 120 min due to the coherence between the two ordering phases and matrix.These results illustrated the importance of aging on structural evolution and mechanical property of Cu-15Ni-8Sn alloy at various heat treatment stages,which could potentially help in manufacturing promising alloys for their extensive engineering applications.

纯Al和AA2037铝合金腐蚀相关缺陷的正电子湮没研究

应用慢正电子束多普勒展宽技术研究了纯Al和AA2037铝合金与腐蚀相关的缺陷.慢正电子束多普勒展宽测量是通过改变正电子的能量,测量正电子湮没的多普勒展宽谱,分析得到了不同正电子能量的S参数和S-E曲线,然后对S-E曲线进行了分析和处理以得到材料表面及近表面的缺陷真实分布.实验结果表明,纯Al与在1mol/LNaOH溶液中腐蚀引起了纳米尺度界面缺陷的产生,导致S参数明显上升;而水淬AA2037铝合金腐蚀后引起S参数明显下降,其原因可能是Cu在氧化层与基体界面富集.通过原子力显微镜(AFM)观察证实了纯Al样品表面经过腐蚀后有大量几百纳米大小的孔洞产生,而AA2037铝合金中只有少量的孔洞产生.

AA2037新型连铸铝合金热轧板退火的正电子湮没研究

应用正电子湮没等技术对AA2037连铸铝合金热轧板不同温度退火下空位-溶质相互作用及沉淀相进行了研究,研究表明:室温时效形成的主要是空位-铜复合体以及空位-镁-铜复合体;温度为200℃退火时由于过渡相的形成正电子平均寿命出现峰值,符合多普勒展宽谱的商谱中观察到锰信号的存在,表明形成了空位-镁-锰复合体或过渡相中可能存在锰;温度高于250℃时,随着过渡相变粗、溶解,锰信号消失,而铜信号增强,在350℃后铜信号达到饱和,温度为450℃左右时,稳定相形成.

新型AA2037连铸轧铝合金高温沉淀相的正电子湮没研究

采用正电子湮没寿命谱和符合多普勒展宽谱方法对AA2037连铸轧铝合金热轧板和70%冷轧板高温(约470℃)退火的沉淀相进行了研究.结果表明,正电子平均寿命随退火时间延长而减小.其原因是由于热轧或冷轧形变导致的空位、位错等缺陷的回复和再结晶;另一方面由于随退火时间延长沉淀相不断析出,符合多普勒展宽曲线出现明显的铜元素、锰元素的特征,并且沉淀相越多,信号越明显.这证实了沉淀相(T相)中存在铜元素和锰元素.

Infuence of elemental composition in environmental impacts of steel

The environmental behavior of four steels was analyzed.In the operation phase of concentrating solar power plants,steels withstand high temperature because of its contact with molten salts.Hence,choosing the steel type for the molten salt tanks remains a great challenge.In the cold tank,carbon steel is usually used although an approach with low chromium content steel is being studied for these applications.Likewise,in high temperature applications,such as hot store tank,austenitic stainless steel is the most frequent choice.However,ferritic steel is being considered as a promising material in these applications.As many researchers studied the steel technical properties without considering their environmental damages,this work aimed to introduce the environmental aspects into the material choice by using the life cycle assessment technique.On one hand,the results showed the environmental adequacy of carbon steel against low chromium content steel.On the other hand,the results obtained in those steels suitable in high temperature application revealed signifcant environmental benefts from the ferritic steel instead of the austenitic steel.

Microstructure Characterization of Early Corrosion Behavior of AM60B Magnesium Alloys

The microstructures and corrosion behavior of AM60B magnesium alloys, produced by both high-pressure die casting （HPDC） and super vacuum die casting （SVDC） processes, were investigated by a combination of X-ray diffraction （XRD）, scanning electron microscopy （SEM）, and slow positron beam technique. XRD confirmed that calcium carbonate （CaCO3） deposited on the surface of alloys during the early stages of corrosion, and the deposition rate of CaCO3 for SVDC with corrosion time was slower than that of HPDC. SEM observation found that the -phases in the skin surface of SVDC alloy had a greater volume fraction and more continuous distribution than that of HPDC alloy, leading to lower volume fraction of CaCO3 deposited on surface of SVDC alloy for the same corrosion time. The slow positron beam Doppler broadening measurement revealed that the thickness of surface corrosion layer increased with corrosion time. Compared with HPDC alloy, the increase rate of thickness for SVDC alloy is slower, which implied that SVDC alloy exhibited a better corrosion resistance than HPDC alloy.