DYNAMIC STABILITY OF SPINDLE BLADE IN RING SPINNING Zhou Bingrong(Department of Mechanical Engineering)

It is discussed that a tangential force T induces a self-excited vibration in the motion ofspindle blades of a ring spinning frame.Depending on the relative magnitude of the tangentialforce compared with the tangential damping force the motion of blade is either stable orunstable.The chief factors causing the self-excited vibration can also be traced from the charac-ter of the experimental locus.

Spontaneous Orientation Polarization of Anisotropic Equivalent Dipoles Harnessed by Entropy Engineering for Ultra‑Thin Electromagnetic Wave Absorber

The synthesis of carbon supporter/nanoscale high-entropy alloys(HEAs)electromagnetic response composites by carbothermal shock method has been identified as an advanced strategy for the collaborative competition engineering of conductive/dielectric genes.Electron migration modes within HEAs as manipulated by the electronegativity,valence electron configurations and molar proportions of constituent elements determine the steady state and efficiency of equivalent dipoles.Herein,enlightened by skin-like effect,a reformative carbothermal shock method using carbonized cellulose paper(CCP)as carbon supporter is used to preserve the oxygencontaining functional groups(O·)of carbonized cellulose fibers(CCF).Nucleation of HEAs and construction of emblematic shell-core CCF/HEAs heterointerfaces are inextricably linked to carbon metabolism induced by O·.Meanwhile,the electron migration mode of switchable electronrich sites promotes the orientation polarization of anisotropic equivalent dipoles.By virtue of the reinforcement strategy,CCP/HEAs composite prepared by 35%molar ratio of Mn element(CCP/HEAs-Mn_(2.15))achieves efficient electromagnetic wave(EMW)absorption of−51.35 dB at an ultra-thin thickness of 1.03 mm.The mechanisms of the resulting dielectric properties of HEAs-based EMW absorbing materials are elucidated by combining theoretical calculations with experimental characterizations,which provide theoretical bases and feasible strategies for the simulation and practical application of electromagnetic functional devices(e.g.,ultra-wideband bandpass filter).

Reduced graphene oxide-grafted bovine serum albumin/bredigite nanocomposites with high mechanical properties and excellent osteogenic bioactivity for bone tissue engineering

The optimization of the scaffolds to provide a suitable matrix and accelerate the regeneration process is vital for bone tissue engineering.However,poor mechanical and biological characteristics remain the primary challenges that must be addressed.For example,although bredigite(Br)has shown great potential for application in bone tissue engineering,it easily fails in replacement.In the present work,these challenges are addressed by reinforcing the Br matrix with nanosheets of graphene oxide(rGO)that have been reduced by bovine serum albumin(BSA)in order to enhance the mechanical properties and biological behavior.The reduction of graphene oxide by BSA improves the water stability of the nanosheets and provides an electrostatic interaction between theBSA-rGO nanosheets and theBr particles.The high thermal conductivity of theBSA-rGO nanosheets decreases the porosity of the Br by transferring heat to the core of the tablet.Furthermore,the addition of BSA-rGO nanosheets into the Br matrix enhances the adhesion of G-292 cells on the surface of the tablets.These findings suggest that the tablet consisting of BSA-rGO-reinforced Br has encouraging potential for application in bone tissue engineering.

Spark Plasma Sintering of Mg-based Alloys:Microstructure,Mechanical Properties,Corrosion Behavior,and Tribological Performance

Within the past ten years,spark plasma sintering(SPS)has become an increasingly popular process for Mg manufacturing.In the SPS process,interparticle diffusion of compressed particles is rapidly achieved due to the concept of Joule heating.Compared to traditional and additive manufacturing(AM)techniques,SPS gives unique control of the structural and microstructural features of Mg components.By doing so,their mechanical,tribological,and corrosion properties can be tailored.Although great advancements in this field have been made,these pieces of knowledge are scattered and have not been contextualized into a single work.The motivation of this work is to address this scientific gap and to provide a groundwork for understanding the basics of SPS manufacturing for Mg.To do so,the existing body of SPS Mg literature was first surveyed,with a focus on their structural formation and degradation mechanisms.It was found that successful Mg SPS fabrication highly depended on the processing temperature,particle size,and particle crystallinity.The addition of metal and ceramic composites also affected their microstructural features due to the Zener pinning effect.In degradative environments,their performance depends on their structural features and whether they have secondary phased composites.In industrial applications,SPS'd Mg was found to have great potential in biomedical,hydrogen storage,battery,automotive,and recycling sectors.The prospects to advance the field include using Mg as a doping agent for crystallite size refinement and using bulk metallic Mg-based glass powders for amorphous SPS components.Despite these findings,the interactions of multi-composites on the processing-structure-property relationships of SPS Mg is not well understood.In total,this work will provide a useful direction in the SPS field and serve as a milestone for future Mg-based SPS manufacturing.

Mechanical and damping performances of TPMS lattice metamaterials fabricated by laser powder bed fusion

Lattice metamaterials based on three-period minimum surface(TPMS)are an effective means to achieve lightweight and high-strength materials which are widely used in various fields such as aerospace and ships.However,its vibration and noise reduction,and damping properties have not been fully studied.Therefore,in this study,the TPMS structures with parameterization were designed by the method of surface migration,and the TPMS structures with high forming quality was manufactured by laser powder bed fusion(LPBF).The mechanical properties and energy absorption characteristics of the beam and TPMS structures were studied and compared by quasi-static compression.The modal shapes of the beam lattice structures and TPMS structures were obtained by the free modal analysis,and the damping properties of two structures were obtained by modal tests.For the two structures after heat treatment with the same porosity of 70%,the yield strength of the beam lattice structure reaches 40.76 MPa,elastic modulus is 20.38 GPa,the energy absorption value is 32.23 MJ·m^(-3),the damping ratio is 0.52%.The yield strength,elastic modulus,energy absorption value,and damping ratio of the TPMS structure are 50.74 MPa,25.37 GPa,47.34 MJ·m^(-3),and 0.99%,respectively.The results show that TPMS structures exhibit more excellent mechanical properties and energy absorption,better damping performance,and obvious advantages in structural load and vibration and noise reduction compared with the beam lattice structures under the same porosity.

Influence of layer thickness on formation quality,microstructure,mechanical properties,and corrosion resistance of WE43 magnesium alloy fabricated by laser powder bed fusion

Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.

Assessing Mechanical Properties of Natural Fibre Reinforced Composites for Engineering Applications

Mechanical properties of ukam, banana, sisal, coconut, hemp and e-glass fibre reinforced laminates were evaluated to assess the possibility of using it as new material in engineering applications. Samples were fabricated by the hand lay-up process (30:70 fibre and matrix ratio by weight) and the properties evaluated using the INSTRON material testing system. The mechanical properties were tested and showed that glass laminate has the maximum tensile strength of 63 MPa, bending strength of 0.5 MPa, compressive strength of 37.75 MPa and the impact strength of 17.82 J/m2. The ukam plant fibre laminate has the maximum tensile strength of 16.25 MPa and the impact strength of 9.8J/m among the natural fibres;the sisal laminate has the maximum compressive strength of 42 MPa and maximum bending strength of 0.0036 MPa among the natural fibres. Results indicated that natural fibres are of interest for low-cost engineering applications and can compete with artificial glass fibres (E-glass fibre) when a high stiffness per unit weight is desirable. Results also indicated that future research towards significant improvements in tensile and impact strength of these types of composites should focus on the optimisation of fibre strength rather than interfacial bond strength.

From VIB‑to VB‑Group Transition Metal Disulfides:Structure Engineering Modulation for Superior Electromagnetic Wave Absorption

The laminated transition metal disulfides(TMDs),which are well known as typical two-dimensional(2D)semiconductive materials,possess a unique layered structure,leading to their wide-spread applications in various fields,such as catalysis,energy storage,sensing,etc.In recent years,a lot of research work on TMDs based functional materials in the fields of electromagnetic wave absorption(EMA)has been carried out.Therefore,it is of great significance to elaborate the influence of TMDs on EMA in time to speed up the application.In this review,recent advances in the development of electromagnetic wave(EMW)absorbers based on TMDs,ranging from the VIB group to the VB group are summarized.Their compositions,microstructures,electronic properties,and synthesis methods are presented in detail.Particularly,the modulation of structure engineering from the aspects of heterostructures,defects,morphologies and phases are systematically summarized,focusing on optimizing impedance matching and increasing dielectric and magnetic losses in the EMA materials with tunable EMW absorption performance.Milestones as well as the challenges are also identified to guide the design of new TMDs based dielectric EMA materials with high performance.

Development of an In-Situ Composite Doped Coating for Corrosion Protection and Mechanical Properties Enhancements in Process Engineering

Process engineering has been seen as one of the vital tools for improving surface coating phenomena for advance application. In an attempt to improve the mechanical, physical and chemical performance of the steel structure for ex-tended application, Zn-CeO2/ZnCeO2-Al2SiO5 thin film composite was fabri-cated on mild steel using direct electrolytic route. Process variation of Al2SiO5 particulate ranges from 5 to 15 g per litre. The embedded coating was charac-terized using Scanning electron microscope (SEM). The chemical effect of the developed alloy was characterized through linear potentiodynamic polarization experiment and the performances of samples were examined in simulated 3.5% sodium chloride. The microhardness verification study proves that there is sig-nificant improvement in hardness trend. The tribological assessment indicated that there is less plastic deformation as a result of the counter body. In all, Zn-CeO2/Zn-CeO2-Al2SiO5 exhibits good stability, with agglomeration and great built up of crystal at the interface.

Influence of B4C and ZrB2 reinforcements on microstructural,mechanical and wear behaviour of AA 2014 aluminium matrix hybrid composites

Considering their affordability and high strength-to-weight ratio,lightweight aluminium alloys are the subject of intensive research aimed at improving their properties for use in the aerospace industry.This research effort aims to develop novel hybrid composites based on AA 2014 alloy through the use of liquid metallurgy stir casting to reinforce dual ceramic particles of Zirconium Diboride(ZrB_(2))and Boron Carbide(B4C).The weight percentage(wt%)of ZrB_(2) was varied(0,5,10,and 15),while a constant 5 wt%of B4C was maintained during this fabrication.The as-cast samples have been assessed using an Optical Microscope(OM)and a Scanning Electron Microscope(SEM)with Energy Dispersive Spectroscopy(EDS).The properties such as hardness,tensile strength,and wear characteristics of stir cast specimens were assessed to examine the impact of varying weight percentages of reinforcements in AA 2014 alloy.In particular,dry sliding wear behaviour was evaluated considering varied loads using a pin-on-disc tribotester.As the weight%of ZrB_(2) grew and B4C was incorporated,hybrid composites showed higher hardness,tensile strength,and wear resistance.Notably,the incorporation of a cumulative reinforcement consisting of 15 wt%ZrB_(2) and 5 wt%B4C resulted in a significant 31.86%increase in hardness and a 44.1%increase in tensile strength compared to AA 2014 alloy.In addition,it has been detected that wear resistance of hybrid composite pin(containing 20 wt%cumulative reinforcement)is higher than that of other stir cast wear test pins during the whole range of applied loads.Fractured surfaces of tensile specimens showed ductile fracture in the AA 2014 matrix and mixed mode for hybrid composites.Worn surfaces obtained employing higher applied load indicated abrasive wear with little plastic deformation for hybrid composites and dominant adhesive wear for matrix alloy.Hence,the superior mechanical and tribological performance of hybrid composites can be attributed to dual reinforcement particles being dispersed well and the effective transmission of load at this specific composition.

Predicting the Mechanical Behavior of a Bioinspired Nanocomposite through Machine Learning

The bioinspired nacre or bone structure represents a remarkable example of tough,strong,lightweight,and multifunctional structures in biological materials that can be an inspiration to design bioinspired high-performance materials.The bioinspired structure consists of hard grains and soft material interfaces.While the material interface has a very low volume percentage,its property has the ability to determine the bulk material response.Machine learning technology nowadays is widely used in material science.A machine learning model was utilized to predict the material response based on the material interface properties in a bioinspired nanocomposite.This model was trained on a comprehensive dataset of material response and interface properties,allowing it to make accurate predictions.The results of this study demonstrate the efficiency and high accuracy of the machine learning model.The successful application of machine learning into the material property prediction process has the potential to greatly enhance both the efficiency and accuracy of the material design process.

Engineering vascularized organotypic tissues via module assembly

Adequate vascularization is a critical determinant for the successful construction and clinical implementation of complex organotypic tissue models. Currently, low cell and vessel density and insufficient vascular maturation make vascularized organotypic tissue construction difficult,greatly limiting its use in tissue engineering and regenerative medicine. To address these limitations, recent studies have adopted pre-vascularized microtissue assembly for the rapid generation of functional tissue analogs with dense vascular networks and high cell density. In this article, we summarize the development of module assembly-based vascularized organotypic tissue construction and its application in tissue repair and regeneration, organ-scale tissue biomanufacturing, as well as advanced tissue modeling.

Bidirectional rotating direct-current triboelectric nanogenerator with self-adaptive mechanical switching for harvesting reciprocating motion

Amid the growing interest in triboelectric nanogenerators(TENGs)as novel energy-harvesting devices,several studies have focused on direct current(DC)TENGs to generate a stable DC output for operating electronic devices.However,owing to the working mechanisms of conventional DC TENGs,generating a stable DC output from reciprocating motion remains a challenge.Accordingly,we propose a bidirectional rotating DC TENG(BiR-TENG),which can generate DC outputs,regardless of the direction of rotation,from reciprocating motions.The distinct design of the BiR-TENG enables the mechanical rectification of the alternating current output into a rotational-direction-dependent DC output.Furthermore,it allows the conversion of the rotational-direction-dependent DC output into a unidirectional DC output by adapting the configurations depending on the rotational direction.Owing to these tailored design strategies and subsequent optimizations,the BiR-TENG could generate an effective unidirectional DC output.Applications of the BiR-TENG for the reciprocating motions of swinging doors and waves were demonstrated by harnessing this output.This study demonstrates the potential of the BiR-TENG design strategy as an effective and versatile solution for energy harvesting from reciprocating motions,highlighting the suitability of DC outputs as an energy source for electronic devices.

Foundation of Graduate Study in Mechanical EngineeringmAdvanced Dynamics

Dynamics is the foundation of undergraduate study in mechanical engineering. If you are good in dynamics, you will be good on all other courses. Advanced dynamics is the foundation for graduate study. The author taught advanced dynamics for more than ten years, this is the author＇s observation. Why it is so？ Because the course of advanced dynamics covers usually many mathematical fundamentals such as vectors, tensors, matrices and rotation operators; principles and applications in dynamics from particle dynamics to rigid body motion, from small oscillation to vibration of systems with multiple degrees of freedom, the author＇s course covers also special relativity theory. They are very innovative. And they set the foundation for the study of all the graduate courses. Science is always in progress, dynamics is in the same form. Just say a few examples to illustrate the frontier of dynamics： missile shooting missile is important in our defense, the author covered this as an example in particle dynamics. Space ship travels from Earth to Mars is another example. Several rotational motions with different axes can be combined to one through the use of rotation operator. This is important because it usually can save time. All these examples will be included in this paper in some details.

Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based SOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(SVR)were applied to estimate SOH,and root mean square error(RMSE)was used to evaluate and compare the estimation performance.The results showed that the feature selection pipeline can improve SOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and SVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on SOH estimation performance and tries to fill the gap of effective SOH estimation between theoretical study and real dynamic application.

Corrigendum to“Toward stable and highly reversible zinc anodes for aqueous batteries via electrolyte engineering”[J.Energy Chem.83(2023)209–228]

It is regretful that the Acknowledgments part was lost in the final process of publication.The Acknowledgments part should be added as follow.The work described in this paper was supported by the grants from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.16205721).

Microstructure and mechanical behavior of AXM Mg alloy systems—A review

Automobiles are the inevitable mode of transportation.However,increasing fuel prices and carbon dioxide emissions are posing a serious threat to automobile users and the environment.Thus,the development of new lightweight materials has been a key area of research.Magnesium-based commercial alloys(AZ and ZK series alloys)are the lightest among all structural metals.However,there is still a question about the replacement of Aluminum-based alloys due to HCP crystal structure.In this connection,Mg-Al-Ca-Mn(AXM)Mg alloy can be a choice as an alternative to the existing Mg-based commercial alloys for structural applications.It contains(Al,Mg)_(2)Ca,Al_(2)Ca,Mg_(2)Ca,and Al_(8)Mn_(5)as the secondary phases,contributing to the microstructural refinement and property enhancement.However,the formation of those precipitates depends on the amount of Al,Ca,and Mn,especially,the Ca/Al ratio.In addition,the secondary processes influence the grain refinement and property enhancement of texture modifications.Hence,this review article focuses on elaborating on the significance of the Ca/Al ratio for the precipitate formation,secondary process,and texture modifications.The co-segregation behavior of other micro-alloying elements like Cerium,Lanthanum,and Zinc in AXM Mg alloy systems has also been discussed for property enhancement.

Interplay between temperature-dependent strengthening mechanisms and mechanical stability in high-performance austenitic stainless steels

The effects of deformation temperature on the transformation-induced plasticity(TRIP)-aided 304L,twinning-induced plasti-city(TWIP)-assisted 316L,and highly alloyed stable 904L austenitic stainless steels were compared for the first time to tune the mechan-ical properties,strengthening mechanisms,and strength-ductility synergy.For this purpose,the scanning electron microscopy(SEM),electron backscattered diffraction(EBSD),X-ray diffraction(XRD),tensile testing,work-hardening analysis,and thermodynamics calcu-lations were used.The induced plasticity effects led to a high temperature-dependency of work-hardening behavior in the 304L and 316L stainless steels.As the deformation temperature increased,the metastable 304L stainless steel showed the sequence of TRIP,TWIP,and weakening of the induced plasticity mechanism;while the disappearance of the TWIP effect in the 316L stainless steel was also observed.However,the solid-solution strengthening in the 904L superaustenitic stainless steel maintained the tensile properties over a wide temper-ature range,surpassing the performance of 304L and 316L stainless steels.In this regard,the dependency of the total elongation on the de-formation temperature was less pronounced for the 904L alloy due to the absence of additional plasticity mechanisms.These results re-vealed the importance of solid-solution strengthening and the associated high friction stress for superior mechanical behavior over a wide temperature range.

Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.

Generating highly active oxide-phosphide heterostructure through interfacial engineering to break the energy scaling relation toward urea-assisted natural seawater electrolysis

Urea-assisted natural seawater electrolysis is an emerging technology that is effective for grid-scale carbon-neutral hydrogen mass production yet challenging.Circumventing scaling relations is an effective strategy to break through the bottleneck of natural seawater splitting.Herein,by DFT calculation,we demonstrated that the interface boundaries between Ni_(2)P and MoO_(2) play an essential role in the selfrelaxation of the Ni-O interfacial bond,effectively modulating a coordination number of intermediates to control independently their adsorption-free energy,thus circumventing the adsorption-energy scaling relation.Following this conceptual model,a well-defined 3D F-doped Ni_(2)P-MoO_(2) heterostructure microrod array was rationally designed via an interfacial engineering strategy toward urea-assisted natural seawater electrolysis.As a result,the F-Ni_(2)P-MoO_(2) exhibits eminently active and durable bifunctional catalysts for both HER and OER in acid,alkaline,and alkaline sea water-based electrolytes.By in-situ analysis,we found that a thin amorphous layer of NiOOH,which is evolved from the Ni_(2)P during anodic reaction,is real catalytic active sites for the OER and UOR processes.Remarkable,such electrode-assembled urea-assisted natural seawater electrolyzer requires low voltages of 1.29 and 1.75 V to drive 10 and600 mA cm^(-2)and demonstrates superior durability by operating continuously for 100 h at 100 mA cm^(-2),beyond commercial Pt/C||RuO_(2) and most previous reports.