Shape recovery properties and load-carrying capacity of a 4D printed thick-walled kirigami-inspired honeycomb structure

Kirigami arts have provided a more promising method for building multiscale structures,which can shape two-dimensional(2D)sheets into three-dimensional(3D)configurations by cutting and folding.Here,we first carried out a theoretical analysis of the mechanical properties of 2D honeycomb lattice structures and experimental verification combined with finite element(FE)simulation.Furthermore,a series of thick-walled 3D kirigami-inspired honeycomb(TW3KH)structures with different mechanical properties were designed and fabricated on the exploration and optimization of geometric parameters of 2D honeycomb structures.The investigations of folding feasibility,self-expansion,and self-folding performance experimentally showed that our designed four-dimensional(4D)printing structure had good programmability and shape memory capability and a large volume change ratio during shape change.Meanwhile,research on its compression deformation behavior found that the TW3KH structures can recover load-bearing capacity very well when the angle is positive.Therefore,these TW3KH structures have great advantages in space-saving smart load-bearing equipment.

Analysis on the turning point of dynamic in-plane compressive strength for a plain weave composite

Experimental investigations on dynamic in-plane compressive behavior of a plain weave composite were performed using the split Hopkinson pressure bar. A quantitative criterion for calculating the constant strain rate of composites was established. Then the upper limit of strain rate, restricted by stress equilibrium and constant loading rate, was rationally estimated and confirmed by tests. Within the achievable range of 0.001/s-895/s, it was found that the strength increased first and subsequently decreased as the strain rate increased. This feature was also reflected by the turning point(579/s) of the bilinear model for strength prediction. The transition in failure mechanism, from local opening damage to completely splitting destruction, was mainly responsible for such strain rate effects. And three major failure modes were summarized under microscopic observations: fiber fracture, inter-fiber fracture, and interface delamination. Finally, by introducing a nonlinear damage variable, a simplified ZWT model was developed to characterize the dynamic mechanical response. Excellent agreement was shown between the experimental and simulated results.

A time integral formulation and algorithm for structural dynamics with nonlinear stiffness

A newly-developed numerical algorithm, which is called the new Generalized-α （G-α） method, is presented for solving structural dynamics problems with nonlinear stiffness. The traditional G-α method has undesired overshoot properties as for a class of α-method. In the present work, seven independent parameters are introduced into the single-step three-stage algorithmic formulations and the nonlinear internal force at every time interval is approximated by means of the generalized trapezoidal rule, and then the algorithm is implemented based on the finite difference theory. An analysis on the stability, accuracy, energy and overshoot properties of the proposed scheme is performed in the nonlinear regime. The values or the ranges of values of the seven independent parameters are determined in the analysis process. The computational results obtained by the new algorithm show that the displacement accuracy is of order two, and the acceleration can also be improved to a second order accuracy by a suitable choice of parameters. Obviously, the present algorithm is zero- stable, and the energy conservation or energy decay can be realized in the high-frequency range, which can be regarded as stable in an energy sense. The algorithmic overshoot can be completely avoided by using the new algorithm without any constraints with respect to the damping force and initial conditions.

Molecular dynamics simulations on the relationship between the elastic parameters and the molecular structures of nano-hybrid POSS materials

To research the relationship between the elastic parameters and the molecular structures of nano hybrid polyhedral oligomeric silsesquioxanes （POSS） materials, the mechanical properties at different temperatures for three POSS polymers with different molecular architectures, polymerlized norbornene POSS homopolymer （PNPOSS, pedant architecture）, γ- （2, 3 glycidoxy） propyl diaminoethane POSS polymer （GPDP, catena architecture） and trimethoxysilylcyelopentyl POSS polymer （ TSCP, cage - cage network architecture） were obtained by molecular dynamics simulations based on the Compass force-field. Results indicate that the moleculax architectures of the POSS polymers have great influence on the reinforced effects. The effect of the cage-cage network architecture is best, while that of the catena architecture takes second place and the pedant architecture has the least influence comparatively. The reinforced effects of the POSS monomers were examined. The influences of the temperatures on these effects were analyzed also. It may provide some basis for the reasonable applications of the excellent mechanical properties of the organic-inorganic nano-hybrid materials. It may also provide references for exploitation and design of the POSS materials.

Stochastic Second-Order Two-Scale Method for Predicting the Mechanical Properties of Composite Materials with Random Interpenetrating Phase

In this paper,a stochastic second-order two-scale(SSOTS)method is proposed for predicting the non-deterministic mechanical properties of composites with random interpenetrating phase.Firstly,based on random morphology description functions(RMDF),the randomness of the material properties of the constituents as well as the correlation among these random properties are fully characterized through the topologies of the constituents.Then,by virtue of multiscale asymptotic analysis,the random effective quantities such as stiffness parameters and strength parameters along with their numerical computation formulae are derived by a SSOTS strategy combined with the Monte-Carlo method.Finally,the SSOTS method developed in this paper shows an excellent computational accuracy,and therefore present an important advance towards computationally efficient multiscale modeling frameworks considering microstructure uncertainties.

Statistical second-order two-scale analysis and computation for heat conduction problem with radiation boundary condition in porous materials

This paper discusses a statistical second-order two-scale（SSOTS） analysis and computation for a heat conduction problem with a radiation boundary condition in random porous materials.Firstly,the microscopic configuration for the structure with random distribution is briefly characterized.Secondly,the SSOTS formulae for computing the heat transfer problem are derived successively by means of the construction way for each cell.Then,the statistical prediction algorithm based on the proposed two-scale model is described in detail.Finally,some numerical experiments are proposed,which show that the SSOTS method developed in this paper is effective for predicting the heat transfer performance of porous materials and demonstrating its significant applications in actual engineering computation.

A Shape-Memory Deployable Subsystem with a Large Folding Ratio in China’s Tianwen-1 Mars Exploration Mission

Once China’s Tianwen-1 Mars probe arrived in a Mars orbit after a seven-month flight in the deep cold space environment,it would be urgently necessary to monitor its state and the surrounding environment.To address this issue,we developed a flexible deployable subsystem based on shape memory polymer composites(SMPC-FDS)with a large folding ratio,which incorporates a camera and two temperature telemetry points for monitoring the local state of the Mars orbiter and the deep space environment.Here,we report on the development,testing,and successful application of the SMPC-FDS.Before reaching its Mars remote-sensing orbit,the SMPC-FDS is designed to be in a folded state with high stiffness;after reaching orbit,it is in a deployed state with a large envelope.The transition from the folded state to the deployed state is achieved by electrically heating the shape memory polymer composites(SMPCs);during this process,the camera on the SMPC-FDS can capture the local state of the orbiter from multiple angles.Moreover,temperature telemetry points on the SMPC-FDS provide feedback on the environment temperature and the temperature change of the SMPCs during the energization process.By simulating a Mars on-orbit space environment,the engineering reliability of the SMPC-FDS was comprehensively verified in terms of the material properties,structural dynamic performance,and thermal vacuum deployment feasibility.Since the launch of Tianwen-1 on 23 July 2020,scientific data on the temperature environment around Tianwen-1 has been successfully acquired from the telemetry points on the SMPCFDS,and the local state of the orbiter has been photographed in orbit,showing the national flag of China fixed on the orbiter.

Methodological survey of using Bayesian Network for predicting pharmacology-based bioactivities of Chinese medicines:a scoping review

Background:It seems to be numerous unclear black-box mechanisms of Chinese Medicines(CMs)with multiple bioactivities in the real-world clinical practice.Meanwhile,prior prediction is necessary before the implementation of pharmacodynamics-pharmacokinetics-based researches.With emergent ML techniques for TCM domain,Bayesian Network(BN)has shown its potentials for CM-bioactivity prediction and syndromes identification in Traditional Chinese Medicine(TCM),benefited from many advantages,such as flexibility in addressing,data-driven and probability-based inference under complex uncertainty.Although BN has been extensively used in TCM,the scarcity of researches on refining methodological features of BN-modelling for optimization poses a significant challenge.Our goal is to present methodological overview of BN-modelling for CM-bioactivities prediction towards pharmacology,which tends to acquire a sequence of intimations for boosting in-depth and optimized CM-BN collaboration based on detected gaps.Methods:We performed systematic search of 13 databases from their inception to November 10th 2022 regardless of language written,which excluded unindexed journals and clinical trial registries,using the 3 keywords(CM,Pharmacology,BN).And full-text original researches with the given subject were under consideration.Afterwards,selection of eligible studies,data refinement and inspection were totally conducted by 6 review authors.Results:A total of 7 studies involving 17 BN models were included for synthesis and refinement,based on existing literatures and databases with 2 modelling functions:regression and tagging.There were 3 prediction patterns:property-bioactivity,efficacy-bioactivity and constituent-bioactivity inference,covering 8 feature-utilized efficacies,5 feature-utilized properties and 10 feature-utilized constituents.Thereafter,without an independent validation dataset,established BNs were mostly utilized to predict the root-node probabilities of unknown data.Indeed,incomplete report on modelling samples,directed acyclic graphs,conditional probability tables and algorithms hindered us from gathering information.Conclusion:A spot of studies were found in this work.And current evidence suggested that some breakthroughs should be achieved in CM-BN integration in the future.At last,to our knowledge,we preliminarily proposed certain recommendations and elicited implications for future work.

Carbon fiber reinforced liquid crystalline elastomer composites:a dual exploration in strength augmentation and transformation flexibility through 4D printing

Liquid Crystal Elastomers(LCEs)are renowned for their reversible deformation capabilities.Yet,enhancing their mechanical strength while retaining such flexibility has posed a considerable challenge.To overcome this,we utilized 4D printing to develop an innovative composite of LCE with carbon fiber fabric(LCEC).This approach has notably increased the tensile strength of LCE by eightfold,all the while maintaining its exceptional capacity for reversible deforma-tion.By adjusting the alignment angle between carbon fiber and the LCE printing direction from 0°to 90°,the LCEC demonstrates an array of new deformation patterns,including bending,twisting,wrapping,and S-shaped transformations,which are distinct from pure LCE materials.Our study unveils that LCE composites exhibit deformation processes markedly different from their pure material counterparts,with the ability of pure LCE to sustain tensile strains exceeding 1900%.These findings,previously undocumented and unexplored,represent a substantial contribution to the field of smart materials.Employing finite element analysis,we explored the carbon fiber and LcE matrix dynamics,revealing bending mechanics in LCECs.This combined experimental and simulation approach yields crucial insights for crafting durable,high-strength LCECs with diverse deformational properties,advancing smart material technology.

Shape Memory Polymer Composites:4D Printing,Smart Structures,and Applications

Shape memory polymers (SMPs) and their composites (SMPCs) are smart materials that can be stably deformed and then return to their original shape under external stimulation, thus having a memory of their shape. Three-dimensional (3D) printing is an advanced technology for fabricating products using a digital software tool. Four-dimensional (4D) printing is a new generation of additive manufacturing technology that combines shape memory materials and 3D printing technology. Currently, 4D-printed SMPs and SMPCs are gaining considerable research attention and are finding use in various fields, including biomedical science. This review introduces SMPs, SMPCs, and 4D printing technologies, highlighting several special 4D-printed structures. It summarizes the recent research progress of 4D-printed SMPs and SMPCs in various fields, with particular emphasis on biomedical applications. Additionally, it presents an overview of the challenges and development prospects of 4D-printed SMPs and SMPCs and provides a preliminary discussion and useful reference for the research and application of 4D-printed SMPs and SMPCs.

Icephobic materials and strategies:From bio-inspirations to smart systems

Unwanted ice formations may cause severe functional degradations of facilities and also have a negative impact on their lifespans.Avoiding and removing ice accumula-tion is always a hot topic in the industrial and technological field.Bionic functional surfaces have been greatly studied for several decades and have proved to be excel-lent candidates for passive anti-/deicing applications.However,the drawbacks limit their potential industrial uses under harsh conditions,like low temperatures and high humidity.Most researches on bionic surfaces are focused on a certain function of nat-ural creatures and their underlined fundamental theories are revealed by taking the interface as the static.Actually,living organisms,either plants or animals,are often sensitive and responsive to their surroundings,avoiding risks and even self-repairing upon damage.From this prospect,a novel view of the bionic icephobic materials has been proposed in the present review,which is expected to be studied and designed by taking the biological species as a system.As two representative icephobic mate-rials,the anti-/deicing theories of superhydrophobic and slippery surfaces are first discussed.Further,the recent progress of smart icephobic strategies is summarized from interfaces to substrates.We aim to provide new bionic insights on designing future icephobic strategies.

Recent Advances in Space-Deployable Structures in China

Deployable space structure technology is an approach used in building spacecraft,especially when realizing deployment and folding functions.Once in orbit,the structures are released from the fairing,deployed,and positioned.With the development of communication,remote-sensing,and navigation satellites,space-deployable structures have become cutting-edge research topics in space science and technology.This paper summarizes the current research status and development trend of spacedeployable structures in China,including large space mesh antennas,space solar arrays,and deployable structures and mechanisms for deep-space exploration.Critical technologies of space-deployable structures are addressed from the perspectives of deployable mechanisms,cable-membrane form-finding,dynamic analysis,reliable environmental adaptability analysis,and validation.Finally,future technology developments and trends are elucidated in the fields of mesh antennas,solar arrays,deployable mechanisms,and on-orbit adjustment,assembly,and construction.

A bio-inspired 3D metamaterials with chirality and anti-chirality topology fabricated by 4D printing

Artificial architected metamaterials equipped with unique mechanical and physical properties that are naturally inaccessible can be obtained by rational design.In this work,the innovative three-dimensional(3D)chiral and anti-chiral metamaterials are developed referring to the face-rotating polyhedral(FRP)structure present in the virus.Through assembling planar triangular units into the regular octahedron cells,several typical forms of chiral and anti-chiral metamaterials can be obtained by different assembly methods.By changing the topology parameters,the Poisson’s ratio can be adjusted between[0,2.8].The metamaterials are fabricated by 3D printing utilizing shape memory polymer,and the mechanical properties are analyzed via Finite Element Analysis(FEA)and experiments,including Young’s modulus,Poisson’s ratio,and tension-twist coupling behavior.In addition,target metamaterial with specific local deformation behavior is obtained by programmatic calculations and distributions to meet special requirements or achieve unique applications.The shape memory property endows the mechanical metamaterials with more potential applications.

Control of Surface Wrinkles on Shape Memory PLA/PPDO Micro‑nanofibers and Their Applications in Drug Release and Anti‑scarring

Micro-and nano-fibers of shape memory polymers(SMP)offer multiple advantages like high specific surface area,poros-ity,and intelligence,and are suitable for biomedical applications.In this study,biodegradable poly(p-dioxanone)(PPDO)materials were incorporated to improve the brittleness of shape memory polylactic acid(PLA),and plasticizers were used to reduce the transition temperature of SMP composites such that their transitions could be induced close to body temperature.Furthermore,an electrostatic spinning technology was applied to prepare SMP fibers with wrinkled structures and regulate their microstructures and morphologies such that the intelligent transition of wrinkled and smooth morphologies can be achieved on the fiber surface.The application of this controllable-morphology fiber membrane in intelligent controlled drug release and scar inhibition after Ahmed Glaucoma Valve(AGV)implantation was also studied.The drug release from the stretched and deformed drug-loaded fiber membranes was faster than those from membranes with the original shape.This membrane with micro-and nano-fibers had good anti-scarring effects that improved after drug loading.The achievement of intelligent controlled drug release and the evident anti-scarring effects of the membrane broaden the application of SMP fibers in the biomedical field.

Mechanical properties and shape memory behavior of 4D printed functionally graded cellular structures

The properties of functionally graded(FG) cellular structures vary spatially, and the varying properties can meet the requirements of different working environments. In this study, we fabricated FG cellular structures with shape memory effect by 4D printing and evaluated the compressive performance and shape memory behavior of these structures with temperature through experimental analysis and finite element simulations. The results show that the maximum energy absorption gradually decreases but the compressive modulus gradually increases with increasing gradient parameters. Moreover, the finite element simulations also show that the compressive deformation mode of the structure shifts from uniform to non-uniform deformation with increasing gradient parameters. The compressive modulus and compressive strength of 4D printed FG structures decrease with increasing temperature due to the influence of the shape memory polymer, and they exhibit outstanding shape recovery capability under high-temperature stimulus. The proposed 4D printed FG structures with such responsiveness to stimulus shed light on the design of intelligent energy-absorbing devices that meet specific functional requirements.

A two-step unconditionally stable explicit method with controllable numerical dissipations

A family of unconditionally stable direct integration algorithm with controllable numerical dissipations is proposed. The numerical properties of the new algorithms are controlled by three parameters α, β and γ. By the consistent and stability analysis, the proposed algorithms achieve the second-order accuracy and are unconditionally stable under the condition that α≥-0.5, β≤ 0.5 and γ≥-(1+α)/2. Compared with other unconditionally stable algorithms, such as Chang's algorithms and CR algorithm, the proposed algorithms are found to be superior in terms of the controllable numerical damping ratios. The unconditional stability and numerical damping ratios of the proposed algorithms are examined by three numerical examples. The results demonstrate that the proposed algorithms have a superior performance and can be used expediently in solving linear elastic dynamics problems.

QUASICONTINUUM SIMULATION OF NANOINDENTATION OF NICKEL FILM

A large-scale atom simulation of nanoindentation into a thin nickel film using the quasicontinuum method was performed. The initial stages of the plasticity deformation of nickel were studied. Several useful results were obtained as follows： （1） The response of the load versus indentation depth on the load versus indentation depth curve, besides the straight parts corresponding to the elastic property of nickel, the sudden drop of the load occurred several times; （2） The phenomena of dislocation nucleation -- the dislocation nucleation took place when the load descended, which makes it clear that dislocation nucleation causes the drop of the load; （3） The mechanism of the dislocation emission - the Peierls-Nabarro dislocation model and a pow- erful criterion were used to analyze the dislocation emission. And the computational value was in good agreement with the predict value; （4） The density of geometrically necessary dislocations. A simple model was used to obtain the density of geometrically necessary dislocations beneath the indenter. Furthermore, the influence of the boundary conditions on the simulation results was discussed.

The hot compressive deformation behavior of the metal matrix composites with the large whisker orientation

Finite element analysis was used to investigate the effects of whisker misalignment on the hot compressive deformation behavior of whisker-reinforced composites. The simulation provided the evolution of the stress field of the composites and the whisker rotation process. It is found that with increasing the angle of whisker misalignment the whisker rotation angle decreases. Meanwhile, the mechanical behaviors of the composites such as work hardening or strain softening are affected by the whisker orientation and rotation during the hot compressive deformation. The predicted results are in agreement with the experimental results.

Phase Effect in Controlling Non-autonomous Chaos in the Presence of Noise

The effect of random phase on the Josephson junction system dynamic model is investigated.It is shown that random phase has the suppressing ability for controlling chaos.The top Lyapunov exponent is used to detect the chaotic dynamics in the system,and the method for calculating the top Lyapunov exponent is based on Khasminskii’s spherical coordinate formulation for linear stochastic systems.In addition,Poincarémap,phase portraits and time evolution are investigated to verify the obtained results.It is found that these results have the excellent agreement.

Adjustable volume and loading release of shape memory polymer microcapsules

Research on microcapsules has been conducted in recent years given trends in miniaturization and novel functionalization.In this work,we designed and prepared a series of unique shape memory polyurethane(SMPU)microcapsules with stimuli-responsive func-tions.The microcapsule has a core-shell structure in which the surface morphology can be adjusted,and it has a certain loadbearing capacity.In addition,the SMPU microcapsule has a stimuliresponsive function for shape memory and solvent response.The temperature of its shape recovery is approximately body tempera-ture,and it can swell to rupture under the stimulation of organic solvents.Thus,the SMPU microcapsule has potential applications in biomedical fields,such as drug release.