Memory Effect Research Articles

DESIGN, IMPLEMENTATION, AND TESTING OF A 3D-PRINTED GRIPPER ACTUATED BY NITINOL SPRINGS

This article explores the use of shape memory alloy (SMA) materials in the creation of robot effectors. Specifically, we focus on the design and implementation of a gripper powered by nitinol springs. Nitinol, an alloy of nickel and titanium, can return to a pre-set shape when heated - a phenomenon known as the shape memory effect - which we utilize to control the gripper. The article showcases the design, construction, and testing of the gripper, including its speed and reliability in grasping different objects. Our findings indicate that the gripper was reliable solution, but further research is necessary to optimize its functions and control for more efficient results in practical applications.

Plasmon AgNPs/MoS2/ZnO nanorods array ternary heterojunctions enabling high-efficiency solar-light energy utilization for photocatalysis and recyclable SERS detection

BackgroundSurface-enhanced Raman scattering (SERS) has gained widespread use in molecule-level detection benefiting from its high sensitivity, nondestructive data acquisition, and capacity for providing molecular fingerprint information. However, the strong adhesion of target molecules to the substrate (known as the "memory effect") inherently hinders the reusability of SERS substrates. Research has shown that self-cleaning SERS substrates based on versatile semiconductor materials with SERS enhancement capabilities and solar photocatalytic properties offer an effective platform for the sensitive detection and degradation of harmful molecules. ResultsIn this research, a resuable SERS-active substrate was facilely fabricated by anchoring silver nanoparticles (AgNPs) to the edges of MoS2 nanosheet decorated on ZnO nanorod arrays (NRAs). This innovative design exhibited a remarkable SERS enhancement factor (EF) of 4.6 × 107 and demonstrated significant solar photocatalytic efficiency. Such superior characteristics of ternary plasma heterojunction were ascribable to the synergistic effect of the “Schottky barrier” and “hot spots” between MoS2 and AgNPs, the inherent chemical enhancement proficiency of the MoS2/ZnO NRAs heterojunction, as well as the ultrafast electron transfer within the ternary heterojunction. SignificanceThe developed ternary heterojunction substrate enabled highly sensitive SERS detection of trace amounts of organic molecules. Moreover, this SERS substrate exhibited self-cleaning and recyclability via solar-light-driven photocatalysis. This bifunctional recyclable SERS substrate proved capable of meeting various requirements for routine monitoring of environmental organic pollutants and provided a robust avenue for advancing energy utilization materials that serve as high-performance SERS sensors and catalysts.

Romanovski–Jacobi spectral collocation schemes for distributed order differential problems

The article highlights the growing importance of computational mathematics in tackling intricate real-world phenomena governed by distributed order fractional dynamics. These dynamics, characterized by memory effects and non-local interactions, are pervasive in various fields such as physics, biology, finance, and engineering. Despite their prevalence, analytical solutions for distributed order fractional differential equations remain difficult to find, necessitating the development of robust numerical methods. The paper explores the effectiveness of Romanovski–Jacobi spectral collocation techniques in this context and provides a thorough analysis of how to use them to solve distributed order fractional differential equations. By leveraging these schemes, researchers gain valuable insights into efficiently analyzing and simulating fractional systems, thereby advancing our understanding of complex dynamics across diverse domains. It provides precise numerical findings by using finite expansion to evaluate residuals. The precision of the approach is illustrated by numerical simulations, especially in distributed order fractional differential equations. Additionally, we provide a few numerical tests to demonstrate the method’s ability to preserve the underlying problem’s non-smooth solution.

Fully 3D-Printed Miniature Soft Hydraulic Actuators with Shape Memory Effect for Morphing and Manipulation.

Miniature shape-morphing soft actuators driven by external stimuli and fluidic pressure hold great promise in morphing matter and small-scale soft robotics. However, it remains challenging to achieve both rich shape morphing and shape locking in a fast and controlled way due to the limitations of actuation reversibility and fabrication. Here, we report fully 3D-printed, sub-millimeter thin-plate-like miniature soft hydraulic actuators with shape memory effect for programmable fast shape morphing and shape locking. It combines commercial high-resolution multi-material 3D printing of stiff shape memory polymers (SMPs) and soft elastomers and direct printing of microfluidic channels and 2D/3D channel networks embedded in elastomers in a single print run. We demonstrated leveraging spatial patterning of hybrid compositions and expansion heterogeneity of microfluidic channel networks for versatile hydraulically actuated shape morphing, including circular, wavy, helical, saddle, and warping shapes with various curvatures. The morphed shapes can be temporarily locked and recover to their original planar forms repeatedly by activating shape memory effect of the SMPs. Utilizing the fast shape morphing and locking in the miniature actuators, we demonstrated their potential applications in non-invasive manipulation of small-scale objects and fragile living organisms, multimodal entanglement grasping, and energy-saving manipulators. This article is protected by copyright. All rights reserved.

Graphene Oxide-Enhanced and Dynamically Crosslinked Bio-Elastomer for Poly(lactic acid) Modification

Being a bio-sourced and biodegradable polymer, polylactic acid (PLA) has been considered as one of the most promising substitutes for petroleum-based plastics. However, its wide application is greatly limited by its very poor ductility, which has driven PLA-toughening modifications to be a topic of increasing research interest in the past decade. Toughening enhancement is achieved often at the cost of a large sacrifice in strength, with the toughness–strength trade-off having remained as one of the main bottlenecks of PLA modification. In the present study, a bio-elastomeric material of epoxidized soybean oil (ESO) crosslinked with sebacic acid (SA) and enhanced by graphene oxide (GO) nanoparticles (NPs) was employed to toughen PLA with the purpose of simultaneously preserving strength and achieving additional functions. The even dispersion of GO NPs in ESO was aided by ultrasonication and guaranteed during the following ESO-SA crosslinking with GO participating in the carboxyl–epoxy reaction with both ESO and SA, resulting in a nanoparticle-enhanced and dynamically crosslinked elastomer (GESO) via a β-hydroxy ester. GESO was then melt-blended with PLA, with the interfacial reaction between ESO and PLA offering good compatibility. The blend morphology, and thermal and mechanical properties, etc., were evaluated and GESO was found to significantly toughen PLA while preserving its strength, with the GO loading optimized at ~0.67 wt%, which gave an elongation at break of ~274.5% and impact strength of ~10.2 kJ/m2, being 31 times and 2.5 times higher than pure PLA, respectively. Moreover, thanks to the presence of dynamic crosslinks and GO NPs, the PLA-GESO blends exhibited excellent shape memory effect and antistatic properties.

A thermo-mechanical constitutive model for triple-shape and two-way shape memory polymers

Semicrystalline polymers often have diverse molecular configurations in response to the variation of temperature, making it easier to realize multiple or two-way shape memory effects (SMEs). In order to provide guidance for the design of relevant smart structures, it is necessary to develop corresponding constitutive models to better characterize the thermal-mechanical behavior of such shape memory polymers (SMPs). For the first time, a thermo-mechanical finite deformation constitutive model is presented to reveal the deformation mechanism of the triple-shape two-way SME of semicrystalline SMPs in our work, based on the theory of thermodynamics with internal state variables. To verify the validity of the model, the model results are compared with the test data for a typical shape memory cycle. It is found that the model can be employed to describe the non-equilibrium response of semicrystalline SMPs with two types of crystallites in the vicinity of crystallization and melting. Since the model results fit well with the test data, the effectiveness of the model in predicting the triple two-way shape memory behavior is demonstrated.

Advanced stability analysis of a fractional delay differential system with stochastic phenomena using spectral collocation method.

In recent years, there has been a growing interest in incorporating fractional calculus into stochastic delay systems due to its ability to model complex phenomena with uncertainties and memory effects. The fractional stochastic delay differential equations are conventional in modeling such complex dynamical systems around various applied fields. The present study addresses a novel spectral approach to demonstrate the stability behavior and numerical solution of the systems characterized by stochasticity along with fractional derivatives and time delay. By bridging the gap between fractional calculus, stochastic processes, and spectral analysis, this work contributes to the field of fractional dynamics and enriches the toolbox of analytical tools available for investigating the stability of systems with delays and uncertainties. To illustrate the practical implications and validate the theoretical findings of our approach, some numerical simulations are presented.

Long-lasting, fast-switchable photochromism in Na0.5Bi0.5TiO3 induced by photocatalytic memory effect, and its subsequently enhanced piezoelectric response and catalytic performances

A ferroelectric ceramic material of Na0.5Bi0.5TiO3 was found to possess a pronounced, long-lasting, and fast-switchable photochromic behavior responsive to visible light. The working mechanism of its photochromism could be attributed to an interesting photocatalytic memory effect, during which photogenerated electrons were trapped by Bi3+/Ti4+ and oxygen vacancies generated in Na0.5Bi0.5TiO3. The release kinetics of trapped electrons could be modulated by controlling environment conditions to make its photochromism phenomenon both long-lasting and fast-switchable to meet various application requirements. In the meantime, the photochromism process changed its inner electronic structure, resulting in stronger oxidation capability, increased piezoelectric response, improved charge carrier separation and transfer, and more active oxygen species production. Thus, its photocatalytic, piezocatalytic and photopiezocatalytic performances were all significantly enhanced as demonstrated by its TC-HCl degradation performances. This work offered a novel approach to search for and design inorganic photochromic materials with good reversibility for various technical applications.

A doubly history‐dependent quasivariational inequality arising in viscoelastic frictional contact problems with wear

AbstractWe aim here to investigate a new mathematical model that describes the contact between a viscoelastic body, accounting for long memory and wear effects, and an obstacle referred to as the foundation. The contact model is governed by a normal compliance condition, coupled with Coulomb's law of dry friction for sliding, and wear effects. We derive the variational formulation of the model, which involves coupling of a quasi‐variational inequality with a nonlinear equation. By pursuing the abstract history‐dependent quasi‐variational inequalities and leveraging the fixed point theorem, we establish results concerning both existence and uniqueness.

Universal Symmetry of Optimal Control at the Microscale

Optimizing the energy efficiency of driving processes provides valuable insights into the underlying physics and is of crucial importance for numerous applications, from biological processes to the design of machines and robots. Knowledge of optimal driving protocols is particularly valuable at the microscale, where energy supply is often limited. Here, we experimentally and theoretically investigate the paradigmatic optimization problem of moving a potential carrying a load through a fluid, in a finite time and over a given distance, in such a way that the required work is minimized. An important step towards more realistic systems is the consideration of memory effects in the surrounding fluid, which are ubiquitous in real-world applications. Therefore, our experiments were performed in viscous and viscoelastic media, which are typical environments for synthetic and biological processes on the microscale. Despite marked differences between the protocols in both fluids, we find that the optimal control protocol and the corresponding average particle trajectory always obey a time-reversal symmetry. We show that this symmetry, which surprisingly applies here to a class of processes far from thermal equilibrium, holds universally for various systems, including active, granular, and long-range correlated media in their linear regimes. The uncovered symmetry provides a rigorous and versatile criterion for optimal control that greatly facilitates the search for energy-efficient transport strategies in a wide range of systems. Using a machine learning algorithm, we demonstrate that the algorithmic exploitation of time-reversal symmetry can significantly enhance the performance of numerical optimization algorithms. Published by the American Physical Society 2024

Mechanical Properties, Energy Absorption, and Shape Memory Behavior of 3D Printed PLA‐MXene Nanocomposites and Gyroid Lattices

This work investigates the influence of MXene content on the mechanical and functional response of PLA‐MXene composites fabricated additively using fused deposition modeling. The mechanical, thermal, and microstructural properties of the fabricated samples are investigated considering dense and architected triply periodic minimal surfaces (TPMS) gyroid specimens. Overall, the addition of 0.25–0.5 wt% MXene is found to improve the stiffness, fracture strength, and energy absorption capabilities of the PLA. However, further increasing MXene content to 1 wt% becomes detrimental to the general performance of the composite. In terms of functional behavior, the PLA‐MXene blends developed in this work are shown to display a shape memory effect, wherein deformed samples are shown to recover their shape when submerged in hot water. The reported results provide insights into the use of PLA‐MXene in engineering applications, namely those involving impact shielding or energy absorption.

NONLINEARITY AND MEMORY EFFECTS: THE INTERPLAY BETWEEN THESE TWO CRUCIAL FACTORS IN THE HARRY DYM MODEL

This study investigates the nonlinear time-fractional Harry Dym ([Formula: see text]) equation, a model with significant applications in soliton theory and connections to various other nonlinear evolution equations. The Harry Dym ([Formula: see text]) equation describes the propagation of nonlinear waves in various physical contexts, including shallow water waves, nonlinear optics, and plasma physics. The fractional-order derivative introduces a memory effect, allowing the model to capture nonlocal interactions and long-range dependencies in the wave dynamics. The primary objective of this research is to obtain accurate analytical solutions to the [Formula: see text] equation and explore its physical characteristics. We employ the Khater III method as the primary analytical technique and utilize the He’s variational iteration ([Formula: see text]) method as a numerical scheme to validate the obtained solutions. The close agreement between analytical and numerical results enhances the applicability of the solutions in practical applications of the model. This research contributes to a deeper understanding of the [Formula: see text] equation’s behavior, particularly in the presence of fractional-order dynamics. The obtained solutions provide valuable insights into the complex interplay between nonlinearity and memory effects in the wave propagation phenomena described by the model. By shedding light on the physical characteristics of the [Formula: see text] equation, this study paves the way for further investigations into its potential applications in diverse physical settings.

Effect of Al content on thermal stability, shape memory effect and mechanical properties of Cu–Al–Fe shape memory alloys

Effect of Al content on thermal stability, shape memory effect and mechanical properties of Cu–Al–Fe shape memory alloys

Smart materials for sustainable energy

In the new era of technologies, different smart or responsive materials are used which can respond to external stimuli, such as a specific amount of mechanical stress, pressure, temperature, pH, or sunlight radiations, by modifying their shape or dimensions or mechanical properties. As global temperatures rise and weather patterns become more erratic and severe. The risk to communities with energy-passive structures is growing, smart materials such as smart rooftops, thermoelectrics, photovoltaics, pyroelectrics, chromoactive, photoluminescent, as well as other innovations, help to conserve renewable energy smartly and sustainably. This review paper reflects on the applications of different smart materials as renewable smart resources. Intelligent quantum dot solar cells, Schottky solar cells, organic thin-film photovoltaic cells, dye-sensitized solar cells (DSSCs), and organic-inorganic heterojunction solar cells have high conversion efficiency, low cost, and possess wide absorption spectra that reach the near-infrared range. Biomechanical energy can be transformed into green energy using triboelectric and piezoelectric-based smart nanogenerators such as zinc oxide nanowires. Shape memory materials such as Nitinol (NiTi) have been embedded in the wind turbine blades to enhance aerodynamic efficiency. Piezoelectric nanogenerators can convert mechanical energy directly into electrical energy by using wireless sensors to harvest energy from moving water in hydroelectric power plants. Thermoelectric materials such as silver antimony telluride (AgSbTe2) offer a sustainable energy option, which employs industrial waste heat to produce power. Smart materials like graphene are more reliable and effective than carbon nanotubes for storing green hydrogen. Smart non-enzymatic biofuel cells are used in biomedical gadgets such as anesthesia machines and pacemakers, which are self-powered and have great sensitivity. Shape memory materials (SMM) are introduced in natural gas and oil reservoirs because they offer exceptional qualities such as the shape memory effect (SME), lightweight, corrosion resistance, and superelasticity, which enhance the performance and robustness of offshore industries. These new advancements, challenges, and applications of smart materials for renewable energy are covered in this review paper.

Engineering Biodegradable Polyurethanes with Precisely Controlled Hierarchical Structures to Access Shape Memory Effect and Enhanced Bioactivities.

Biodegradable polymers with shape memory effects (SMEs) offer promising solutions for short-term medical interventions, facilitating minimally invasive procedures and subsequent degradation without requiring secondary surgeries. However, achieving a good balance among desirable SMEs, mechanical performance, degradation rate, and bioactivities remains a significant challenge. To address this issue, we established a strategy to develop a versatile biodegradable polyurethane (PPDO-PLC) with tunable hierarchical structures via precise chain segment control. Initial copolymerization of l-lactide and ε-caprolactone sets a tunable Tg close to body temperature, followed by block copolymerization with poly(p-dioxanone) to form a hard domain. This yields a uniform microphase-separation morphology, ensuring robust SME and facilitating the development of roughly porous surface structures in alkaline environments. Cell experiments indicate that these rough surfaces significantly enhance cellular activities, such as adhesion, proliferation, and osteogenic differentiation. Our approach provides a methodology for balancing biodegradability, SMEs, three-dimensional (3D) printability, and bioactivity in materials through hierarchical structure regulation.

DESIGN AND IMPLEMENTATION OF FUZZY-FRACTIONAL WU–ZHANG SYSTEM USING HE–MOHAND ALGORITHM

In recent years, fuzzy and fractional calculus are utilized for simulating complex models with uncertainty and memory effects. This study is focused on fuzzy-fractional modeling of (2+1)-dimensional Wu–Zhang (WZ) system. Caputo-type time-fractional derivative and triangular fuzzy numbers are employed in the model to observe uncertainties in the presence of non-local and memory effects. The extended He–Mohand algorithm is proposed for the solution and analysis of the current model. This approach is based on homotopy perturbation method along with Mohand transformation. Effectiveness of proposed methodology at upper and lower bounds is confirmed through residual errors. The theoretical convergence of proposed algorithm is proved alongside numerical computations. Existence and uniqueness of solution are also theoretically proved in the given paper. Current investigation considers three types of fuzzifications i.e. fuzzified equations, fuzzified conditions, and finally fuzzification in both model and conditions. Different physical aspects of WZ system profiles are analyzed through 2D and 3D illustrations at upper and lower bounds. The obtained results highlight the impact of uncertainty on WZ system in fuzzy-fractional space. Hence, the proposed methodology can be used for other fuzzy-fractional systems for better accuracy with lesser computational cost.

In search of the molecular mechanisms of adaptation memory in rods: basic activity of phosphodiesterase

Retinal rods, the photoreceptors responsible for twilight vision, are capable of adapting to a wide range of light levels. The molecular mechanisms of light adaptation have been well studied, but an interesting question is what changes occur in the phototransduction cascade after the adaptive light stimuli are eliminated. Previously, we showed the phenomenon of adaptation memory in amphibian rods: after background illumination photoreceptor sensitivity to light remained reduced for several minutes, while the dark current recovered within 20—30 s. This suggests the existence of additional, as yet unknown, regulatory mechanisms of the phototransduction cascade that act after the adaptive effect of light. In search of specific mechanisms that could explain the effect of adaptation memory, we performed electrophysiological experiments on isolated frog rods to evaluate the basal activity of the effector enzyme of the phototransduction cascade, the phosphodiesterase type 6, in the dark and after saturating background illumination. It was found that the post-adaptation state of rods was characterized by increased basal phosphodiesterase activity, which gradually decreased to the dark level within tens of seconds after turning off the adaptive illumination. These results also suggest that the components of the phototransduction cascade may undergo some unstudied changes after light adaptation.

Part-set cuing effects in spatial memory: the role of interitem associations

Part-set cuing facilitation and impairment effects are rarely found in spatial memory, which is a challenge to the theories of part-set cuing effects based on lexical stimulus. This study aims to investigate whether there part-set cuing facilitation and impairment effects are present in spatial memory by constructing two types of memory scenes with high and low degrees of interitem associations, achieved by manipulating the presentation of miniatures. This study examined the effects of different part-set cues on free recall, recognition, and reconstruction tasks. The results of two experiments revealed that matrix cues impaired the performance of three recall tasks in memory scenes with a high degree of interitem associations, and scene cues facilitated the reconstruction performance (Experiment 1). Conversely, in memory scenes with a low degree of interitem associations, the impairment effect of matrix cues was not observed in the three recall tasks, but scene cues still facilitated the reconstruction performance (Experiment 2). These findings supported the retrieval strategy disruption hypothesis, the two-mechanism and the multi-mechanism accounts, demonstrating the significance of interitem associations in spatial memory. Furthermore, the results provided direct evidence for the importance of the encoding-retrieval strategy matching principle in spatial memory tasks.

Bifurcation investigation, phase synchronization and FPGA implementation of a new photosensitive Fitz Hugh Nagumo neuron based meminductor

Abstract This paper focuses on the estimation of the nonlinear encoding and responses of a photosensitive Fitz Hugh Nagumo (FHN) neuron-based-meminductor and provides a relevant analysis of its phase synchronization. In the pattern, a Fitz Hugh–Nagumo neuron connected to a meminductor is activated by a photocell, and a time-varying current source is generated by the presence of external optical signals. This coupling is a benchmark circuit with memory similar to artificial eyes with the ability to capture and encode external signals. It is designed with the aim of studying the dynamics of a neuron with a memory effect highlighted through the meminductor. An appropriate dynamical analysis is provided using standard indicators such as bifurcations to point out thorough transitions and the nature of the electrical neuronal activities. Some couplings between two FHN neurons with meminductor using hybrid synapses composed of passive electronic components are achieved. Relevant tools are used to analyze the stability of the synchronization which gives prominent details on the selection of the appropriate coupling. The energy balance of the external system is evaluated which gives the effort to achieve encoding signals and also proves the feasibility of the proposal in real-time implementation. Simulations are performed on FPGA. The results present a good agreement. In many engineering applications, the detection of optical signals is inescapable as well as the synchronization of its signals for the transmission of the stimuli. These results could be useful for the designer.

Gravitational Wave Displacement and Velocity Memory Effects

Abstract In this article, we compare in detail the linear and nonlinear approach to the Gravitational Waves Displacement and Velocity Memory (GWDM and GWVM) effects. We consider astrophysical situations that give rise to gravitational waves with GWVM effect, i.e. with a residual velocity (the so-called ``velocity-coded memory") and discuss the possibility of future detection of the GWVM effect.