Smart Materials Research Articles

Unraveling the Impact of Boron Nitride and Silicon Nitride Nanoparticles on Thermoplastic Polyurethane Fibers and Mats for Advanced Heat Management.

The urgent challenges posed by the energy crisis, alongside the heat dissipation of advanced electronics, have embarked on a rising demand for the development of highly thermally conductive polymer composites. Electrospun composite mats, known for their flexibility, permeability, high concentration and orientational degree of conductive fillers, stand out as one of the prime candidates for addressing this need. This study explores the efficacy of boron nitride (BN) and its potential alternative, silicon nitride (SiN) nanoparticles, in enhancing the thermal performance of the electrospun composite thermoplastic polyurethane (TPU) fibers and mats. The 3D reconstructed models obtained from FIB-SEM imaging provided valuable insights into the morphology of the composite fibers, aiding the interpretation of the measured thermal performance through scanning thermal microscopy for the individual composite fibers and infrared thermography for the composite mats. Notably, we found that TPU-SiN fibers exhibit superior heat conduction compared to TPU-BN fibers, with up to a 6 °C higher surface temperature observed in mats coated on copper pipes. Our results underscore the crucial role of arrangement of nanoparticles and fiber morphology in improving heat conduction in the electrospun composites. Moreover, SiN nanoparticles are introduced as a more suitable filler for heat conduction enhancement of electrospun TPU fibers and mats, suggesting immense potential for smart textiles and thermal management applications.

Epileptic seizure forecasting with wearable-based nocturnal sleep features.

Non-invasive biomarkers have recently shown promise for seizure forecasting in people with epilepsy. In this work, we developed a seizure-day forecasting algorithm based on nocturnal sleep features acquired using a smart shirt. Seventy-eight individuals with epilepsy admitted to the Centre hospitalier de l'Université de Montréal epilepsy monitoring unit wore the Hexoskin biometric smart shirt during their stay. The shirt continuously measures electrocardiography, respiratory, and accelerometry activity. Ten sleep features, including sleep efficiency, sleep latency, sleep duration, time spent in non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM), wakefulness after sleep onset, average heart and breathing rates, high-frequency heart rate variability, and the number of position changes, were automatically computed using the Hexoskin sleep algorithm. Each night's features were then normalized using a reference night for each patient. A support vector machine classifier was trained for pseudo-prospective seizure-day forecasting, with forecasting horizons of 16- and 24-h to include both diurnal and nocturnal seizures (24-h) or diurnal seizures only (16-h). The algorithm's performance was assessed using a nested leave-one-patient-out cross-validation approach. Improvement over chance (IoC) performances were achieved for 48.7% and 40% of patients with the 16- and 24-h forecasting horizons, respectively. For patients with IoC performances, the proposed algorithm reached mean IoC, sensitivity and time in warning of 34.3%, 86.0%, and 51.7%, respectively for the 16-h horizon, and 34.2%, 64.4% and 30.2%, respectively, for the 24-h horizon. Smart shirt-based nocturnal sleep analysis holds promise as a non-invasive approach for seizure-day forecasting in a subset of people with epilepsy. Further investigations, particularly in a residential setting with long-term recordings, could pave the way for the development of innovative and practical seizure forecasting devices. Seizure forecasting with wearable devices may improve the quality of life of people living with epilepsy who experience unpredictable, recurrent seizures. In this study, we have developed a seizure forecasting algorithm using sleep characteristics obtained from a smart shirt worn at night by a large number of hospitalized patients with epilepsy (78). A daily seizure forecast was generated following each night using machine learning methods. Our results show that around half of people with epilepsy may benefit from such an approach.

Temperature‐Responsive Polyoxometalates‐Based Materials: From Underlying Mechanism to Promising Applications

AbstractPolyoxometalates (POMs) are multifunctional anionic metal‐oxygen complexes with structural and electronic diversity, as well as tunable acid‐base and redox properties, resulting in their potential as building blocks for constructing temperature‐responsive polyoxometalates‐based materials (TRPMs). TRPMs represent a class of intelligent materials exhibiting property changes in response to temperature fluctuations, offering distinctive applications in various fields such as catalysis, medicine, sensors, imaging, and so on. Though many TRPMs are reported, a systematic review including recent advances is still absent. This review provides insights into recent advancements in temperature‐responsive mechanisms, nanostructure design strategies, and the characterization of TRPMs. Special emphasis is placed on enhancing the temperature‐responsive properties of TRPMs by incorporating POMs into suitable organic ligands, such as ionic liquid cations, deep eutectic solvent cations, cationic surfactants, and polymers. The incorporation of organic ligands with POMs not only enables temperature‐responsive phase transitions but also enhances other properties, such as catalyst selectivity and drug loading capacity, expanding TRPMs applications. Consequently, this review summarizes the applications of TRPMs in catalysis, drug delivery and release, and chemical sensing, as well as discusses future technological challenges. The in‐depth understanding of TRPMs may help in the design of TRPMs from the nanoscale, guiding and inspiring future development.

Dynamic Spectral Metafabric with Unidirectional Moisture Transport Property for Personal Thermal Management.

Personal thermal management technology, which adjusts the heat exchange between the human body and the environment, can passively heat or cool the body to maintain a comfortable core temperature, thereby enhancing comfort and reducing energy consumption. However, most existing personal thermal management materials have static properties, such as fixed solar reflectance and infrared emissivity, which do not support real-time dynamic temperature regulation. Moreover, sweat accumulation on the skin surface, while contributing to temperature regulation, can significantly reduce comfort. This study constructs a unidirectional moisture-permeable intelligent thermal management fabric system to achieve superior thermal and moisture comfort in complex environments. The fabric incorporates thermochromic microcapsules into PAN nanofibers by using electrospinning technology for intelligent thermal management. Subsequent hydrophobic treatment of the fiber film surface imparts the fabric with unidirectional wetting properties. The nanofibrous structure provides intrinsic elasticity and breathability. In heating mode, the fabric's average sunlight reflectance is 42.1%, which increases to 82.2% in cooling mode, resulting in a reflectance difference of approximately 40%. The hydrophobic treatment endows the fabric with excellent moisture absorption and perspiration properties, demonstrated by a unidirectional moisture transport index of 696.63 and a perspiration evaporation rate of 5.88 mg/min. When the fabric temperature matches the ambient temperature, the photothermal conversion power difference of the Janus metafabric in two modes reaches 248.37 W m-2. Additionally, Janus metafabrics show the potential for temperature-responsive design and repeated writing applications. The outstanding wearability and dynamic spectral properties of these metafabrics open new pathways for sustainable energy, smart textiles, and thermal-moisture comfort applications.

Efficient and sustainable production of intelligent nonwovens as indicators of food spoilage through solution blow spinning of proteins and natural pigments from agri-food waste

The efficient manufacturing of food spoilage indicators based on intelligent nonwovens represents a promising alternative to enable the application of these materials in food quality monitoring. The objective of this study was to rapidly produce intelligent nanofiber nonwovens made of zein/gelatin (Z/G) functionalized with various concentrations (5–15% w/w on the matrix) of anthocyanin-rich food-residue extracts from purple cabbage (CAE) or purple sweet potato (PAE) using the solution-blow-spinning (SBS) technique for use in food-quality-monitoring applications. The addition of CAE or PAE to the Z/G matrix reduced the viscosity of the solution and (consequently) the nanofiber diameters from 999 nm to 882 and 583 nm, respectively. Such incorporation also improved the mechanical, thermal, and water-related properties of the nanofibers and endowed them with antioxidant capacities. Nonwovens composed of Z/G nanofibers with added CAE or PAE, especially at concentrations of 15%, exhibited visible color changes (ΔE ≥ 3) that rapidly altered in response to pH (3–10) and when exposed to ammonia vapor. The nonwovens were successfully used to monitor the deterioration of pasteurized milk and fish fillets. They reveal a visual color change from pink at 0 h to a more intense pink at 48 h in response to milk deterioration and a color change from pink at 0 h to light brown after 48 h when the fish fillets were considered deteriorated. The use of these nanofiber nonwovens to monitor changes in food quality highlights the significant potential of the SBS technique and the use of anthocyanins from agri-food waste to produce new intelligent packaging materials for use in food applications.

Stretchable and Self-Powered Mechanoluminescent Triboelectric Nanogenerator Fibers toward Wearable Amphibious Electro-Optical Sensor Textiles.

Flexible electro-optical dual-mode sensor fibers with capability of the perceiving and converting mechanical stimuli into digital-visual signals show good prospects in smart human-machine interaction interfaces. However, heavy mass, low stretchability, and lack of non-contact sensing function seriously impede their practical application in wearable electronics. To address these challenges, a stretchable and self-powered mechanoluminescent triboelectric nanogenerator fiber (MLTENGF) based on lightweight carbon nanotube fiber is successfully constructed. Taking advantage of their mechanoluminescent-triboelectric synergistic effect, the well-designed MLTENGF delivers an excellent enhancement electrical signal of 200% and an evident optical signal whether on land or underwater. More encouragingly, the MLTENGF device possesses outstanding stability with almost unchanged sensitivity after stretching for 200%. Furthermore, an extraordinary non-contact sensing capability with a detection distance of up to 35cm is achieved for the MLTENGF. As application demonstrations, MLTENGFs can be used for home security monitoring, intelligent zither, traffic vehicle collision avoidance, and underwater communication. Thus, this work accelerates the development of wearable electro-optical textile electronics for smart human-machine interaction interfaces.

Overcoming Challenges of Lignin Nanoparticles: Expanding Opportunities for Scalable and Multifunctional Nanomaterials.

ConspectusThe increasing demand for polymeric materials derived from petroleum resources, along with rising concerns about climate change and global plastic pollution, has driven the development of biobased polymeric materials. Lignin, which is the second most abundant biomacromolecule after cellulose, represents a promising renewable raw material source for the preparation of advanced materials. The lucrative properties of lignin include its high carbon content (>60 atom %), high thermal stability, biodegradability, antioxidant activity, absorbance of ultraviolet radiation, and slower biodegradability compared to other wood components. Moreover, the advent of lignin nanoparticles (LNPs) over the last ten years has circumvented many well-known shortcomings of technical lignins, such as heterogeneity and poor compatibility with polymers, thereby unlocking the great potential of lignin for the development of advanced functional materials.LNPs stand out owing to their well-defined spherical shape and excellent colloidal stability, which is due to the electrostatic repulsion forces of carboxylic acid and phenolic hydroxyl groups enriched on their surface. These forces prevent their aggregation in aqueous dispersions (pH 3-9) and provide a high surface area to mass ratio that has been exploited to adsorb positively charged compounds such as enzymes or polymers. Consequently, it is not surprising that LNPs have become a prominent player in applied research in areas such as biocatalysis and polymeric composites, among others. However, like all ventures of life, LNPs also face certain challenges that limit their potential end-uses. Solvent instability remains the most challenging aspect due to the tendency of these particles to dissolve or aggregate in organic solvents and basic or acidic pH, thus limiting the window for their chemical functionalization and applications. In addition, the need for organic solvent during their preparation, the poor miscibility with hydrophobic polymeric matrices, and the nascent phase regarding their use in smart materials have been identified as important challenges that need to be addressed.In this Account, we recapitulate our efforts over the past years to overcome the main limitations mentioned above. We begin with a brief introduction to the fundamentals of LNPs and a detailed discussion of their associated challenges. We then highlight our work on: (i) Preparation of lignin-based nanocomposites with improved properties through a controlled dispersion of LNPs within a hydrophobic polymeric matrix, (ii) Stabilization of LNPs via covalent (intraparticle cross-linking) and noncovalent (hydration barrier) approaches, (iii) The development of an organic-solvent-free method for the production of LNPs, and (iv) The development of LNPs toward smart materials with high lignin content. Finally, we also offer our perspectives on this rapidly growing field.

Intelligent Systems Based on Cyclodextrins for the Treatment of Breast Cancer.

The incidence of breast cancer has been increasing over the last four decades, although the mortality rate has decreased. Endocrine therapy and chemotherapy are the most used options for cancer treatment but several obstacles are still attributed to these therapies. Smart materials, such as nanocarriers for targeting, delivery and release of active ingredients, sensitive to intrinsic-stimuli (pH-responsive, redox-responsive, enzyme- responsive, and thermo-responsive) and extrinsic-stimuli (ultrasound-responsive, magnetic-responsive, light-responsive) have been studied as a novel strategy in breast cancer therapy. Cyclodextrins (CDs) are used in the design of these stimuli-responsive drug carrier and delivery systems, either through inclusion complexes with hydrophobic molecules or covalent bonds with large structures to generate new materials. The present work aims to gather and integrate recent data from in vitro and in vivo preclinical studies of CD-based stimuli- responsive systems to contribute to the research in treating breast cancer. All drug carriers showed high in vitro release rates in the presence of a stimulus. The stimuli-responsive nanoplatforms presented biocompatibility and satisfactory results of IC50, inhibition of cell viability and antitumor activity against several breast cancer cell lines. Additionally, these systems led to a significant reduction in drug dosages, which encouraged possible clinical studies for better alternatives to traditional antitumor therapies.

Effect of ZrO2 nanoparticles on the self-lubrication behavior of the linseed oil-loaded microcapsule/ epoxy composite coatings

Smart polymeric coatings play a crucial role in protecting steel surfaces from corrosion and wear. One of progressive smart behavior is self-healing behavior especially in self-healing epoxy coatings. Creating or improving the second smart behavior is known as a new trend for these smart materials. This study aims to investigate the effects of ZrO2 nanoparticles on the self-lubricating behavior as the second smart behavior of the linseed oil-loaded microcapsule/epoxy composite coatings. To do so, the in-situ polymerization method was used for the synthesis of linseed oil-loaded microcapsule. Results showed that the average size of prepared linseed oil-loaded microcapsules was 563 nm. The composite coatings were prepared by different content of ZrO2 nanoparticles (0, 3, 6, 9, 12, and 15 wt%) and constant content of linseed oil-loaded microcapsules (5 wt%). The tribological performance of samples was studied using pin-on-disk test. The worn surface of the samples was also studied using field emission scanning electron microscope (FESEM) images. Results proved that the frictional coefficient and wear rate of the samples were significantly decreased by increasing the concentrations of the ZrO2 nanoparticles up to 9 wt%. The lowest friction coefficient and wear rate values of 0.085 and 0.142 × 10−6 mm3/Nm were obtained for 5 wt% linseed oil-loaded microcapsules/epoxy with 9 wt% ZrO2 which were about 82 % and 88 % lower than those of pure epoxy coating.

Strength Prediction of Smart Cementitious Materials Using a Neural Network Optimized by Particle Swarm Algorithm

Because of the improved physical, mechanical and crack–resistant properties, smart cementitious materials have garnered significant attention in civil engineering. However, the method of predicting performance of smart cementitious materials remains a formidable task. To address this issue, this study develops a neural network optimized by particle swarm algorithm, specifically designed for predicting the strength of smart cementitious materials. Particle swarm optimization is used to determine the initial weights and biases of the neural network in this algorithm. Two types of smart cementitious materials, namely 3D printed fiber reinforced concrete and graphene nanoparticles–reinforced cementitious composites, are studied as examples. Utilizing the PSO–BPNN method and data gathered from the existing articles, the predictive models for the mechanical properties of these materials are developed. Five commonly used statistical metrics are applied to evaluate the predictive performance. The results indicate suggest the PSO–BPNN outperforms the traditional back propagation neural network. Thus, a reliable and robust performance predictive model can be built for smart cementitious materials using the proposed approach.

A bidirectional-controllable magnetorheological elastomer-based quasi-zero-stiffness isolator

To enhance the low-frequency vibration isolation bandwidth of quasi-zero stiffness (QZS) isolators under variable amplitude excitations, this paper proposes an adaptive bidirectional-controllable QZS isolator (Bi-QZS) based on magnetic-controlled smart material named magnetorheological elastomer (MRE) as positive element and tilting spring as negative element. Firstly, the positive element of isolator is composed of laminated MRE and permanent magnet to realize bidirectional stiffness adjustment. Then the magnetic circuit of vibration isolator is designed and the specific parameters are obtained by taking the magnetic field and energy consumption as the optimization objectives. Secondly, a static theoretical model is established to calculate the achievable range of stiffness variation, and match the parameters of the negative element. Static analysis shows that bidirectional stiffness control is beneficial to achieve stiffness matching. Additionally, the adjustment of bidirectional stiffness variation on the dynamic response of the system is deduced by harmonic balance method. Numerical simulation results indicate that adjusting stiffness in reverse can increase the vibration isolation bandwidth when the excitation amplitude increases, and adjusting in forward can reduce the peak value of jump region. Also, increasing the damping ratio under reverse conditions has a certain contribution to reducing the response peak. Finally, static and dynamic tests are carried out, results reveal a bidirectional stiffness adjustment capability, with a 36.4% adjustment in reverse stiffness and a 70% adjustment in forward stiffness. The resonance frequency can be reduced from 14.4 Hz to 5.8 Hz by stiffness bidirectional-controllable.

Photo‐Directed Growth of Surface Micro‐Patterns on Photosensitive Semicrystalline Polymers

AbstractPatterning polymeric materials with controllable microstructures can meet diversified requirements and realize promising applications. Exploring micro‐/nano‐pattern methodology offers possibilities for future techniques, however, the self‐organized growth of polymeric materials has some limitations and the development of direct and noncontact patterning processes is still challenging. In this work, the study presents a facile strategy for endowing polymers with spatially regulated microstructures by direct photo‐printing, which incorporates both advantages of typical top‐down and bottom‐up approaches. By employing the photodimerization of anthracene‐containing semi‐crystallized polymers, the gradient crosslinking results in a mismatch of thermal expansion coefficients between the crosslinked surface and the uncrosslinked bottom layer. After heating treatment, constrained by the crosslinked surface, the uncrosslinked bottom polymer of the molten state in the exposed region tends to flow and migrate toward the unexposed region, similar to a volcanic eruption, which accurately determines the height and morphology of pattern. Besides, the well‐defined patterns can controllably grow upon thermal treatment due to phase transformation and migration. The versatility of the proposed strategy not only provides a brand‐new reliable platform to pattern functional materials with photo‐regulated and reversible microstructures, but also promotes the development of smart materials that can find applications in information safety, reversible microfluidics, and electronic devices.

Advances in Directional Liquid Transport Textiles: Mechanism, Construction, and Applications

AbstractThe seamless integration of emerging directional liquid transport (DLT) technology with traditional textile materials has ushered in the next‐generation multifunctional textiles, i.e., DLT textiles, which will play a vital role in areas such as wearable smart materials and ecological environmental protection. To further promote the combination of DLT technology and textile technology, a concise overview of the research progress in DLT textiles, including the basic transport mechanisms, various preparation strategies and diversified applications of DLT textiles is provided. In this review, the theoretical mechanisms of directional transport from the perspective of wetting and wicking is discussed. Besides, the preparation strategies of DLT textiles, and categorized them into three categories is summarized: fiber‐based DLT textiles, fabric‐based DLT textiles, and fiber/fabric hybrid‐based textiles. Subsequently, the current and potential applications of DLT textiles are classified and discussed, mainly focusing on functional clothing, oil‐water separation, fog collection, distillation, sensors, biomedicine, and so on. Finally, the challenges and prospects of DLT textile research to enhance the functionality and application performance is outlined.

Recent Advances in Smart Self-Assembled Bioinspired Hydrogels: A Bridging Weapon for Emerging Health Care Applications from Bench to Bedside.

Stimuli-responsive low molecular weight hydrogel interventions for Biomedical challenges are a rapidly evolving paradigm in the bottom-up approach recently. Peptide-based self-assembled nano biomaterials present safer alternatives to their non-degradable counterparts as demanded for today's most urged clinical needs.Although a plethora of work has already been accomplished, programming hydrogelators with appropriate functionalities requires a better understanding as the impact of the macromolecular structure of the peptides and subsequently, their self-assembled nanostructures remain unidentified. Henceforth this review focuses on two aspects: Firstly, the underlying guidelines for building biomimetic strategies to tailor scaffolds leading to hydrogelation along with the role of non-covalent interactions that are the key components of various self-assembly processes. In the second section, it is aimed to bring together the recent achievements with designer assembly concerning their self-aggregation behaviour and applications mainly in the biomedical arena like drug delivery carrier design, antimicrobial, anti-inflammatory as well as wound healing materials. Furthermore, it is anticipated that this article will provide a conceptual demonstration of the different approaches taken towards the construction of these task-specific designer hydrogels. Finally, a collective effort among the material scientists is required to pave the path for the entrance of these intelligent materials into medicine from bench to bedside.

Autonomous Self-Healing Agents in Cementitious Materials: Parameters and Impacts on Mortar Properties

The concept of self-healing materials and the development of encapsulated curing agents represent a cutting-edge approach to enhancing the longevity and reducing the maintenance costs of cementitious structures. This systematic literature review aims to shed light on the parameters involved in the autonomous self-healing of cementitious materials, utilizing various encapsulated healing agents such as pellets, granules, and capsules. This review also identifies and selects studies that offer additional insights into the efficacy of the self-healing process in cementitious materials and the influence of these specific encapsulated healing agents on the physical mechanical properties of mortars. This comprehensive approach provides a deep understanding of the interplay between self-healing and the physical–mechanical properties of mortars containing these encapsulated healing agents. The main findings indicate that the cement-to-sand ratio, characteristics of fine aggregates, and encapsulation methods significantly impact crack control, self-healing efficiency, and properties of mortar in both fresh and hardened states. The content of encapsulated healing agents within the cementitious matrix affects both the initial workability or flow and subsequent mechanical properties. While pellets coated with PVA film typically reduce workability in the fresh state and compressive strength, capsules coated with Portland cement and sodium silicate mitigate these effects and improve crack sealing in fresh and hardened states without compromising the self-healing capacity of cracks. The three-point flexural test has emerged as the preferred method for a pre-crack assessment over 28 days, with variations depending on the type of healing agent used. As noted in the literature, water has been identified as the optimal environment for autonomous healing. These findings underscore the potential of encapsulation techniques to enhance self-healing capabilities through the controlled release of agents within the cementitious matrix, thereby advancing the research on and development of intelligent construction materials and increasing the durability of cement-based structures.

In-drop capillary spooling and shape-memory behavior of microfiber made from self-healing thermoplastic polyurethane with supramolecular interactions and dynamic covalent bonds

Self-autonomic repair or self-healing is a property of materials that enables them to automatically heal their surfaces from damage, such as scratches and cracks. Intrinsic self-healing has recently garnered significant attention because it can semi-permanently reform the bonds between cracked surfaces. This paper reports the synthesis of thermoplastic polyurethane (TPU) microfibers that heal intrinsically because of multiple hydrogen bonds and disulfide metathesis. The synthesized TPUs contain ureido-pyrimidinone and aromatic disulfide moieties, which form supramolecular interactions and dynamic covalent bonds. The TPU surfaces coated on glass substrates are scratched by a blade, they heal and return to their original state after heat treatment for one hour. The mechanical properties of the TPUs are maximized when the disulfide to quadruple hydrogen bond ratio is 3:7 (TPU-S3U7). Their self-healing efficiency can be improved further by adding more disulfide bonding moieties. As a result, this TPU exhibits the shape-memory effect, and the wet-spun microfibers are completely spooled by buckling into a silicone oil droplet with a diameter of 400 µm. This soft actuating materials can be applied to smart technologies such as smart textiles, smart medical implants, and soft robotics.

Innovative ICT in Smart Buildings Domain: A Pantentometric Analysis

Background: “Smart Building” constructed using “Smart Materials” for “Smart People” and to create or build “Smart Societies or Cities” is the new trend all over the world. Introduction: To implement smartness holistically, it is essential to surf through databases where innovations from all over the world are visible or can be retrieved. A "One stop solution" to locate innovations from specific domains is patent databases and hence this paper showcases the current scenario of civil constructions using AI-ML or alike technologies. Method: Relecura database is primarily used for performing analysis of all the patents related to these two collaborative domains. A special focus is given to the analysis of data from 2015-2021, to know the latest trends in technology used for constructing smart buildings. Result: Smart home, sensors, and machine learning are highly found keywords. China is the leading country for patents in the smart building domain. The use of computational models and pictorial communication can be explored to increase the patentability of the innovation. Conclusion: This patent analysis will be useful to the end readers, researchers, and students to understand the innovative concepts implemented so far and in turn understand the possible research gaps in these collaborative domains.

PH-Sensitive Polymers with their Important Applications (A Review)

Abstract:: Materials that modify their chemical or physical characteristics in reaction to diverse stimuli, such as moisture, heat, water, or pH, are commonly known as smart materials or stimuli-responsive polymers. Typical applications for these polymers include catalysis, finishing, and coating processes. Tissue engineering, drug delivery, and gene transportation are additional applications that have emerged in the past two decades. As a result, their potential use extends to a wider range of applications, encompassing chemical processes, drug delivery, body-site targeting, separation, membrane activity, sensing and actuation, and agriculture. Recently, pH-responsive polymers have garnered considerable interest for implementation in membrane and 4D printing. The current review work encompasses previously published research through 2022, with a particular focus on the critical application of pH-sensitive polymers.

Enhanced Stability-Based Hydroxymethyl Cellulose/Polyacrylamide Interpenetrating Dual Network Hydrogel Electrolyte for Flexible Yarn Zinc-Ion Batteries

As the field of wearable electronics continues to boom, the demand for flexible energy storage devices continues to grow. However, the development of soft energy supply devices with excellent stability is still a challenging task. Traditional hydrogel electrolytes are prone to mechanical deformation, which makes it difficult to maintain the functional stability of flexible yarn due to its short battery life and low wear resistance. Here, we developed a reversible energy-dissipating dual-network hydrogel electrolyte. The hydroxymethyl cellulose (CMC)/polyacrylamide (PAM) hydrogel electrolyte has a tensile deformation of 2700% and a high ionic conductivity of 6.37 × 10−2 S cm−1. The specific capacity of the assembled CMC/PAM-based yarn cell was 170 μAh cm−1 at 1 mA cm−1 and 73.14% after 100 cycles. The excellent performance is attributed to the crosslinked double network structure, in which the introduction of carboxyl groups is conducive to the improvement of hydrophilicity and ionic conductivity. The hydrogen bond and reversible CMC macromolecular chain can be restored after stress relief, which greatly improves the toughness of the material. Even under different bending angles and repeated bending conditions, zinc yarn batteries still have outstanding mechanical properties and cycle stability (71.28% specific capacity after 100 cycles), showing broad application prospects in wearable smart textiles.

Clinic-oriented injectable smart material for the treatment of diabetic wounds: Coordinating the release of GM-CSF and VEGF

Chronic wounds are often caused by diabetes and present a challenging clinical problem due to vascular problems leading to ischemia. This inhibits proper wound healing by delaying inflammatory responses and angiogenesis. To address this problem, we have developed injectable particle-loaded hydrogels which sequentially release Granulocyte-macrophage- colony-stimulating-factor (GM-CSF) and Vascular endothelial growth factor (VEGF) encapsulated in polycaprolactone-lecithin-geleol mono-diglyceride hybrid particles. GM-CSF promotes inflammation, while VEGF facilitates angiogenesis. The hybrid particles (200–1000 nm) designed within the scope of the study can encapsulate the model proteins Bovine Serum Albumin 65 ± 5 % and Lysozyme 77 ± 10 % and can release stably for 21 days. In vivo tests and histological findings revealed that in the hydrogels containing GM-CSF/VEGF-loaded hybrid particles, wound depth decreased, inflammation phase increased, and fibrotic scar tissue decreased, while mature granulation tissue was formed on day 10. These findings confirm that the hybrid particles first initiate the inflammation phase by delivering GM-CSF, followed by VEGF, increasing the number of vascularization and thus increasing the healing rate of wounds. We emphasize the importance of multi-component and sequential release in wound healing and propose a unifying therapeutic strategy to sequentially deliver ligands targeting wound healing stages, which is very important in the treatment of the diabetic wounds.