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Abstract Materials that provide dynamically tunable infrared (IR) response are important for many applications, including active camouflage and thermal management. However, current IR-tunable systems often exhibit limitations in mechanical properties or practicality of their tuning modalities, or require complex and costly fabrication methods. An additional challenge relates to providing compatibility between different spectral channels, such as allowing an object to be reversibly concealed in the IR without making it appear in the visible range. Here, we demonstrate that conducting polymer-cellulose papers, fabricated through a simple and cheap approach, can overcome such challenges. The papers exhibit IR properties that can be electrochemically tuned with large modulation (absolute emissivity modulation of 0.4) while maintaining largely constant response in the visible range. Owing to high ionic and electrical conductivity, the tuning of the top surface can be performed electrochemically from the other side of the paper even at tens of micrometer thicknesses, removing the need for overlaying electrode and electrolyte in the optical beam path. These features enabled a series of electrically tunable IR devices, where we focus on demonstrating dynamic radiative coolers, thermal camouflage, anti-counterfeiting tags, and grayscale IR displays. The conducting polymer-cellulose papers are sustainable, cheap, flexible and mechanically robust, providing a versatile materials platform for active and adaptive IR optoelectronic devices.

Abstract Sepia melanin, a biopigment extracted from the ink sac of cuttlefish, is relevant to sustainable organic electronics. In this work, we flexographically print films from an ink of Sepia melanin including shellac as a bio-sourced binder on silver electrode-patterned paper. We examine the electrical response in high humidity and ambient conditions (here the electronic conductivity is as high as 10−4 S/cm). Additionally, we study the biodegradation of the printed films and their individual constituents based on their mineralization into CO2 under composting conditions. The printed films exhibit biodegradation levels of about 97 ± 25% in 85 d. We observe microorganism colonization on the printed film’s surface. The analysis of the microbial community on the compost reveals that bacterial species within the Acidimicrobiia class, specifically Actinomarinales order, are potentially responsible for the biodegradation of the printed film. Meanwhile, ecotoxicity tests conducted by germinating Lolium multiflorum and Tagetes erecta suggest that printed films have negligible phytotoxicity.

Abstract Paper-based electronics have attracted much attention due to their softness, degradability, and low cost. However, paper-based sensors are difficult to apply to high-humidity environments or even underwater. Here, we report a fully paper-integrated piezoresistive sensing system that exhibits flexibility, waterproofing, air permeability, and biocompatibility. This system consists of hydrophobic paper as the substrate and encapsulation layer, conductive paper with a double ‘zig-zag’ and dotted surface structure as the sensing layer, and silver paste films as the interconnects. The structural design of the sensing layer helps to increase the contact area in adjacent layers under pressure and further improves the pressure sensitivity. The piezoresistive system can be worn on human skin in the ambient environment, wet environment, and water for real-time monitoring of physiological signals with air permeability and waterproofing due to its hydrophobic fiber structure. Such a device provides a reliable, economical, and eco-friendly solution to wearable technologies.

Abstract Flexible sensors have recently attracted much attention for potential applications in motion measurement and wearable health monitoring. In this paper, an environment-friendly, economic, and high-performance paper-based self-inductive folding displacement sensor (PSIFS) was proposed, with displacement resolution of 20 μm and wide measurement range of 43.2 mm. The sensor sensitivity could reach 4.44% mm−1 with the maximum deviation of 0.00904 in experiments. The sensing mechanism based on inductance variation due to three-dimensional deformation of planar inductor coil and structural design principle under two dimensions of sensitivity and size were proposed and studied. The folding method to enhance sensitivity was proposed and 3 times sensitivity enhancement could be achieved by once folding. Multiple breathing states and motion states of the human joints could be recognized. The proposed simple paper-based sensor, folding method to increase sensitivity, and structural design model may provide a way for the research of flexible sensors.

Abstract Paper-based electrochemical sensors provide the opportunity for low-cost, portable and environmentally friendly single-use chemical analysis and there are various reports of surface-functionalized paper electrodes. Here we report a composite paper electrode that is fabricated through designed papermaking using cellulose, carbon fibers (CF), and graphene oxide (GO). The composite paper has well-controlled structure, stable, and repeatable properties, and offers the electrocatalytic activities for sensitive and selective chemical detection. We demonstrate that this CF/GO/cellulose composite paper can be reduced electrochemically using relatively mild conditions and this GO reduction confers electrocatalytic properties to the composite paper. Finally, we demonstrate that this composite paper offers sensing performance (sensitivity and selectivity) comparable to, or better than, paper-based sensors prepared by small-batch surface-modification (e.g., printing) methods. We envision this coupling of industrialized papermaking technologies with interfacial engineering and electrochemical reduction can provide a platform for single-use and portable chemical detection for a wide range of applications.

Abstract Complementary electronics has represented the corner stone of the digital era, and silicon technology has enabled this accomplishment. At the dawn of the flexible and wearable electronics age, the seek for new materials enabling the integration of complementary metal-oxide semiconductor (CMOS) technology on flexible substrates, finds in low-dimensional materials (either 1D or 2D) extraordinary candidates. Here, we show that the main building blocks for digital electronics can be obtained by exploiting 2D materials like molybdenum disulfide, hexagonal boron nitride and 1D materials such as carbon nanotubes through the inkjet-printing technique. In particular, we show that the proposed approach enables the fabrication of logic gates and a basic sequential network on a flexible substrate such as paper, with a performance already comparable with mainstream organic technology.

Abstract Paper, as a foldable, pollution-free, and low-cost material, has become a suitable support substrate for producing flexible thermoelectric (TE) generators to realize waste heat recycling and the application of human-powered electronic devices. We propose a facile fabrication method to modify cellulose paper with inorganic TE powders via vacuum filtration, making a modified paper that possesses good thermoelectric properties. By connecting the modified paper to copper foils, flexible paper-based TE generators (PTGs) are fabricated. The obtained PTG with three units of P–N modules can generate an output voltage of ∼41.2 mV at a temperature difference of 50 K. Based on this modified paper, a thermal sensor that responds to heat sources, such as fingers, is proposed with a rapid response time of 0.25 s. This work offers a promising strategy for the simple fabrication of PTGs, paving the way for achieving the commercial application of self-powered wearable electronics.

Paper is a ubiquitous material used in a range of applications, many of which expose it to fatigue loading. Here, a detailed study of the mechanical response of paper during high‐cycle fatigue loading is reported, with fiber fracture found to be a key degradation mechanism.

Abstract The increasing demands to further electrify and digitalize our society set demands for a green electrical energy storage technology that can be scaled between very small, and heavily distributed electrical energy sources, to very large volumes. Such technology must be compatible with fast-throughput, large-volume and low-cost fabrication processes, such as using printing and coating techniques. Here, we demonstrate a sequential production protocol to fabricate supercapacitors including electrodes based on cellulose nanofibrils (CNF) and the conducting polymer PEDOT:PSS. Thin and lightweight paper electrodes, carbon adhesion layers and the gel electrolyte are fabricated using spray coating, screen printing, and bar coating, respectively. These all solid-state supercapacitors are flexible, mechanically robust and exhibit a low equivalent series resistance (0.22 Ω), thus resulting in a high power density (∼104 W/kg) energy technology. The supercapacitors are combined and connected to a power management circuit to demonstrate a smart packaging application. This work shows that operational and embedded supercapacitors can be manufactured in a manner to allow for the integration with, for instance smart packaging solutions, thus enabling powered, active internet-of-things (IoT) devices in a highly distributed application.

Desktop printers and sprayers powering flexible electronics The power of commercial printers and spray coaters has been brought together to fasten the prototyping of flexible electronics. A collaborative team led by Prof Oana Jurchescu from Wake Forest University, US design an aerosol spray laser lithography approach to make patterned electrode arrays with low cost. The lithography step is realized by a desktop laser printer while the toner acts as the photoresist. The electrodes are deposited with spray coating of metal inks, followed by a heat-assisted transfer or peel-off process to finish the patterning. They then printed organic thin-film transistor arrays on paper and show that the devices work well under normal and bending conditions. This approach has proven successful, easy and compatible in fabricating flexible transistor arrays. It can be expected to fasten the pace in prototyping and manufacturing of flexible electronics.

Transparent perovskite solar cells on paper Modified nanocellulose paper has been shown to be excellent biodegradable substrate for flexible perovskite solar cells and potentially other green flexible devices. A team of Chinese scientists led by Prof Wei Huang from Institute of Advanced Materials, Nanjing Tech University fabricate flexible perovskite solar cells on transparent nanocellulose paper. This becomes feasible only after they develop a treatment recipe to improve the mechanical, optical properties and the waterproof ability of the pure nanocellulose paper. The flexible solar cells on the modified substrates show high specific power of 0.56 W g-1 and good stability and mechanical durability. Another key advantage of nanocellulose paper is its biodegradation capability, making it a better substrate compared to PEN and PET for the next generation green flexible electronics.

Glucose in saliva tested by paper sensors Saliva based glucose test can now be made easily and cheaply with inkjet-printed paper sensors enabled by enzyme glucose oxidase. Most present technologies rely on blood tests to monitor glucose concentration. To tackle this problem, a collaborative international team led by Prof Sahika Inal from King Abdullah University of Science and Technology, Saudi Arabia designs disposable glucose sensors based on saliva testing. They construct the analytical device by ink-jet printing cheap conducting polymer, an enzyme containing biological film and an encapsulation layer on paper substrates to measure glucose concentrations in human saliva. The devices stay active for more than a month in air-free storage conditions with minor performance losses. The high versatility and adaptability of the material system enable the possibilities to design affordable and expandable enzyme testing based diagnostic platforms.

Abstract Printing of electronics is pursued as a low-cost alternative to conventional manufacturing processes. In addition, owing to relatively low process temperatures, flexible substrates can be used enabling novel applications. Among flexible substrates, paper was found to be a particularly interesting candidate, since it has an order of magnitude lower price than low-cost polymer alternatives, and is biodegradable. As ink materials, organic and metal-oxide semiconductors are thoroughly being investigated; however, they lack in electric performance compared to silicon in terms of device mobility, reliability, and energy efficiency. In recent years, liquid precursors for silicon were found and used to create polycrystalline silicon (poly-Si). However, fabrication of transistors on top of low-cost flexible substrates such as paper has remained an outstanding challenge. Here we demonstrate both p-channel and n-channel poly-Si thin-film transistors (TFTs) fabricated directly on top of paper with field-effect mobilities of 6.2 and 2.0 cm2/V s, respectively. Many fabrication challenges have been overcome by limiting the maximum process temperature to approximately 100 °C, and avoiding liquid chemicals commonly used for etching and cleaning. Patterning of poly-Si has been achieved by additive selective crystallization of the precursor film using an excimer laser. This work serves as a proof of concept, and has the potential to further improve device performance. Owing to the low-cost, biodegradable nature of paper, and the high performance, reliability, and energy efficiency of poly-Si TFTs, this work opens a pathway toward truly low-cost, low-power, recyclable applications including smart packages, biodegradable health monitoring units, flexible displays, and disposable sensor nodes.

Abstract Lightweight refractory high-entropy alloys (LW-RHEAs) hold significant potential in the fields of aviation, aerospace, and nuclear energy due to their low density, high strength, high hardness, and corrosion resistance. However, the enormous composition space has severely hindered the development of novel LW-RHEAs with excellent comprehensive performance. In this paper, an machine learning (ML)-based alloy design strategy combined with a multi-objective optimization method was proposed and applied for a rational design of Al-Nb-Ti-V-Zr-Cr-Mo-Hf LW-RHEAs. The quantitative relation of “composition-structure-property” was first established by ML modeling. Then, feature analysis reveals that Cr content greater than 12 at.% is a key criterion for alloys with high corrosion resistance. The phase structure, density, melting point, hardness and corrosion resistance of the alloys were screened layer by layer, and finally, three LW-RHEAs with superb hard and corrosion resistance were successfully designed. Key experimental validation indicates that three target alloys have densities around 6.5 g/cm3, and all alloys are disordered bcc_A2 single-phase with the highest hardness of 593 HV and the largest pitting potential of 2.5 VSCE, which far exceeds all the literature reports. The successful demonstration in this paper clearly demonstrates that the present design strategy driven by the ML technique should be generally applicable to other RHEA systems.

Abstract Recently electronic tattoo sensors have attracted immense interest for health monitoring mainly due to their higher sensing performance than conventional dry sensors, owing to the ultra-low thickness which results in their conformability to the skin. However, their performance is worse than wet sensors. Further, these electronic tattoo sensors are not durable and reusable when free-standing because of their low thickness and being too delicate. Here, we report a remarkably high-performance freestanding, reusable, ultrathin and ultra-soft electronic tattoo sensor made of parylene-hydrogel double layer system with high water retention over extended periods that can be used for the extended period of 6 months. The hydrogel electronic tattoo (HET) sensors consist of electrically conductive self-adhesive hydrogel with a thickness of 20 µm and Young’s modulus of only 31 kPa at 37 °C, allowing for ultra-conformal contact to the skin microscopic features. Our HET sensors are fabricated using a scalable cost-effective method on ordinary tattoo papers and are laminated on the skin like temporary tattoos and were used for electrophysiological signals recording such as electrocardiography (ECG), electromyography (EMG), and skin hydration, temperature sensing. The HET sensors, for the first time, show 234% lower sensor-skin interface impedance (SSII) and significantly lower susceptibility to motion than gold standard medical grade silver/silver chloride wet gel electrodes which are known to have the lowest SSII and susceptibility to motion. Further, the low HET-skin interface impedance leads to a considerably larger signal amplitude and signal-to-noise ratio (SNR) of the electrophysiological signals recorded using HET sensors in comparison with those obtained using gold standard medical grade silver/silver chloride wet gel electrodes. The SNR of some types of electrophysiological signals such as EMG recorded using HET is up to 19 dB higher than gold standard medical grade electrodes due to higher signal amplitude, significantly lower susceptibility of HET to motion and lower motion artifacts. Also, the HET sensor is the first free-standing ultrathin tattoo sensor that can be transferred from the skin to tattoo paper and vice versa many times and the electrophysiological sensing quality remained high during repeated use for over 6 months.

Abstract In this paper we address the question of whether high-temperature superconductors have anything in common with BCS-BEC crossover theory. Towards this goal, we present a proposal and related predictions which provide a concrete test for the applicability of this theoretical framework. These predictions characterize the behavior of the Ginzburg-Landau coherence length, $${\xi }_{0}^{{{{\rm{coh}}}}}$$ ξ 0 coh , near the transition temperature T c, and across the entire superconducting T c dome in the phase diagram. That we are lacking a systematic characterization of $${\xi }_{0}^{{{{\rm{coh}}}}}$$ ξ 0 coh in the entire class of cuprate superconductors is perhaps surprising, as it is one of the most fundamental properties of any superconductor. This paper is written to motivate further experiments and, thus, address this shortcoming. Here we show how measurements of $${\xi }_{0}^{{{{\rm{coh}}}}}$$ ξ 0 coh contain direct indications for whether or not the cuprates are associated with BCS-BEC crossover and, if so, where within the crossover spectrum a particular superconductor lies.

Abstract Wearable sweat sensors are becoming increasingly popular for their robust capabilities in non-invasive, dynamic, and continuous real-time monitoring of biological information. Real-time monitoring of large-scale samples is crucial for realizing intelligent health. A major bottleneck for enabling large-scale sweat elucidation is the fabrication of wearable sensors equipped with microfluidic devices and flexible electrodes in a cost-effective, homogeneous performance and rapid large-scale way. Herein, a “Screen+Wax”-printing technique was introduced to prepare these components and construct “Lego Bricks” type wearable sweat sensor sensor to monitor sweat Na+ and K+. Flexible electrode arrays and paper-based microfluidic layers (they act as building blocks) were fabricated on polyethylene terephthalate and paper surfaces, respectively, using screen printing and wax printing. Gold nanoparticles and Na+/K+ ion-selective membranes were modified on the electrode surfaces by electrodeposition and drop coating, respectively. In this work, we highlight the excellent performance of the “Lego Bricks” type wearable sweat sensor in testing the Na+ and K+ imbalance of sweat from different body regions during exercise and, more significantly, to track the physical activity during prolonged exercise under different interventions. Furthermore, the prepared “Lego Bricks” wearable sweat ion electrochemical sensor is demonstrated to be capable of large-scale samples elucidation with outstanding performance and cost-effectiveness, which is expected to deeply integrate sweat monitoring into physical activity, providing an important tool for intelligent health.

Abstract Glue laminated bamboo (glubam) is a type of engineered bamboo material developed for applications in building structures and interiors. This paper focuses on the fungal (Aspergillus niger) colonization from 14 to 56 days in thick- and thin-strip glubam board with the investigation of physical, mechanical (compression), and microcosmic properties. Two-degree of carbonization treatment was employed to improve the antifungal property of the thick-strip glubam. After 56 days of infection, the deep-degree carbonized thick-strip glubam presents better anti-mold properties than medium and non-carbonized specimens. For thin-strip glubam, both parallel and perpendicular to the main bamboo fiber direction were considered. The longitudinal thin-strip glubam retains decent compressive properties, while the transverse specimens stay a stable compressive strength along all fungal tests. The paper reports the experimental values of mass loss, color changes, compressive strengths, modulus of elasticity in compression, and microstructure observations from optical and SEM microscopy at different fungal exposure timespans.

Abstract Herein, the deteriorating aspects of a historical manuscript (papers and leather bookbinding) dated back to the 17th century were evaluated with reference to the role of the associated fungal communities. The deterioration signs were investigated using visual assessment, SEM, ATR-FTIR, XRD, color changes, and pH values compared with control. Data showed that the most deterioration aspects were represented by the dust, dirt, erosion, stains, bores, weakness, missed parts, decreasing in paper crystallinity, shifting of wavenumbers of cellulosic band, and changing of color and pH. The dependent-culturable technique showed that thirteen fungal strains were associated with historical manuscript and identified using traditional and molecular methods as Aspergillus niger (three isolates), A. fumigatus (two isolates), A. quadrilineatus (three isolates), Penicillium citrinum (two isolates), and P. chrysogenium (three isolates). These fungal strains showed high efficacy to secretion various hydrolytic enzymes including cellulase, amylase, gelatinase, and pectinase which play a critical role in biodeterioration.

Abstract Prolonged contact between a corrosive liquid and metal alloys can cause progressive dealloying. For one such process as liquid-metal dealloying (LMD), phase field models have been developed to understand the mechanisms leading to complex morphologies. However, the LMD governing equations in these models often involve coupled non-linear partial differential equations (PDE), which are challenging to solve numerically. In particular, numerical stiffness in the PDEs requires an extremely refined time step size (on the order of 10−12 s or smaller). This computational bottleneck is especially problematic when running LMD simulation until a late time horizon is required. This motivates the development of surrogate models capable of leaping forward in time, by skipping several consecutive time steps at-once. In this paper, we propose a U-shaped adaptive Fourier neural operator (U-AFNO), a machine learning (ML) based model inspired by recent advances in neural operator learning. U-AFNO employs U-Nets for extracting and reconstructing local features within the physical fields, and passes the latent space through a vision transformer (ViT) implemented in the Fourier space (AFNO). We use U-AFNOs to learn the dynamics of mapping the field at a current time step into a later time step. We also identify global quantities of interest (QoI) describing the corrosion process (e.g., the deformation of the liquid-metal interface, lost metal, etc.) and show that our proposed U-AFNO model is able to accurately predict the field dynamics, in spite of the chaotic nature of LMD. Most notably, our model reproduces the key microstructure statistics and QoIs with a level of accuracy on par with the high-fidelity numerical solver, while achieving a significant 11, 200 × speed-up on a high-resolution grid when comparing the computational expense per time step. Finally, we also investigate the opportunity of using hybrid simulations, in which we alternate forward leaps in time using the U-AFNO with high-fidelity time stepping. We demonstrate that while advantageous for some surrogate model design choices, our proposed U-AFNO model in fully auto-regressive settings consistently outperforms hybrid schemes.

Abstract Recent advances in additive manufacturing have enabled the creation of three-dimensional (3D) architectured pyrolytic carbon (PyC) structures with ultrahigh specific strength and energy absorption capabilities. However, their scalability is limited by reduced strength at larger sizes. Here we introduce a modular assembling approach to scale up PyC lattice structures while retaining strength. Three assembling mechanisms—adhesive, Lego-adhesive, and mechanical interlocking—are explored, demonstrating notably increased specific compressive strength and modulus as size increases, driven by energy release from assembly joint fractures. Practical application is demonstrated by using assembled PyC lattices as the core of an aerospace sandwich structure, significantly enhancing indentation resistance compared to conventional aramid paper honeycomb core. The method also enables versatile designs, including curved structures for space debris protection and bio-scaffold applications. This scalable approach offers a promising pathway for integrating PyC structures into large-scale engineering applications requiring superior mechanical properties and programmability in complicated shape design.

Abstract Flexible integrated circuits (FlexICs) have drawn increasing attention, particularly in remote sensors and wearables operating in a limited power budget. Here, we present an ultra-low power timer designed to wake-up an external circuit periodically, from a deep-sleep state into an active state, thereby largely reducing the system power consumption. We achieved this with a circuit topology that exploits the transistor’s leakage current to generate a low frequency wake-up signal. This topology is compatible with IC technologies where only n-type transistors are available. The design was implemented with the sustainable FlexIC process of PragmatIC, that is based on Indium Gallium Zinc Oxide (IGZO) thin-film transistors. Our timer generates mean wake-up frequency of 0.24 ± 0.15 Hz, with a mean power consumption of 26.7 ± 14.1 nW. In this paper, we provide details of the Wake-Up timer’s design and performance at different supply voltages, under temperature variations and different light conditions.

Abstract Exploring sustainable alternative constituents is a key pathway to carbon-neutralization of concrete, but often limited to insufficient understandings of how they interact with conventional concrete components at microscale. In this paper we reviewed the most cutting-edge microprobes used for such purposes, from both laboratory setup to synchrotron radiation-based techniques. We also provided practical guidelines on sample preparation and result analysis, which could benefit researchers who plan to adopt these methods

Abstract Memristors offer vast application opportunities in storage, logic devices, and computation due to their nonvolatility, low power consumption, and fast operational speeds. Two-dimensional materials, characterized by their novel mechanisms, ultra-thin channels, high mechanical flexibility, and superior electrical properties, demonstrate immense potential in the domain of high-density, fast, and energy-efficient memristors. Hexagonal boron nitride (h-BN), as a new two-dimensional material, has the characteristics of high thermal conductivity, flexibility, and low power consumption, and has a significant application prospect in the field of memristor. In this paper, the recent research progress of the h-BN memristor is reviewed from the aspects of device fabrication, resistance mechanism, and application prospect.

Abstract Charge density wave (CDW) is discovered within a wide interval in solids, however, its microscopic nature is still not transparent in most realistic materials, and the recently studied chiral ones with chiral structural distortion remain unclear. In this paper, we try to understand the driving forces of chiral CDW transition by chiral phonons from the electron-phonon coupling scenario. We use the prototypal monolayer 1T-TiSe2 as a case study to unveil the absence of chirality in the CDW transition and propose a general approach, i.e., symmetry-breaking stimuli, to engineer the chirality of CDW in experiments. Inelastic scattering patterns are also studied as a benchmark of chiral CDW (CCDW, which breaks the mirror/inversion symmetry in 2D/3D systems). We notice that the anisotropy changing of Bragg peak profiles, which is contributed by the soft chiral phonons, can show a remarkable signature for CCDW. Our findings pave a path to understanding the CCDW from the chiral phonon perspective, especially in van der Waals materials, and provides a powerful way to manipulate the chirality of CDW.

Abstract Predicting the properties of non-fullerene acceptors (NFAs), complex organic molecules used in organic solar cells (OSCs), poses a significant challenge. Some existing approaches primarily focus on atom-level information and may overlook high-level molecular features, including the subunits of NFAs. While other methods that effectively represent subunit information show improved prediction performance, they require labor-intensive data labeling. In this paper, we introduce an efficient molecular description method that automatically extracts molecular information at both the atom and subunit levels without any labor-intensive data labeling. Inspired by the Word2Vec method, our Ring2Vec method treats the “rings” in organic molecules as analogous to “words” in sentences. We achieve fast and accurate predictions of the energy levels of NFA molecules, with a minimal prediction error of merely 0.06 eV. Furthermore, our method can potentially have broad applicability across various domains of molecular description and property prediction, owing to the efficiency of the Ring2Vec model.

Abstract Transparent conducting oxides (TCOs) are crucial for high-performance displays, solar cells, and wearable sensors. However, their high process temperatures and brittle nature have hindered their use in flexible electronics. In this paper, we overturn these limitations by harnessing Cabrera-Mott oxidation to fabricate large-area, two-dimensional (2D) transparent electrodes via liquid metal printing. Our robotic, vacuum-free process deposits ultrathin (2–10 nm) indium tin oxide (ITO) with exceptional flexibility, transparency (>95%) and conductivity (>1300 S/cm) by utilizing hypoeutectic In-Sn alloys to print at

Abstract Electrical stimulation is effective for various therapeutic applications; however, to increase convenience, it is crucial to eliminate generators and batteries for wireless power transmission. This paper presents a full textile-based body-coupled electrical stimulation (BCES) system designed for wireless electrical stimulation using energy loss from electronic devices and static electricity from physical activity. We developed the BCES socks by knitting conductive threads to ensure stability and comfort. BCES socks generate electric fields ranging from tens to hundreds of millivolts per millimeter, which are sufficient to activate muscle fibers. Experimental and computational analyses confirmed the effective concentration of the electric fields. Human trials demonstrated significant improvements in exercise performance, with a 21.47% increase in calf raise frequency, an 11.97% increase in repetition count, and a 6.25% reduction in muscle fatigue. These results indicate the potential of BCES socks as a practical battery-free solution for enhancing muscle activity and reducing fatigue.

Abstract Metal nanoparticles have extraordinary properties, but their integration into mesostructures has been challenging. Producing uniformly dispersed nanoparticles attached to substrates in industrial quantities is difficult. Herein, a “plasmashock” method was developed to synthesize metal nanoparticles anchored on different types of carbonaceous substrates using liquid salt solution precursors. These self-supporting, nanoparticle-loaded carbon fabrics are mechanically robust and have been tested as antibacterial substrates and electrocatalysts for reducing carbon dioxide and nitrite. A piece of silver–carbon nanotube paper with a silver loading of ~0.13 mg cm−2 treated after a few-second plasmashock presents good antibacterial and electrocatalytic properties in wastewater, even after 20 bactericidal immersion cycles, due to the strong bonding of the nanoparticles to the substrate. The results prove the effectiveness of this plasmashock method in creating free-standing functional composite films or membranes.

Abstract Materials datasets usually contain many redundant (highly similar) materials due to the tinkering approach historically used in material design. This redundancy skews the performance evaluation of machine learning (ML) models when using random splitting, leading to overestimated predictive performance and poor performance on out-of-distribution samples. This issue is well-known in bioinformatics for protein function prediction, where tools like CD-HIT are used to reduce redundancy by ensuring sequence similarity among samples greater than a given threshold. In this paper, we survey the overestimated ML performance in materials science for material property prediction and propose MD-HIT, a redundancy reduction algorithm for material datasets. Applying MD-HIT to composition- and structure-based formation energy and band gap prediction problems, we demonstrate that with redundancy control, the prediction performances of the ML models on test sets tend to have relatively lower performance compared to the model with high redundancy, but better reflect models’ true prediction capability.

Abstract The durability of polymer electrolyte fuel cells (PEFCs) in fuel cell electric vehicles is important for the shift from passenger cars to heavy-duty vehicles. The components of a PEFC, namely the proton exchange membrane (PEM), catalyst layer (CL), and gas diffusion layer (GDL), contribute to the degradation of the fuel cell performance. In this paper, we propose a method for simultaneously evaluating the degradation rates of these components by combining electrochemical characterization with operando synchrotron X-ray radiography. The open-circuit voltage, electrochemically active surface area (ECSA), and water saturation were used as the degradation indicators for the PEMs, CLs, and GDLs, respectively. The results of two accelerated stress tests (loading and start-stop cycles) after 10,000 cycles showed that the increase in water saturation owing to the loss of hydrophobicity due to carbon corrosion in the cathode GDL occurred on the same timescale as the degradation in the PEM and cathode CL. Specifically, during the load cycle AST, the cathode CL degraded with a 26% reduction in the ECSA along with the cathode GDL degradation with a 10% increase in water saturation. This suggests that more efforts should be devoted to studies on the durability of GDLs for heavy-duty applications.

Abstract Neuromorphic computing has emphasized the need for memristors with non-volatile, multiple conductance levels. This paper demonstrates the potential of hexagonal boron nitride (hBN)/graphene heterostructures to act as memristors with multiple resistance states that can be optically tuned using visible light. The number of resistance levels in graphene can be controlled by modulating doping levels, achieved by varying the electric field strength or adjusting the duration of optical illumination. Our measurements show that this photodoping of graphene results from the optical excitation of charge carriers from the nitrogen-vacancy levels of hBN to its conduction band, with these carriers then being transferred to graphene by the gate-induced electric field. We develop a qualitative model to describe our observations. Additionally, utilizing our device architecture, we propose a memristive crossbar array for vector-matrix multiplications.

Abstract Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws rely on phenomenological models of the underlying physics, whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and stress. This tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress, temperature, and local environment, such as body-centered cubic crystals (BCC) metals and alloys. In this paper, we present a novel, uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations, using Graph Neural Networks (GNN) with a physics-informed architecture. We demonstrate that this Physics-informed Graph Neural Network (PI-GNN) framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

Abstract Electric heaters based on functional materials and innovative designs have been developed for various applications. In this paper, we propose a soft dielectric heater (SDH) using polyvinyl chloride-gel (PVC-gel) as the dielectric heater and hydrogel as stretchable electrodes. Under an AC voltage, the leakage current in the PVC-gel leads to continuous injection and discharge of charges, causing the polarized plasticizers and flexible PVC chains to vibrate and collide, thereby generating heat through dielectric heating. Furthermore, the SDH generates a uniform temperature distribution even under strains up to 400%. Besides, high transmittance over 86% across the visible range renders it suitable for wearable or skin-mountable heaters from an esthetic viewpoint. Its capacitor-like structure achieves a scalable design, enabling extension from a singular cell to a row/column addressable and pixelated array of heaters. The 5 × 5 SDH array can deliver varied thermal information and sensations while maintaining performance even when stretched.

Abstract Daily monitoring of internal tissues with shape-conformable and breathable ultrasound (US) imaging probes is promising for early detection of diseases. In recent years, textile substrates are widely used for wearable devices since they satisfy both conformability and breathability. However, it is not currently possible to use textile substrates for US probes due to the reflection or attenuation of US waves at the air gaps in the textiles. In this paper, we fabricated a shape-conformable and breathable US imaging probe by sandwiching the US elements between two woven polyester textiles on which copper electrodes were formed through electroless plating. The air gaps between the fibers at the electrode parts were filled with copper, allowing for high penetration of US waves. On the other hand, the non-electrode parts retain air gaps, leading to high breathability. The fabricated textile-based probe showed low flexural rigidity (0.066 × 10−4 N m2 m−1) and high air permeability (11.7 cm3 cm−2 s−1). Human neck imaging demonstrated the ability of the probe to monitor the pulsation of the common carotid artery and change in the internal jugular vein diameter, which led to the early detection of health issues such as arteriosclerosis and dehydration, and the capability of stable 24-hour monitoring.

Abstract Offshore wind energy is pivotal for achieving global renewable energy targets. As of 2022, 12% of global electricity is derived from wind and solar power, with an imperative to reach 90% renewable energy by 2050. The offshore wind industry, constituting 7.1% of global wind power, plays a central role in meeting these goals. The Global Wind Energy Alliance envisions reaching 380 GW by 2030 and 2000 GW by 2050. This paper addresses corrosion challenges in the offshore environment, emphasising sacrificial coatings as an effective mitigation strategy. By critically evaluating the latest revisions of widely used international standards such as Norsok M-501, ISO 12944, and VGBE-S-021, the study focuses on zinc- and aluminium-rich coatings that form a galvanic couple with steel, providing cathodic protection. Liquid coatings, thermally sprayed coatings, and hot-dip galvanised coatings are examined for their applicability with discussion on the advantages and limitations of these systems. Considerations of cost, environmental impact, and testing methods are crucial in selecting corrosion mitigation strategies. The review alludes to these requirements and highlights the significance of durable solutions, such as sacrificial coatings, in ensuring the long-term integrity of offshore wind structures amid the sector’s rapid expansion. Further collaborative research, involving industry and academia, is recommended to refine testing regimes and explore innovative coating solutions.

Abstract Sensor degradation poses a critical yet ‘often overlooked’ challenge in accurately predicting the remaining useful life (RUL) of nuclear reactor pressure vessels (RPVs), hindering safe and efficient plant operation. This paper introduces an approach to RUL estimation that explicitly addresses sensor degradation, a significant departure from conventional methods. We model neutron embrittlement, a dominant degradation process in RPV steel, as a Wiener process and leverage real-world surveillance capsule data for insightful parameterization. Maximum likelihood estimation is utilized to characterize the degradation dynamics in the model. A Kalman filter then seamlessly integrates the degradation model with sensor measurements, effectively compensating for degradation-induced errors and providing refined state estimates. These estimates power a robust RUL prediction framework. Our results expose the profound impact of sensor degradation on conventional RUL predictions. By directly confronting sensor degradation, our method yields substantially more accurate and reliable RUL estimates. This work marks a significant advancement in the field of materials degradation, offering a powerful tool to optimize nuclear power plant safety and longevity.

Abstract This paper provides a study for crystallographic orientation-dependent corrosion rate of aluminum employing an ab initio model with inputs from first-principles calculations. Results showed that the sequence of corrosion rate is in the order of (111)

Abstract In this paper, we introduce an innovative approach for generating robotic faces with a thermal signature similar to that of humans and equipping prosthetic or robotic hands with a lifelike temperature distribution. This approach enhances their detection via infrared cameras and promotes more natural interactions between humans and robots. This method integrates a temperature regulation system into artificial skin, drawing inspiration from the human body’s natural temperature control via blood flow. Central to this technique is a fiber network simulating blood vessels within the artificial skin. Water flows through these fibers under specific temperature and flow conditions, forming a controlled heat release system. The heat emission can be adjusted by changing the dilation of these fibers, primarily by modulating the frequency of circulation. Our findings indicate that this approach can replicate the varied thermal characteristics of different human faces and hand areas. Consequently, the robotic faces appear more human-like in infrared images, aiding their identification by infrared cameras. At the same time, the prosthetic hands achieve a more natural temperature, reducing the discomfort typically felt in direct contact with synthetic limbs. The aim of this study was to address the challenges faced by the users of prosthetic hands. The results from this study show a promising direction in humanoid robotics, fostering improved tactile interactions and redefining human–robot relationships. This innovative technique facilitates further advancements, blurring the lines between artificial aids and natural biological systems.

Abstract As a stress hormone existing in the human body, cortisol can reflect the psychological stress and health status in daily life, and is a potential biomarker of the body’s stress response. To effectively collect sweat and accurately identify the target, this paper reports a flexible wearable cortisol detection device with outstanding reliability and sensitivity. Molecular imprinted polymer (MIP) ensures cortisol specificity. And carbon nanotubes (CNT) on electrodes increase sensitivity, expanding the detection range to 10−3 to 104 nM, with sensitivity at 189.2 nA/lg(nM). In addition, porous chitosan hydrogel (PCSH) collects sweat effectively, its adhesive properties and 80% swelling rate offer a low-cost alternative to microfluidics. Flexible printed circuit board (FPCB) and serpentine electrode (SE) ensure device durability. This non-invasive, highly sensitive device offers a novel method for mental stress monitoring and clinical diagnosis, advancing human physiological state monitoring.

Abstract Herein, we report on conductive ultrathin films (nanosheets) with the characteristics of stretchability and water vapor permeability for skin-conformable bioelectrodes. The films are fabricated by combining conductive fibrous networks of single-wall carbon nanotubes (SWCNTs) and poly(styrene-b-butadiene-b-styrene) (SBS) nanosheets (i.e., SWCNT-SBS nanosheets). An increase in the number of SWCNT coatings increases both the thicknesses and densities of the SWCNT bundles. The SBS nanosheets coated with three layers of SWCNTs (i.e., SWCNT 3rd-SBS nanosheets) show comparable sheet resistance to the SBS nanosheets coated with poly(3,4-ethylenedioxithiophene) doped with poly(4-styrenesulfonate acid) (PEDOT:PSS) containing 5 wt.% butylene glycol (i.e., PEDOT:PSS/BG5-SBS nanosheets). In addition, the SWCNT 3rd-SBS nanosheets exhibit significantly reduced elastic moduli and increased elongations at break compared to the PEDOT:PSS/BG5-SBS nanosheets. Furthermore, the calculated water vapor transmission ratio of the 210-nm-thick SBS nanosheets (268,172 g m−2 (2 h)−1) is greater than that of the filter paper (6345 g m−2 (2 h)−1). The SWCNT 3rd-SBS nanosheets attached to model skin show high tolerances to bending and artificial sweat at different pH values (i.e., the electrical resistance changes ~1.1 times). Finally, the SWCNT 3rd-SBS nanosheet is applied to detect the surface electromyogram from the forearm of a subject. This nanosheet displays a signal-to-noise ratio similar to that of the PEDOT:PSS/BG5-SBS nanosheet.

Abstract Lead-free Cs3Bi2I9 single crystals have been demonstrated to be promising materials for direct X-ray detectors with remarkable performance. However, their application for 2D X-ray imaging is hindered by their time-consuming preparation and limited crystal size. In this paper, a thick Cs3Bi2I9 perovskite film fabricated via facile spray coating at a low processing temperature, which increases the area of the photoactive film, reduces the processing time, decreases the energy budget and the production cost, and enhances the production yield due to high material utilization, has great potential for commercial applications. Careful control of the processing temperature and intervals during spray coating results in a dense and thick perovskite film with well-stacked perovskite domains. The compact perovskite film enhances the charge transport capability of the Cs3Bi2I9 perovskite film and reduces the dark current density of the X-ray detector. The resultant X-ray detector, prepared through a two-step spray coating process, exhibited a sensitivity of 127.23 μC Gyair −1 cm−2 and a detection limit of 7.4 μGyair s−1. In addition, the device delivers long-term stability with a consistent photoresponse when exposed to consecutive X-ray pulse irradiation.

Abstract High-throughput materials research is strongly required to accelerate the development of safe and high energy-density lithium-ion battery (LIB) applicable to electric vehicle and energy storage system. The artificial intelligence, including machine learning with neural networks such as Boltzmann neural networks and convolutional neural networks (CNN), is a powerful tool to explore next-generation electrode materials and functional additives. In this paper, we develop a prediction model that classifies the major composition (e.g., 333, 523, 622, and 811) and different states (e.g., pristine, pre-cycled, and 100 times cycled) of various Li(Ni, Co, Mn)O2 (NCM) cathodes via CNN trained on scanning electron microscopy (SEM) images. Based on those results, our trained CNN model shows a high accuracy of 99.6% where the number of test set is 3840. In addition, the model can be applied to the case of untrained SEM data of NCM cathodes with functional electrolyte additives.

Abstract In the era of ubiquitous computing with flourished visual displays in our surroundings, the application of haptic feedback technology still remains in its infancy. Bridging the gap between haptic technology and the real world to enable ambient haptic feedback on various physical surfaces is a grand challenge in the field of human-computer interaction. This paper presents the concept of an active electronic skin, characterized by three features: richness (multi-modal haptic stimuli), interactivity (bi-directional sensing and actuation capabilities), and invisibility (transparent, ultra-thin, flexible, and stretchable). By deploying this skin on physical surfaces, dynamic and versatile multi-modal haptic display, as well as tactile sensing, can be achieved. The potential applications of this skin include two categories: skin for the physical world (such as intelligent home, intelligent car, and intelligent museum), and skin for the digital world (such as haptic screen, wearable device, and bare-hand device). Furthermore, existing skin-based haptic display technologies including texture, thermal, and vibrotactile feedback are surveyed, as well as multidimensional tactile sensing techniques. By analyzing the gaps between current technologies and the goal of ambient haptics, future research topics are proposed, encompassing fundamental theoretical research on the physiological and psychological perception mechanisms of human skin, spatial-temporal registration among multimodal haptic stimuli, integration between sensing and actuation, and spatial-temporal registration between visual and haptic display. This concept of active electronic skin is promising for advancing the field of ambient haptics, enabling seamless integration of touch into our digital and physical surroundings.

Abstract Intensive research has been carried out on two-dimensional materials, in particular molybdenum disulfide, towards high-performance field effect transistors for integrated circuits1. Fabricating transistors with ohmic contacts is a challenging task due to the formation of a high Schottky barrier that severely limits the performance of the transistors for real-world applications. Graphene-based heterostructures can be used in addition to, or as a substitute for unsuitable metals. In this paper, we present lateral heterostructure transistors made of scalable chemical vapor-deposited molybdenum disulfide and chemical vapor-deposited graphene achieving a low contact resistances of about 9 kΩ·µm and high on/off current ratios of 108. Furthermore, we also present a theoretical model calibrated on our experiments showing further potential for scaling transistors and contact areas into the few nanometers range and the possibility of a substantial performance enhancement by means of layer optimizations that would make transistors promising for use in future logic integrated circuits.

Abstract The vast compositional and configurational spaces of multi-element metal halide perovskites (MHPs) result in significant challenges when designing MHPs with promising stability and optoelectronic properties. In this paper, we propose a framework for the design of B-site-alloyed ABX3 MHPs by combining density functional theory (DFT) and machine learning (ML). We performed generalized gradient approximation with Perdew–Burke–Ernzerhof functional for solids (PBEsol) on 3,159 B-site-alloyed perovskite structures using a compositional step of 1/4. Crystal graph convolution neural networks (CGCNNs) were trained on the 3159 DFT datasets to predict the decomposition energy, bandgap, and types of bandgaps. The trained CGCNN models were used to explore the compositional and configurational spaces of 41,400 B-site-alloyed ABX3 MHPs with a compositional step of 1/16, by accessing all possible configurations for each composition. The electronic band structures of the selected compounds were calculated using the hybrid functional (PBE0). Then, we calculated the optical absorption spectra and spectroscopic limited maximum efficiency of the selected compounds. Based on the DFT/ML-combined screening, 10 promising compounds with optimal bandgaps were selected, and from among these 10 compounds, CsGe0.3125Sn0.6875I3 and CsGe0.0625Pb0.3125Sn0.625Br3 were suggested as photon absorbers for single-junction and tandem solar cells, respectively. The design framework presented herein is a good starting point for the design of mixed MHPs for optoelectronic applications.