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Future exploitation of marine resources in a sustainable and eco-friendly way requires autonomous underwater robotics with human-like perception. However, the development of such intelligent robots is now impeded by the lack of adequate underwater haptic sensing technology. Inspired by the populational coding strategy of the human tactile system, we harness the giant magnetoelasticity in soft polymer systems as an innovative platform technology to construct a multimodal underwater robotic skin for marine object recognition with intrinsic waterproofness and a simple configuration. The bioinspired magnetoelastic artificial skin enables multiplexed tactile modality in each single taxel and obtains an impressive classification rate of 95% in identifying seven types of marine creatures and marine litter. By introducing another degree of freedom in underwater haptic sensing, this work represents a milestone toward sustainable marine resource exploitation.

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

Since its outbreak in 2019, COVID-19 becomes a pandemic, severely burdening the public healthcare systems and causing an economic burden. Thus, societies around the world are prioritizing a return to normal. However, fighting the recession could rekindle the pandemic owing to the lightning-fast transmission rate of SARS-CoV-2. Furthermore, many of those who are infected remain asymptomatic for several days, leading to the increased possibility of unintended transmission of the virus. Thus, developing rigorous and universal testing technologies to continuously detect COVID-19 for entire populations remains a critical challenge that needs to be overcome. Wearable respiratory sensors can monitor biomechanical signals such as the abnormities in respiratory rate and cough frequency caused by COVID-19, as well as biochemical signals such as viral biomarkers from exhaled breaths. The point-of-care system enabled by advanced respiratory sensors is expected to promote better control of the pandemic by providing an accessible, continuous, widespread, noninvasive, and reliable solution for COVID-19 diagnosis, monitoring, and management.

Mass transfer is an essential factor determining photocatalytic performance, which can be modulated by fluid field via manipulating the kinetic characteristics of photocatalysts and photocatalytic intermediates. Past decades have witnessed the efforts and achievements made in manipulating mass transfer based on photocatalyst structure and composition design, and thus, a critical survey that scrutinizes the recent progress in this topic is urgently necessitated. This review examines the basic principles of how mass transfer behavior impacts photocatalytic activity accompanying with the discussion on theoretical simulation calculation including fluid flow speed and pattern. Meanwhile, newly emerged viable photocatalytic micro/nanomotors with self-thermophoresis, self-diffusiophoresis, and bubble-propulsion mechanisms as well as magnet-actuated photocatalytic artificial cilia for facilitating mass transfer will be covered. Furthermore, their applications in photocatalytic hydrogen evolution, carbon dioxide reduction, organic pollution degradation, bacteria disinfection and so forth are scrutinized. Finally, a brief summary and future outlook are presented, providing a viable guideline to those working in photocatalysis, mass transfer, and other related fields.

Polymer-ceramic piezoelectric composites, combining high piezoelectricity and mechanical flexibility, have attracted increasing interest in both academia and industry. However, their piezoelectric activity is largely limited by intrinsically low crystallinity and weak spontaneous polarization. Here, we propose a Ti3C2Tx MXene anchoring method to manipulate the intermolecular interactions within the all-trans conformation of a polymer matrix. Employing phase-field simulation and molecular dynamics calculations, we show that OH surface terminations on the Ti3C2Tx nanosheets offer hydrogen bonding with the fluoropolymer matrix, leading to dipole alignment and enhanced net spontaneous polarization of the polymer-ceramic composites. We then translated this interfacial bonding strategy into electrospinning to boost the piezoelectric response of samarium doped Pb (Mg1/3Nb2/3)O3-PbTiO3/polyvinylidene fluoride composite nanofibers by 160% via Ti3C2Tx nanosheets inclusion. With excellent piezoelectric and mechanical attributes, the as-electrospun piezoelectric nanofibers can be easily integrated into the conventional shoe insoles to form a foot sensor network for all-around gait patterns monitoring, walking habits identification and Metatarsalgi prognosis. This work utilizes the interfacial coupling mechanism of intermolecular anchoring as a strategy to develop high-performance piezoelectric composites for wearable electronics.

Virtual Reality (VR) technology has been widely used in researching situations that require high ecological validity but are difficult to copy. In this paper, we compare the effect of 360-degree videos in VR head-mounted display and 2D computer screen on evoking four types of emotional states, and innovatively assess the effect of emotion evoking using the Go/No-go attention paradigm. Based on the eye movement data collected from a considerable number of participants (N=48), the result reaches marginally significance in the effect of immersion level of evoking (p=0.075), emotion’s level of arousal (p=0.019), and the interaction between them (p=0.037) under the condition of positive evoking. We find that immersive device can better evoke positive emotions with high arousal, while non-immersive device cannot manipulate the intensity of evoked emotions. Our study empirically demonstrate that high-arousal positive emotion evoking is more effective in VR than on a 2D monitor based on computational affection.

Electronic textiles (e-textiles), having the capability of interacting with the human body and surroundings, are changing our everyday life in fundamental and meaningful ways. Yet, the expansion of the field of e-textiles is still limited by the lack of stable and biocompatible power sources with aesthetic designs. Here, we report a rechargeable solid-state Zn/MnO2 fiber battery with stable cyclic performance exceeding 500 hours while maintaining 98.0% capacity after more than 1000 charging/recharging cycles. The mechanism of the high electrical and mechanical performance due to the graphene oxide–embedded polyvinyl alcohol hydrogel electrolytes was rationalized by Monte Carlo simulation and finite element analysis. With a collection of key features including thin, light weight, economic, and biocompatible as well as high energy density, the Zn/MnO2 fiber battery could seamlessly be integrated into a multifunctional on-body e-textile, which provides a stable power unit for continuous and simultaneous heart rate, temperature, humidity, and altitude monitoring.

We discovered a giant magnetoelasticity in soft matter with up to 5-fold enhancement of magnetomechanical coupling factors compared to that of rigid metal alloys without an externally applied magnetic field. A wavy chain analytical model based on the magnetic dipole-dipole interaction and demagnetizing field was established, fitting well to the experimental observation. To explore its potentials in electronic textiles, we coupled it with magnetic induction to invent a textile magnetoelastic generator (MEG), a new working mechanism for biomechanical energy conversion, featuring an intrinsic waterproofness, an ultralow internal impedance of approximately 20 Ω, and a high short-circuit current density of 1.37 mA/cm2, which is about four orders of magnitude higher than that of other textile generator counterparts. Meanwhile, assisted by machine learning, the textile MEG could continuously monitor the respiratory activities on heavily perspiring skin without any encapsulation, allowing a timely diagnosis of the respiration abnormalities in a self-powered manner. We foresee that this discovery can be extended to wide-range soft-matter systems, emerging as a compelling approach to develop electronic textiles for energy, sensing, and therapeutic applications.

Magnetoelastic effect characterizes the change of materials' magnetic properties under mechanical deformation, which is conventionally observed in some rigid metals or metal alloys. Here we show magnetoelastic effect can also exist in 1D soft fibers with stronger magnetomechanical coupling than that in traditional rigid counterparts. This effect is explained by a wavy chain model based on the magnetic dipole-dipole interaction and demagnetizing factor. To facilitate practical applications, we further invented a textile magnetoelastic generator (MEG), weaving the 1D soft fibers with conductive yarns to couple the observed magnetoelastic effect with magnetic induction, which paves a new way for biomechanical-to-electrical energy conversion with short-circuit current density of 0.63 mA cm-2, internal impedance of 180 Ω, and intrinsic waterproofness. Textile MEG was demonstrated to convert the arterial pulse into electrical signals with a low detection limit of 0.05 kPa,  even with heavy perspiration or in underwater situations without encapsulations.

Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can convert subtle skin deformation caused by arterial pulsatility into electricity for high-fidelity and continuous pulse waveform monitoring in an ambulatory and sweaty setting is developed. The sensor holds a signal-to-noise ratio of 23.3 dB, a response time of 40 ms, and a sensitivity of 0.21 µA kPa-1 . With the assistance of machine learning algorithms, the textile triboelectric sensor can continuously and precisely measure systolic and diastolic pressure, and the accuracy is validated via a commercial blood pressure cuff at the hospital. Additionally, a customized cellphone application (APP) based on built-in algorithm is developed for one-click health data sharing and data-driven cardiovascular diagnosis. The textile triboelectric sensor enabled wireless biomonitoring system is expected to offer a practical paradigm for continuous and personalized cardiovascular system characterization in the era of the Internet of Things.

Taking the spherical sliding bearings with orifice throttling as the research object, the mathematical model of lubrication of spherical hybrid sliding bearings is established and the Reynolds equation under laminar flow state is deduced from this model. The pressure distribution of the oil chamber and oil edge are calculated according to the flow conservation principle of the orifice throttle. Combining with the finite difference method and relaxation iterative method to solve the disturbance pressure control equation which is derived by means of perturbation method. The stiffness coefficient and damping coefficient of spherical sliding bearings are used to study the influence of supply pressure, rotating speed, average oil film clearance and other parameters on the dynamic characteristics coefficient of the bearing through numerical analysis. The results show that as the oil film clearance decreases and the oil supply pressure increases, the stiffness coefficient and damping coefficient will increase accordingly. As the rotating speed increases, the changing trend of the direct stiffness is small while the decreasing trend of the direct damping is obvious. When the oil film clearance is 20 μm, the stiffness coefficient and damping coefficient of spherical hybrid sliding bearings reach the maximum. The increasing of rotating speed has little effect on the stiffness while the damping coefficient will be significantly reduced.

Reconfigurable chiral plasmonic complexes are fabricated by planar assembly of multiple individual gold nanorod dimers using DNA origami templates. Additionally, each chiral center can be controlled to switch among achiral, left-handed, and right-handed states. We demonstrate that their overall circular dichroism is determined by the coupling of individual chiral centers and is heavily influenced by the precise number and arrangement of these centers. Our study offers a novel self-assembly method for constructing intricate and dynamic chiral plasmonics as well as investigating the interactions among several plasmonic chiral centers. [ABSTRACT FROM AUTHOR]

Analyzing the influence of bearing parameters on the dynamic characteristics of spherical sliding bearings, which provided theoretical guidance for the operating stiffness, damping and stability of liquid spherical bearings. Taking spherical hybrid sliding bearings as the research object, established the mathematical model of lubrication analysis of spherical sliding bearings, the dynamic liquid lubrication equation under laminar flow was derived by the perturbation method, the partial differential equation of disturbance pressure was solved by the finite difference method, and the liquid was calculated numerically. The stiffness coefficient and damping coefficient of the spherical bearing were used to study the influence of the bearing speed, eccentricity, average oil film clearance and other parameters on the dynamic characteristic coefficient of the bearing through numerical analysis. The results show that the speed、 eccentricity and average oil film clearance have an important influence on the stiffness and damping of the oil film.

Due to study the influence of interfacial slip on the bearing capacity of hydrostatic and hydrostatic ball bearings with small orifice throttling, the Reynolds equation of ball bearings considering interfacial slip was established based on the linear slip model of interfacial slip. The Reynolds equation and the oil film thickness equation are solved by the finite difference method and the relaxation iterative method. The oil film pressure distribution and bearing capacity of the hydrostatic ball bearing considering interface slip are calculated. The results study that the higher the oil supply pressure, the higher the rotational speed, the smaller the oil film clearance, the stronger the dynamic pressure effect and the greater the bearing capacity of the hydrostatic bearing. Considering the sliding effect, the interface sliding leads to the increase of oil film pressure, and the influence on bearing capacity has a critical value. When the oil film gap is larger, the critical value of slip coefficient is larger, the liquid slip effect is stronger, and the carrying capacity increases when the slip degree is lower than the critical value, but decreases when the slip degree is higher than the critical value.