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Lock-stitch embroidery has been the centre of much interest as a versatile and precise method of producing conductive tracks in the fabrication of wearable electronic devices. However, improper fabrication parameter settings could result in the nonconformity of the conductive tracks and damage the conductive coating of the conductive yarns. In this study, we evaluate the appearance quality, dimensional stability and electrical resistance of conductive tracks by taking into account the embroidering speed (ES), stitch length (SL), needle thread pre-tension (NTP) and embroidering direction (ED). The conductive tracks are embroidered onto knitted fabric in different directions with silver-coated polyamide yarn as the needle thread. The results show that stitching the conductive tracks in the wale direction results in a more uniform stitch lines in comparison to the other directions. To resolve the problem of floated stitches, it is recommended that an SL of 4 mm and a higher NTP are used. The percentage of shrinkage in the wale direction is lower than in the course direction. The electrical resistance of the conductive tracks increases with a higher ES and shorter SL. It is also found that a thicker yarn is more sensitive to the NTP and some of the silver coating is rubbed off with an NTP of 50 gf. We also carry out an overlay plot analysis, through which we predict and validate the optimal embroidery parameters that balance appearance quality and electrical resistance. The technique parameters in this study can be used to embroider conductive tracks for smart clothing.

Harvesting energy from the environment to generate electricity is attracting tremendous interest to enrich the forms of energy utilization, reduce greenhouse gas emissions and alleviate the global energy crisis1,2. However, achieving an unlimited and uninterrupted all-day power generation from the ambient energy is still challenging3. Herein, we demonstrate a passive power device to harvest energy from the sun and cold space based on micro-fabricated thermoelectric generator (TEG) integrated with solar absorber (SA) and radiative cooling emitter (RCE) to realize continuous power generation form the ambient. The ultrathin TEG, that with a sensitivity of 10− 4 K achieved output power density of 960 W/m3 while heated to 80°C at room temperature. The solar absorber (SA) performs photothermal conversion to heat the TEG in the daytime4, while the radiative cooling emitter (RCE) radiates the heat to the cold space through the atmospheric window to cool the TEG all the clear day5,6. Our strategy provides a renewable and sustainable thermodynamic resource to build a temperature difference over TEG for all-day uninterrupted power generation for wide application scenarios. This is the first proof-of-principle uninterrupted power generation system independent of time on a small scale, and opportunities exist for environmental energy harvesting and electricity generation beyond traditional technologies.

Wearable electronics have promising applications in human–machine interfaces and Internet of Things. Recent reported wearable sensing techniques are implemented mainly by either encapsulated packaging approaches or deposition of conductive nanomaterials onto flexible textiles. However, such fabrication technologies sacrifice the physical comfort, washability and wettability which are the essential elements to wearables. In this paper, we report a continuous twisted graphene fibre with high tensile strength (369 MPa) and remarkable breaking strain (48.5%), as well as stable electrical and mechanical performances under cyclic washing and chronic wetting. The as-prepared twisted graphene fibre is woven into a pure fabric-based breathable, wettable and washable strain sensor with outstanding sensitivity (gauge factor = 63) to strain while negligible sensitivity upon bend, pressure, temperature and humidity. The strain sensor displays undifferentiated high performance of sensitivity, stability and durability both in air and water, enabling its precise detection of human motions in complex external environment.

Reputation systems are typically used in markets with asymmetric information, but they can cause the cold-start problem for young sellers who lack historical sales. Exploiting a field experiment on a large e-commerce marketplace, we show that in the presence of a reputation-based quality certification, introducing a second certification tier that is less history-dependent and less demanding mitigates the cold-start problem: it increases demand for high-quality young sellers, incentivizes their quality provision, and increases their chance of eventually obtaining the top-tier certification. Moreover, it prompts established sellers to re-optimize their effort decision. Therefore, the net impact of introducing a less history-dependent signal on quality provision depends on underlying market fundamentals.

Multiple material additive manufacturing technology with the capability to integrate glass-ceramic and metallic materials is essential to the development of high-performance functional components for high temperature applications. Here we show the feasibility and characteristics of additively manufactured glass-ceramic/metal 3D electronic components via single-process multiple material laser powder bed fusion (MMLPBF). Copper (II) oxide (CuO) powder is mixed with α-spodumene (lithium aluminosilicate, Li2O·Al2O3·4SiO2) glass-ceramic powder to improve the laser absorbance, reduce the melting point of glass-ceramic to match that of copper and to improve bonding between copper and the glass-ceramic. Up to 92% relative density of the glass-ceramic is realized. The monoclinic crystal α-spodumene has been transformed to tetragonal crystal β-spodumene after laser melting. Sodium chloride (NaCl) and graphite mixed powder is printed as the substrate for the glass-ceramic component for its rapid removal. Embedded conductive copper wires and plates as the main conductive structures are successfully built within the glass-ceramic from powder feedstocks. The electrical resistivity of the printed copper structures is examined. An embedded multiple layer electric circuit, a capacitor and a temperature sensor are successfully printed and tested.

Wearable strain sensors have generated considerable recent research interest due to their huge potential in the real-time detection of human body deformation. State-of-the-art strain sensors are normally fabricated through conductive networks with a single sensing element, which always faces the challenge of either limited stretchability or inferior quality in sensitivity. In this work, we report a highly sensitive strain sensor based on a multi-functionalized fabric through carbonization and polymer-assisted copper deposition. The sensor shows high sensitivity (Gauge factor ∼ 3557.6 in the strain range from 0 to 48%), and outstanding stretchability up to the strain of 300%, which is capable of detecting different types of deformation of the human body. By integrating the high-performance sensor with a deep learning network, we demonstrate a high-accuracy respiration monitoring and emergency alarm system, showing the enormous application potential of the sensor in personal and public healthcare.

Among different fibrous e-textile sensors, humidity sensor has a particular significance in respiration monitoring, water presence alert, and skin contact/non-contact indication. These applications not only demand sensors to have fast response and recovery speed, robustness to attrition and friction, the sensors’ responses also need to be unimodal, i.e., only sensitive to humidity and insensitive to other impacts, such as temperature variation, folding and stretching of the fabric. Previously reported e-textile humidity sensors, when being used as a quick humidity indicator, suffered from slow response/recovery time, interference from multimodal sensitivities, or devices are non-fabric based and cannot be seamlessly integrated with apparels. In this paper, we have studied textile-based humidity sensors constructed from different natural and synthetic fibers (cotton, wool and Coolmax) and discovered that the graphene-oxide (GO) functionalized Coolmax humidity sensor (GO-Coolmax) exhibits ultrafast response/recovery time (less than 0.6 s). The senor is also insensitive to external pressure and temperature changes, i.e., the resistance variations caused by these impacts are within 10%, much smaller than that from humidity variations (above 80%). We have also demonstrated the use of the sensor as a humidity indicator/alert in various wearable applications through prototyping and experiments.

Pressure sensors are vital components of wearable electronics for human-machine interaction, health monitoring, disease prevention and so on. State-of-the-art pressure sensors often require the use of encapsulating materials such as polydimethylsiloxane (PDMS) to provide the mechanical durability, which significantly deteriorates the detection limit, permeability and wearing comfort of the pressure sensors. This paper reports a new type of encapsulation-free, low-detection-limit, and highly permeable pressure sensors, which are made with resilient graphited knitting hemp fabrics. The hemp sensors possess appealing properties including excellent permeability to air, water vapor, and moisture, low detection limit (0.3 Pa), wide working range (up to 500 kPa) outstanding cycling stability and durability. It provides a new route for achieving wearing comfortable and high-performance pressure sensors.

The mismatching patient flow distribution in the health care system in urban China is a great social issue that attracts lots of public attention. In this research, we propose a simulation-based optimisation method using the multi-fidelity optimisation with ordinal transformation (OT) and optimal sampling (OS) () algorithm to evaluate the patient flow distribution, so as to continuously improve the hierarchical health care service system. The low-fidelity model applying the queueing network theory is constructed for the OT part of the , followed by a high-fidelity but time-consuming discrete event simulation model for the OS part. An empirical study on the background of the hierarchical health care delivery system in China is presented, where the proposed method is implemented to optimise the system profit by guiding the patient flow distribution. A comparison with other widely used simulation optimisation methods sustains the efficacy of the with the evidence that acquiring effective information from the...

Transparent and conformal superhydrophobic coating with mechanochemical robustness is of great importance for various applications, such as waterproof, self-cleaning, and anti-icing for windows of cars and buildings. However, it remains a daunting challenge to endow the functional surface with programmable wettability. Herein, we propose a hierarchical coating consisting of polydimethylsiloxane (PDMS) nanoparticles (NPs) and PDMS microparticles (MPs) functional NPs through a combination of thermal treatment and spray treatment. The evaporation of PDMS under heat treatment is firstly applied to form a uniform nanoarchitectures, followed by spraying a mixed P25-PDMS dispersion to construct a protective coating with enhanced surface roughness. This resulted coating is conformal and possess reversible wettability on various substrates. In virtue of the light-response property of P25, the reversible wettability between superhydrophobicity and hydrophobicity can be achieved by repetitive UV-light irradiation and dark environment storage. Besides, the coating can maintain superhydrophobicity with high transmittance (76% optical transmittance) after immersion in acid/base solution for 24 h and continuously sand impingement. Furthermore, the coating exhibits mechanochemical robustness against high speed water jet and Elcometer 99 tape peeling test for 30 cycles due to the high adhesion between the robust coating and the glass. For practical application, the coating was demonstrated to have excellent performance in anti-icing, photocatalytic degradation of pollutants and self-cleaning.

Problem Definition: This paper studies the information-sharing strategy for a retail platform on which multiple competing sellers distribute their products. Academic/Practical Relevance: Due to the rapid growth of retail platforms in recent years, information sharing has become an increasingly important issue because retail platforms can gather enormous consumer information that may not be visible to the sellers. Understanding how to share such information with those sellers will provide useful implications from both the theoretical and practical perspectives. Methodology: We develop a game-theoretic model where multiple sellers compete on a retail platform by selling substitutable products and the platform charges a commission fee for each transaction. The platform owns superior demand information and can control the accuracy level when sharing the information with the sellers. There are two potential constraints on the platform's sharing strategy: privacy (the platform cannot share the information collected from one seller with other sellers) and fairness (the platform has to treat all sellers equally). Results: We find that the platform always has incentives to share the information, and such sharing benefits both the platform and all sellers. When there is no fairness constraint, the optimal strategy for the platform is to select a subgroup of sellers and truthfully share information with them. Under the fairness constraint, the platform must share the same information with all sellers and thus has an incentive to reduce the accuracy of the shared information. Moreover, we identify a simple pricing mechanism that can achieve the optimal information-sharing outcome. Finally, we show that when the sellers differ in their market power, the platform would prefer to share information truthfully with those sellers who have a lower impact on others. Managerial Implications: This research highlights the importance of understanding the impact of information sharing on a retail platform with competing sellers. It also provides a simple single-price mechanism to implement the optimal sharing strategy. These results could provide useful guidelines for platform managers to better design their information-sharing services.