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Defect engineering is the core strategy for improving thermoelectric properties. Herein, cation doping along with modulation of cation vacancy has been developed in GeTebased materials as an effective method to induce vacancy-based defects to boost their thermoelectric performance. A series of ternary compounds of Ge 9 Sb 2 Te 12−x (x = 0, 0.03, 0.06, 0.09, 0.12, 0.15) was prepared by vacuum-melting and annealing combined with the spark plasma sintering (SPS) process. The role of Sb doping and cation vacancy on thermoelectric properties was systematically investigated. It is found that alloying Sb 2 Te 3 into GeTe increases the concentration of cation vacancies, which is corroborated by both positron annihilation measurements and theoretical calculations. The vacancies, stacking faults, and planar defect interactions determine the thermoelectric transport properties. Adjusting the deficiency of Te effectively tunes the concentration of cation vacancies and dopant defects in the structure. In turn, this tunes the carrier concentration close to its optimum. A high power factor of 32.6 μW cm −1 K −2 is realized for Ge 9 Sb 2 Te 11.91 at 725 K. Moreover, large strains induced by the defect structures, including Sb dopant, vacancy, staking faults, as well as planar defects intensify phonon scattering, leading to a significant decrease in the thermal conductivity from 7.6 W m −1 K −1 for pristine GeTe to 1.18 W m −1 K −1 for Ge 9 Sb 2 Te 11.85 at room temperature. All of the above contribute to a high ZT value of 2.1 achieved for the Ge 9 Sb 2 Te 11.91 sample at 775 K.

The discovery of discriminating molecular biomarkers often couples omics for data acquisition with advanced information processing methods for data analysis. Here, we move information processing upstream for data acquisition and report that a sample's "chemical space" can be actively probed using a tailored sequence of redox-based input signals. Specifically, we use a redox-active iridium salt (KIrCl) and an oxidative pulse-redox-relaxation input sequence to probe serum samples for chemical information. Optical and electrical output responses are collected simultaneously and analyzed using signal metrics that are sensitive to component and concentration dependent chemical information. We use the example of schizophrenia to illustrate the potential of this signal processing approach to rapidly discover discriminating signatures using simple and inexpensive instrumentation. These studies indicate that redox-probing provides an orthogonal measurement approach to accelerate biomarker discovery and further suggest a simple means to supply chemical information for the internet-of-things in medical and consumer applications.

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The development of sensors with high sensitivity, good flexibility, low cost, and capability of detecting multiple inputs is of great significance for wearable electronics. Herein, we report a napkin-based wearable capacitive sensor fabricated by a novel, low-cost, and facile strategy. The capacitive sensor is composed of two pieces of electrode plates manufactured by spontaneous assembly of silver nanowires (NWs) on a polydimethylsiloxane (PDMS)-patterned napkin. The sensor possesses high sensitivity (>7.492 kPa−1), low cost, and capability for simultaneous detection of multiple signals. We demonstrate that the capacitive sensor can be applied to identify a variety of human physiological signals, including finger motions, eye blinking, and minute wrist pulse. More interestingly, the capacitive sensor comfortably attached to the temple can simultaneously monitor eye blinking and blood pulse. The demonstrated sensor shows great prospects in the applications of human–machine interface, prosthetics, home-based healthcare, and flexible touch panels.

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Since there are nonlinearities in an electro-hydraulic servo shaking table, when the shaking table corresponds to sinusoidal shaking tests, its response contains higher harmonics, resulting in harmonic distortion and deteriorating the control performance. It needs to provide harmonic information for harmonic cancellation. The purpose of the paper is to develop an online acceleration harmonic identification algorithm for the shaking table. The unscented Kalman filter is applied to achieve this task. A nonlinear state space of the sinusoidal acceleration response is built for the unscented Kalman filter, which estimates the state of the nonlinear model, and the amplitude and phase of each harmonic, including the fundamental, can be directly decomposed from the identified state vector. The state transition equation is linear and the measurement equation is nonlinear. The efficiency and real-time performance of the developed acceleration harmonic identification are validated by simulation and experiment, in which the estimation error is further used to testify the estimation accuracy.

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