Inspired by the epidermal–dermal and outer microstructures of the human fingerprint, a novel flexible sensor device is designed to improve haptic perception and surface texture recognition, which is ...consisted of single‐walled carbon nanotubes, polyethylene, and polydimethylsiloxane with interlocked and outer micropyramid arrays. The sensor shows high pressure sensitivity (−3.26 kPa−1 in the pressure range of 0−300 Pa), and it can detect the shear force changes induced by the dynamic interaction between the outer micropyramid structure on the sensor and the tested material surface, and the minimum dimension of the microstripe that can be discerned is as low as 15 µm × 15 µm (interval × width). To demonstrate the texture discrimination capability, the sensors are tested for accurately discerning various surface textures, such as the textures of different fabrics, Braille characters, the inverted pyramid patterns, which will have great potential in robot skins and haptic perception, etc.
Fingerprint‐inspired flexible tactile sensor shows high pressure sensitivity (−3.26 kPa−1), and the minimum dimension of the microstripe that can be discerned is as low as 15 µm × 15 µm. The tactile sensor can accurately discern various surface textures, such as different fabrics, Braille characters, and the inverted pyramid patterns, which will have great potential in robot skins and haptic perception.
Designing electronic skin (e-skin) with proteins is a critical way to endow e-skin with biocompatibility, but engineering protein structures to achieve controllable mechanical properties and ...self-healing ability remains a challenge. Here, we develop a hybrid gluten network through the incorporation of a eutectic gallium indium alloy (EGaIn) to design a self-healable e-skin with improved mechanical properties. The intrinsic reversible disulfide bond/sulfhydryl group reconfiguration of gluten networks is explored as a driving force to introduce EGaIn as a chemical cross-linker, thus inducing secondary structure rearrangement of gluten to form additional β-sheets as physical cross-linkers. Remarkably, the obtained gluten-based material is self-healing, achieves synthetic material-like stretchability (>1600%) and possesses the ability to promote skin cell proliferation. The final e-skin is biocompatible and biodegradable and can sense strain changes from human motions of different scales. The protein network microregulation method paves the way for future skin-like protein-based e-skin.
Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and quantum chemistry communities over the past century. Although many ...approximation methods have been introduced, the complexity of quantum mechanics remains hard to appease. The advent of quantum computation brings new pathways to navigate this challenging and complex landscape. By manipulating quantum states of matter and taking advantage of their unique features such as superposition and entanglement, quantum computers promise to efficiently deliver accurate results for many important problems in quantum chemistry, such as the electronic structure of molecules. In the past two decades, significant advances have been made in developing algorithms and physical hardware for quantum computing, heralding a revolution in simulation of quantum systems. This Review provides an overview of the algorithms and results that are relevant for quantum chemistry. The intended audience is both quantum chemists who seek to learn more about quantum computing and quantum computing researchers who would like to explore applications in quantum chemistry.
The Poisson equation occurs in many areas of science and engineering. Here we focus on its numerical solution for an equation in d dimensions. In particular we present a quantum algorithm and a ...scalable quantum circuit design which approximates the solution of the Poisson equation on a grid with error . We assume we are given a superposition of function evaluations of the right-hand side of the Poisson equation. The algorithm produces a quantum state encoding the solution. The number of quantum operations and the number of qubits used by the circuit is almost linear in d and polylog in −1. We present quantum circuit modules together with performance guarantees which can also be used for other problems.
The number of measurements demanded by hybrid quantum-classical algorithms such as the variational quantum eigensolver (VQE) is prohibitively high for many problems of practical value. For such ...problems, realizing quantum advantage will require methods that dramatically reduce this cost. Previous quantum algorithms that reduce the measurement cost (e.g., quantum amplitude and phase estimation) require error rates that are too low for near-term implementation. Here we propose methods that take advantage of the available quantum coherence to maximally enhance the power of sampling on noisy quantum devices, reducing the measurement number and runtime compared to the standard sampling method of the VQE. Our scheme derives inspiration from quantum metrology, phase estimation, and the more recent “alpha-VQE” proposal, arriving at a general formulation that is robust to error and does not require ancilla qubits. The central object of this method is what we call the “engineered likelihood function” (ELF), used for carrying out Bayesian inference. We show how the ELF formalism enhances the rate of information gain in sampling as the physical hardware transitions from the regime of noisy intermediate-scale quantum computers to that of quantum error–corrected ones. This technique speeds up a central component of many quantum algorithms, with applications including chemistry, materials, finance, and beyond. Similar to the VQE, we expect small-scale implementations to be realizable on today’s quantum devices.
As chemical sensors are in great demand for portable and wearable analytical applications, it is highly desirable to develop an all-solid-state ion-selective electrode (ISE) and reference electrode ...(RE) platform with simplicity and stability. Here we propose a wearable sensor platform with a new type of all-solid-state ISE based on a gold nanodendrite (AuND) array electrode as the solid contact and a poly(vinyl acetate)/inorganic salt (PVA/KCl) membrane-coated all-solid-state RE. A simple and controllable method was developed to fabricate the AuNDs on a microwell array patterned chip by one-step electrodeposition without additional processing. For the first time, the AuND electrodes with different real surface area and double layer capacitance were developed as solid contact of the Na+-ISE to investigate the relationship between performance of the ISE and surface area. As-prepared AuND-ISE with larger surface area (∼7.23 cm2) exhibited enhanced potential stability compared to those with smaller surface area (∼1.85 cm2) and to bare Au ISE. Important as the ISE, the PVA/KCl membrane-coated Ag/AgCl RE exhibited highly stable potential even after 3 months’ storage. Finally, a wearable sweatband sensor platform was developed for efficient sweat collection and real-time analysis of sweat sodium during indoor exercise. This all-solid-state ISE and RE integrated sensor platform provided a very simple and reliable way to construct diverse portable and wearable devices for healthcare, sports, clinical diagnosis, and environmental analysis applications.
Abstract
Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cases. Here ...we focus on a particular one of such use cases, credit valuation adjustment (CVA), and identify opportunities and challenges towards quantum advantage for practical instances. To build a NISQ-friendly quantum circuit able to solve such problem, we draw on various heuristics that indicate the potential for significant improvement over well-known techniques such as reversible logical circuit synthesis. In minimizing the resource requirements for amplitude amplification while maximizing the speedup gained from the quantum coherence of a noisy device, we adopt a recently developed Bayesian variant of quantum amplitude estimation using engineered likelihood functions. We perform numerical analyses to characterize the prospect of quantum speedup in concrete CVA instances over classical Monte Carlo simulations.
Transition-metal alloys have attracted a great deal of attention as an alternative to Pt-based catalysts for hydrogen evolution reaction (HER) in alkaline. Herein, a facile and convenient strategy to ...fabricate Co3Mo binary alloy nanoparticles nesting onto molybdenum oxide nanosheet arrays on nickel foam is developed. By modulating the annealing time and temperature, the Co3Mo alloy catalyst displays a superior HER performance. Owing to substantial active sites of nanoparticles on nanosheets as well as the intrinsic HER activity of Co3Mo alloy and no use of binders, the obtained catalyst requires an extremely low overpotential of only 68 mV at 10 mA cm–2 in alkaline, with a corresponding Tafel slope of 61 mV dec–1. At the same time, the catalyst demonstrates excellent stability during the long-term measurements. The density functional theory calculation provides a deeper insight into the HER mechanism, unveiling that the active sites on the Co3Mo-based catalyst are Mo atoms. This strategy of combining catalytic active species with hierarchical nanoscale materials can be extended to other applications and provides a candidate of nonnoble metal catalysts for practical electrochemical water splitting.
Machine health management is one of the main research contents of PHM technology, which aims to monitor the health states of machines online and evaluate degradation stages through real-time sensor ...data. In recent years, classic sparsity measures such as kurtosis, Lp/Lq norm, pq-mean, smoothness index, negative entropy, and Gini index have been widely used to characterize the impulsivity of repetitive transients. Since smoothness index and negative entropy were proposed, the sparse properties have not been fully analyzed. The first contribution of this paper is to analyze six properties of smoothness index and negative entropy. In addition, this paper conducts a thorough investigation on multivariate power average function and finds that existing classical sparsity measures can be respectively reformulated as the ratio of multivariate power mean functions (MPMFs). Finally, a general paradigm of index design is proposed for the expansion of sparsity measures family, and several newly designed dimensionless health indexes are given as examples. Two different run-to-failure bearing datasets were used to analyze and validate the capabilities and advantages of the newly designed health indexes. Experimental results prove that the newly designed health indexes show good performance in terms of monotonic degradation description, first fault occurrence time determination and degradation state assessment.
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