Differential Mutation Incorporated Quantum Honey Badger Algorithm with Dynamic Opposite Learning and Laplace Crossover for Fuzzy Front-End Product Design.

In this paper, a multi-strategy fusion enhanced Honey Badger algorithm (EHBA) is proposed to address the problem of easy convergence to local optima and difficulty in achieving fast convergence in the Honey Badger algorithm (HBA). The adoption of a dynamic opposite learning strategy broadens the search area of the population, enhances global search ability, and improves population diversity. In the honey harvesting stage of the honey badger (development), differential mutation strategies are combined, selectively introducing local quantum search strategies that enhance local search capabilities and improve population optimization accuracy, or introducing dynamic Laplacian crossover operators that can improve convergence speed, while reducing the odds of the HBA sinking into local optima. Through comparative experiments with other algorithms on the CEC2017, CEC2020, and CEC2022 test sets, and three engineering examples, EHBA has been verified to have good solving performance. From the comparative analysis of convergence graphs, box plots, and algorithm performance tests, it can be seen that compared with the other eight algorithms, EHBA has better results, significantly improving its optimization ability and convergence speed, and has good application prospects in the field of optimization problems.

Laser-Patterned Hierarchical Aligned Micro-/Nanowire Network for Highly Sensitive Multidimensional Strain Sensor.

Flexible multidirectional strain sensors capable of simultaneously detecting strain amplitudes and directions have attracted tremendous interest. Herein, we propose a flexible multidirectional strain sensor based on a newly designed single-layer hierarchical aligned micro-/nanowire (HAMN) network. The HAMN network is efficiently fabricated using a one-step femtosecond laser patterning technology based on a modulated line-shaped beam. The anisotropic performance is attributed to the significantly different morphological changes caused by an inhomogeneous strain redistribution among the HAMN network. The fabricated strain sensor exhibits high sensitivity (gauge factor of 65 under 2.5% strain and 462 under larger strains), low response/recovery time (140 and 322 ms), and good stability (over 1000 cycles). Moreover, this single-layer strain sensor with high selectivity (gauge factor differences of ∼73 between orthogonal strains) is capable of distinguishing multidimensional strains and exhibits decoupled responses under low strains (<1%). Therefore, the strain sensors enable the precise monitoring of subtle movements, including radial pulses and wrist bending, and the rectification of pen-holding posture. Benefitting from these remarkable performances, the HAMN-based strain sensors show potential applications, including healthcare and complex human motion monitoring.

Self-Aligned Plasmonic Lithography for Maskless Fabrication of Large-Area Long-Range Ordered 2D Nanostructures.

This paper proposes a one-step maskless 2D nanopatterning approach named self-aligned plasmonic lithography (SPL) by line-shaped ultrafast laser ablation under atmospheric conditions for the first time. Through a theoretical calculation of electric field and experimental verification, we proved that homogeneous interference of laser-excited surface plasmon polaritons (SPPs) can be achieved and used to generate long-range ordered 2D nanostructures in a self-aligned way over a wafer-sized area within several minutes. Moreover, the self-aligned nanostructures can be freely transferred between embossed nanopillars and engraved nanoholes by modulating the excitation intensity of SPPs interference through altering the incident laser energy. The SPL technique exhibits further controllability in the shape, orientation, and period of achievable nanopatterns on a wide range of semiconductors and metals by tuning processing parameters. Nanopatterned films can further act as masks to transfer structures into other bulk materials, as demonstrated in silica.