In this work, a novel polarization-maintaining hollow-core fiber structure featuring a semi-circular nested dual-ring geometry is proposed. To simultaneously optimize two inherently conflicting performance metrics, namely, birefringence and confinement loss, a multi objective genetic algorithm is employed for geometric parameter tuning, resulting in a set of Pareto-optimal solutions. At the target wavelength of 1550 nm, the first optimal design achieves birefringence exceeding $1\times {10}^{-4}$ over a 1275 nm bandwidth while maintaining confinement loss around ${10}^0$ dB/m; the second design maintains birefringence above $1\times {10}^{-4}$ across a 1000 nm spectral range, with confinement loss on the order of ${10}^{-1}$ dB/m. These optimized designs offer a promising approach for improving the performance of polarization-sensitive applications such as interferometric sensing and high coherence laser systems. The results confirm the suitability of multi-objective genetic algorithms for integrated multi-objective fiber optimization and provide a new strategy for designing low-loss and high-birefringence fiber devices.

To address prevalent industrial challenges, including the high cost of fabricating microstructures via photolithography and 3D printing, impurity residues easily generated by conventional physical/chemical pore-forming techniques, and the limited sensitivity of regular capacitive sensors, this paper innovatively proposes an integrated low-temperature in situ gas foaming strategy using ammonium bicarbonate for the fabrication of porous TPU-based ionic gels. Relying on the complete gaseous decomposition property of ammonium bicarbonate upon heating, a three-dimensionally interconnected continuous porous network is spontaneously constructed inside the polymer matrix. Thermoplastic polyurethane (TPU) is selected as the continuous polymer phase, and [EMIM][TFSI] imidazolium ionic liquid is blended as the ion source to synthesize composite ionic gel substrates. A PDMS composite slurry filled with graphene is employed to prepare flexible substrates, followed by low-temperature oxygen plasma surface modification to introduce polar functional groups such as hydroxyl and carboxyl onto electrode surfaces. A standard sandwich-structured ionic pressure sensor with the configuration of “top modified electrode—porous ionic gel dielectric layer—bottom modified electrode” is finally assembled. The porous framework and modified electrodes constitute a dual synergistic enhancement system: the porous structure markedly reduces the equivalent elastic modulus of the gel and improves its compressive deformation capacity; polar-modified electrodes optimize the interfacial compatibility between electrodes and gels, shorten ion migration paths and lower interfacial contact resistance. Systematic calibration of multiple batches of parallel samples reveals that the as-fabricated sensor achieves a high sensitivity of 25.3 kPa⁻¹ across the full measuring range from 0 to 1000 kPa with a linear fitting coefficient R² = 0.992. The loading response time and unloading recovery time of the device are 60 ms and 80 ms respectively, with a performance degradation of less than 3% after 1000 consecutive loading–unloading cycles, featuring low hysteresis error and excellent signal repeatability. Multi-scenario in vivo wearable tests on human subjects verify that the device can precisely capture subtle fluctuations of radial artery pulse and periodic laryngeal deformation during swallowing, distinguish characteristic waveform patterns of various English words according to differences in vocal cord vibration, and accurately detect bending motions when attached to finger joints. The entire fabrication process adopts common chemical raw materials and standard laboratory equipment without expensive micro-nano processing facilities, featuring convenient raw material procurement and high process fault tolerance, which enables large-area coating-based mass production. This work delivers a novel technical route for the low-cost large-scale production of high-performance ionic flexible sensors and bears significant industrialization reference value for applications in wearable medical monitoring, bionic robotic electronic skin, flexible human–machine interactive touch panels and other related fields.

This work proposes a novel polarization-maintaining hollow-core anti-resonant fiber structure characterized by high birefringence and low transmission loss. To address the inherent trade-off between birefringence and confinement loss, a Pareto-front-based multi-objective optimization algorithm is introduced into the geometrical design of the ARF. The optimal fiber design achieves a birefringence exceeding $1\times {10}^{-4}$ and a confinement loss of approximately 1 dB/m at the telecommunication wavelength of 1.55 $\mathsf{\mu }$m. In particular, the asymmetric wall thickness configuration further improves the trade-off, enabling confinement loss as low as 0.15 dB/m while maintaining birefringence on the order of $1\times {10}^{-4}$. This approach significantly reduces computational cost and exhibits strong potential for applications in polarization-maintaining communications, precision sensing, and high-power laser delivery.

High-resolution three-dimensional temperature fields are essential for studying flame combustion, and tunable diode laser absorption tomography (TDLAT) is an effective method for diagnosing flame combustion conditions. In actual combustion measurements, the reliance of TDLAT on line-of-sight (LOS) measurements leads to limited data and reduced dimensionality in analyzing combustion fields. This study proposes a method using area-array sensor-coupled absorption spectroscopy to measure the three-dimensional temperature field of flame accurately, aiming for enhanced combustion diagnosis. The laser beam is configured into a cone shape, and after traversing the combustion field under examination, the area-array sensor receives a projection signal. This signal is then used to reconstruct a high-resolution, multidimensional temperature field. We confirmed the accuracy and robustness of the algorithm through numerical simulations and compared these with experimental results from the TDLAT setup. Our TDLAT detection system demonstrates high precision and effectively measures temperature fields in complex flame imaging scenarios.

The combustion temperature field is a key indicator of combustion stability, equipment integrity, and abnormal operating conditions. This study addresses short-horizon forecasting of laboratory-scale apparent infrared temperature fields using a Convolutional Long Short-Term Memory (ConvLSTM) network. A chronological 70/15/15 split is applied to 1800 available sequences, with the first 10 frames of each sample treated as observed inputs. Proper orthogonal decomposition (POD) is applied exclusively to the input frames at a 95% cumulative energy retention threshold, and predictions are evaluated on subsequent frames. POD is therefore used as an input-side low-rank modal preprocessing method to extract dominant coherent structures and suppress redundant variations, rather than as a reduction in the ConvLSTM network architecture itself. Performance is assessed via normalized domain PSNR/SSIM and Kelvin domain errors. The first three forecast steps maintain appreciable image similarity, while the fourth and fifth steps exhibit marked degradation. Therefore, conclusions are restricted to short-horizon forecasting, with no assertions regarding closed loop combustion control or cross-setup generalization. Simultaneously, ablation experiments with the same architecture, including and excluding the POD preprocessing step, quantified the individual contribution of the POD preprocessing step.

To improve dynamic thermal measurement accuracy on aero-engine hot-section components, integrated heat flux/temperature thin-film sensors (TFHFs) were fabricated using micro-nano technology. This study simulated and compared the time constant calibration of the TFHFs’ temperature component under step laser heating and step furnace heating, demonstrating the necessity of power feedback control in laser-based dynamic calibration. Factors influencing the dynamic response of the heat flux component under both radiation and convection were also analyzed. A laser-based test platform with constant-temperature feedback control was developed to validate the simulations. Tests revealed that overshoot in the heat flux response originates from non-ideal longitudinal heat transfer, while the feedback control reduced the temperature time constant by at least half (At the 1000 °C step steady state, the time constant decreased from 2 s to 0.85 s), overcoming the challenge of inaccurate calibration due to non-steady conditions. High-speed wind tunnel tests under convective conditions confirmed that the dynamic response of TFHFs is predominantly influenced by flow velocity. The study enables accurate dynamic measurement of composite thermal parameters under varied thermal boundaries.