Optimized wideband and compact multifunctional photonic device based on Sb2S3 phase change material.

In this paper, a 1 × 2 photonic switch is designed based on a silicon-on-insulator (SOI) platform combined with the phase change material (PCM), Sb2S3, assisted by the direct binary search (DBS) algorithm. The designed photonic switch exhibits an impressive operating bandwidth ranging from 1450 to 1650 nm. The device has an insertion loss (IL) from 0.44 dB to 0.70 dB (of less than 0.7 dB) and cross talk (CT) from -26 dB to -20 dB (of less than -20 dB) over an operating bandwidth of 200 nm, especially an IL of 0.52 dB and CT of -24 dB at 1550 nm. Notably, the device is highly compact, with footprints of merely 3 × 4 µm2. Furthermore, we have extended the device's functionality for multifunctional operation in the C-band that can serve as both a 1 × 2 photonic switch and a 3 dB photonic power splitter. In the photonic switch mode, the device demonstrates an IL of 0.7 dB and a CT of -13.5 dB. In addition, when operating as a 3 dB photonic power splitter, the IL is less than 0.5 dB.

Multifunctional emitter based on inverse design for infrared stealth, thermal imaging and radiative cooling.

In contrast to conventional emitters fashioned from traditional materials, tunable thermal emitters exhibit a distinct propensity to fulfill the demands of diverse scenarios, thereby engendering an array of prospects within the realms of communications, military applications, and control systems. In this paper, a tunable thermal emitter without continuous external excitation is introduced using Ge2Sb2Te5 (GST) and high-temperature-resistant material Mo. It is automatically optimized by inverse design with genetic algorithm (GA) to switch between different functions according to the object temperature to adapt to diverse scenarios. In "off" mode, the emitter orchestrates a blend of infrared (IR) stealth and thermal management. This is evidenced by average absorptivity values of 0.08 for mid-wave infrared (MIR, 3-5 µm), 0.19 for long-wave infrared (LIR, 8-14 µm), and 0.68 for the non-atmospheric window (NAW, 5-8 µm). Conversely, when confronted with high-temperature entities, the emitter seamlessly transitions to "on" mode, instigating a process of radiative cooling. This transformation is reflected in the augmented emissivity of the dual-band atmospheric window including MIR and LIR, attaining peak values of 0.96 and 0.97. This transition yields a cooling potential, quantified at 64 W/m2 at the ambient temperature of 25°C. In addition, our design employs a layered structure, which avoids complex patterned resonators and facilitates large-area fabrication. The emitter in this paper evinces robust insensitivity to polarization variations and the angle of incidence. We believe that this work will contribute to the development in the fields of dynamic tunability for IR stealth, dynamic radiative cooling systems, and thermal imaging.

Tensor completion algorithm-aided structural color design.

In recent years, structural color has developed rapidly due to its distinct advantages, such as low loss, high spatial resolution and environmental friendliness. Various inverse design methods have been extensively investigated to efficiently design optical structures. However, the optimization method for the inverse design of structural color remains a formidable challenge. Traditional optimization approaches, such as genetic algorithms require time-consuming repetitions of structural simulations. Deep learning-assisted design necessitates prior simulations and large amounts of data, making it less efficient for systems with a small number of features. This study proposes a tensor completion algorithm capable of swiftly and accurately predicting missing datasets based on partially obtained datasets to assist in structural color design. Transforming the complex physical problem of structural color design into a spatial structure relationship problem linking geometric parameters and spectral data. The method utilizes tensor multilinear data analysis to effectively capture the complex relationships associated with geometric parameters and spectral data in higher-order data. Numerical and experimental results demonstrate that the algorithm exhibits high reliability in terms of speed and accuracy for diverse structures, datasets of varying sizes, and different materials, significantly enhancing design efficiency. The proposed algorithm offers a viable solution for inverse design problems involving complex physical systems, thereby introducing a novel approach to the design of photonic devices. Additionally, numerical experiments illustrate that the structural color of cruciform resonators with diamond can overcome the high loss issues observed in traditional dielectric materials within the blue wavelength region and enhance the corrosion resistance of the structure. We achieve a wide color gamut and a high-narrow reflection spectrum nearing 1 by this structure, and the theoretical analysis further verifies that diamond holds great promise in the realm of optics.

Optical transparent metamaterial with multi-band compatible camouflage based on inverse design.

Infrared (IR) thermal camouflage and management are deeply desirable in the field of military and astronomy. While IR compatible with laser camouflage technology is extensively studied to counter modern detection systems, most existing strategies for visible light camouflage focus on color matching, which is not suitable for scenarios requiring transparency. In this work, we propose an optically transparent metamaterial with multi-band compatible camouflage capability based on the inverse design. The metamaterial consists of Ag grating, Si3N4 dielectric spacer layer, Ag reflection layer, and Si3N4 anti-reflective layer. An ideal multi-band compatible spectrum is involved in the inverse design algorithm. Calculated results demonstrate high transmittance (T0.38-0.78µm = 0.70) in the visible region, low reflectance (R1.55µm = 0.01) in laser working wavelength, high reflectance (R3-5µm = 0.86 and R8-14µm = 0.92) in the dual-band atmospheric window, and high emissivity (ɛ5-8µm = 0.61) for the non-atmospheric window. The radiative heat flux in the detected band is 31W/m2 and 201W/m2 respectively. Furthermore, the incident and polarized insensitivity of the proposed metamaterial supports applicability for practical situations. This work, emphasizes an effective strategy for conducting optically transparent design with compatible IR-laser camouflage as well as radiative cooling properties by an automated design approach.

Characterization of Fiber-Optic Vector Magnetic Field Sensors Based on the Magneto-Strictive Effect.

Fiber-optic magnetic field sensors have garnered considerable attention in the field of marine monitoring due to their compact size, robust anti-electromagnetic interference capabilities, corrosion resistance, high sensitivity, ease of multiplexing and integration, and potential for large-scale sensing networks. To enable the detection of marine magnetic field vector information, we propose an optical fiber vector magnetic field sensor that integrates three single-axis sensors in an orthogonal configuration. Theoretical analysis and experimental verification are conducted to investigate its magnetic field and temperature sensing characteristics, and a sensitivity matrix is established to address the cross-sensitivity between the magnetic field and temperature; experimental tests were conducted to assess the vector response of the three-dimensional (3D) vector sensor across the three orthogonal axes; the obtained experimental results illustrate the commendable magnetic field vector response exhibited by the sensor in the orthogonal axes, enabling precise demodulation of vector magnetic field information. This sensor presents several advantages, including cost-effectiveness, easy integration, and reliability vectorially. Consequently, it holds immense potential for critical applications in marine magnetic field network detection.

Plant growth-promoting rhizobacteria are important contributors to rice yield in karst soils.

The difficulty of releasing nutrients from soils in karst areas limits the yield of local crops and leads to poverty. In this study, two strains of plant growth-promoting rhizobacteria (PGPR) were isolated from the rhizosphere soil of typical plants in karst areas, which were both identified as Bacillus sp. and named GS1 and N1. And two isolates were used to construct a composite PGPR named MC1. These three strains of PGPR were used for soil inoculation in the pot experiment and field trial and their capacity to promote rice development was assessed. The results showed that MC1 inoculation exhibited notable rice growth-promoting ability in pot experiments, and, respectively, had an increment of 16.96, 18.74, and 11.50% in shoot biomass, total biomass, and rice height compared with control. This is largely attributed to PGPR's capacity to secrete phytohormones and soil enzymes, particularly urease (UE) in GS1, whose secreted UE content was significantly higher by 12.18% compared to the control. When applied to the field, MC1 inoculation not only increased rice yield by 8.52% and the available nutrient content in rice rhizosphere soil, such as available phosphorus (AP) and exchangeable magnesium (EMg); but also improved the abundance of beneficial rhizobacteria and the diversity of microbial communities in rice rhizosphere soil. Results in this study revealed that inoculated PGPR played a major role in promoting rice growth and development, and a new strategy for facilitating the growth of rice crops in agriculture was elucidated. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03593-0.

Sb2S3-Based Dynamically Tuned Color Filter Array via Genetic Algorithm.

Color displays have become increasingly attractive, with dielectric optical nanoantennas demonstrating especially promising applications due to the high refractive index of the material, enabling devices to support geometry-dependent Mie resonance in the visible band. Although many structural color designs based on dielectric nanoantennas employ the method of artificial positive adjustment, the design cycle is too lengthy and the approach is non-intelligent. The commonly used phase change material Ge2Sb2Te5 (GST) is characterized by high absorption and a small contrast to the real part of the refractive index in the visible light band, thereby restricting its application in this range. The Sb2S3 phase change material is endowed with a wide band gap of 1.7 to 2 eV, demonstrating two orders of magnitude lower propagation loss compared to GST, when integrated onto a silicon waveguide, and exhibiting a maximum refractive index contrast close to 1 at 614 nm. Thus, Sb2S3 is a more suitable phase change material than GST for tuning visible light. In this paper, genetic algorithms and finite-difference time-domain (FDTD) solutions are combined and introduced as Sb2S3 phase change material to design nanoantennas. Structural color is generated in the reflection mode through the Mie resonance inside the structure, and the properties of Sb2S3 in different phase states are utilized to achieve tunability. Compared to traditional methods, genetic algorithms are superior-optimization algorithms that require low computational effort and a high population performance. Furthermore, Sb2S3 material can be laser-induced to switch the transitions of the crystallized and amorphous states, achieving reversible color. The large chromatic aberration ∆E modulation of 64.8, 28.1, and 44.1 was, respectively, achieved by the Sb2S3 phase transition in this paper. Moreover, based on the sensitivity of the structure to the incident angle, it can also be used in fields such as angle-sensitive detectors.

Manganese accumulation in hair and teeth as a biomarker of manganese exposure and neurotoxicity in rats.

Manganese (Mn) is an essential trace element to humans. However, excessive Mn causes cognitive impairment resulting from injury to the central nervous system within the hippocampus. No ideal biomarker is currently available for evaluating Mn exposure and associated neurotoxicity in the body. Hence, this study used Mn levels in the serum (MnS), teeth (MnT), and hair (MnH) as biomarkers for evaluating the association between Mn exposure and cognitive impairment in Mn-treated rats. A total of 32 male Sprague-Dawley rats were randomly divided into four groups, received 0, 5, 10, and 20 mg/(kg day) of MnCl2·4H2O for 5 days a week for 18 weeks, respectively. Lifetime Mn cumulative dose (LMCD) was used to evaluate external Mn exposure. Hippocampus, serum, teeth, and hair specimens were collected from the rats for Mn determination by graphite furnace atomic absorption spectrometry. Learning and memory functions were assessed using the Morris water maze test. Results showed that chronic Mn exposure increased the hippocampus (MnHip), MnS, MnT, and MnH levels, as well as impaired learning and memory function in rats. MnHip, MnT, and MnH levels were positively correlated with LMCD (r = 0.759, r = 0.925, and r = 0.908, respectively; p < 0.05), escape latency (r = 0.862, r = 0.716, and r = 0.814, respectively; p < 0.05), and the number of platform crossings (r = -0.734, r = -0.514, and r = -0.566, respectively; p < 0.05). No association was observed between MnS levels and the number of platform crossings (r = -0.286, p > 0.05). Thus, MnT and MnH detected long-term low-dose Mn exposure. These parameters can be reliable biomarkers for Mn exposure and associated neurotoxicity in Mn-treated rats.

Effects of chronic manganese exposure on the learning and memory of rats by observing the changes in the hippocampal cAMP signaling pathway.

Chronic manganese exposure can produce cognitive deficits; however, the underlying mechanism remains unclear; reliable peripheral biomarker of Mn neurotoxicity have not yet been fully developed. Hence, this study aimed to investigate the mechanism of Mn-induced cognitive deficits and the potential biomarker of Mn neurotoxicity in rats. Thirty-two male Sprague Dawley rats were divided into four groups; these groups received intraperitoneal injections of 0, 5, 10 and 20 mg Mn/kg once daily, five days/week for 18 weeks. Learning and memory were assessed via Morris water maze test. Hippocampal and plasma Mn concentrations were measured through graphite furnace atomic absorption spectrometry. The levels of plasma BDNF, hippocampal BDNF, cAMP, protein kinase A, and pCREB were assessed through ELISA or Western blot. Results showed that the Mn concentrations in the hippocampus and plasma of the Mn-treated rats were higher than those of the control rats. Mn exposure impaired the learning and memory of rats. Plasma BDNF levels and hippocampal BDNF, cAMP, protein kinase A, and pCREB levels were significantly lower in the Mn-treated rats than in the control rats. Plasma BDNF levels were negatively correlated with the escape latency and the hippocampal and plasma Mn concentrations. By contrast, plasma BDNF levels were positively correlated with the number of platform crossings and the hippocampal cAMP and BDNF levels. Therefore, Mn impaired learning and memory probably by inhibiting the hippocampal cAMP signaling pathway in rats. Plasma BDNF levels may also be a potential effect biomarker of Mn neurotoxicity.