Enhanced photoelectric properties of PbSnSe thin films via quick oxygen ion-implantation sensitization

Journal of Materials Science - Although chalcogenide materials continue to generate considerable interest due to great potentials for various optoelectronic devices, annealing for a long time in...     

One step from nanofiber to functional hybrid structure: Pd doped ZnO/SnO2 heterojunction nanofibers with hexagonal ZnO columns for enhanced low-temperature hydrogen gas sensing

In this paper, a novel hybrid structure of Pd doped ZnO/SnO₂ heterojunction nanofibers with hexagonal ZnO columns was one step synthesized from electrospun precursor nanofibers. Due to the synergistic effect of hexagonal ZnO, SnO₂ and Pd, the structure exhibited excellent hydrogen (H₂) gas sensing properties. At low-temperature of 120 °C, the response (R_a/R_g) to 100 ppm H₂ gas exceeded 160, the response/recovery time was only 20 s and 6 s respectively and the limit of detection was only 0.5 ppm. Meanwhile, it also had good selectivity for H₂ gas and excellent linearity. In addition, the materials were characterized by XRD, FESEM, HRTEM, XPS, and the synthesis mechanism and gas sensing mechanism were proposed.     

Improving gelling properties of myofibrillar proteins incorporating with cellulose micro/nanofibres

The effects of cellulose microfibres (CMFs, Average size: 100 ± 5 μm) and cellulose nanofibres (CNFs, Average size: 60 ± 3 nm) on the properties of myofibrillar protein (MP) gels from duck breast meat were studied. The results demonstrated that CMFs and CNFs were mostly connected to MP by non-covalent bonds, the diffusion and cross-linking of MP molecules was promoted, and a denser and more complete gel network was formed. With the increases of CMFs and CNFs concentration (0–10%), the hardness was increased by 13.15% and 19.78% for CMFs10% and CNFs10% gels, respectively, and the elasticity was increased by 40% and 80%, respectively. At the same concentration (0–10%), the increase in gel hardness, viscoelasticity and immobilised water content was greater in the CNFs-MP group than in the CMFs-MP group. The CNFs-MP group had a tighter gel network, and CNFs had a better potential to improve the gelation performance of MP.     

传统牦牛酸奶源高产胞外多糖乳酸菌特性及发酵性能

为了研究四川藏区传统牦牛酸奶中高产胞外多糖乳酸菌特性及发酵性能，以本实验室分离出的六株高产胞外多糖乳酸菌为研究对象，以菌株生长量、耐酸性、胆盐耐受力、渗透压耐受力和细胞表面疏水性为指标进行特性研究；以发酵酸奶的凝乳时间、持水力、酸化及后酸化能力、挥发性物质及质构等为指标进行发酵性能研究。菌株的生长曲线表明，6株菌株分别在14 h（218、276、266）、16 h（271、285、231）进入对数生长稳定期，其中编号218的菌株生长量最高，OD值为2.188。耐受性实验结果表明，菌株276具有良好的耐酸能力（P<0.05）；菌株266、218、231耐胆盐的能力较强；6株菌株均具有较好的耐渗透压的能力，其中菌株285对高渗透压的耐受性较强；菌株285和218在两种有机试剂中的疏水性均显著（P<0.05）高于其他菌株，且与十六烷的结合效果较好。发酵试验结果表明，6株菌株所发酵酸奶均在6~8 h内凝固，酸乳在冷藏期间，活菌数均保持在107 CFU/mL以上，均符合发酵剂的标准，其中菌株276的最高为3.22×106 CFU/mL；菌株218发酵制得的酸奶质构特性较好，持水力和酸化能力较其余菌株均最强，分别为60.98%和83 °T；菌株276、266抗后酸化能力较好；菌株231产香性能最优，乙醛含量为24~26 μg/mL，双乙酰含量为1.58~3.73 μg/mL，能够明显改善酸奶的风味。通过综合比较6株高产胞外多糖乳酸菌特性及发酵性能，菌株218为一株性能良好、具有良好稳定性的菌株，可作为乳酸菌发酵剂且具有一定的应用潜力。研究为利用四川藏区传统牦牛酸奶中分离出的高产胞外多糖乳酸菌在发酵乳制品的应用提供理论依据。     

Influence of surfactants on rheological behaviors of polyacrylonitrile/dimethyl sulfoxide/silicon blending polymer solutions

KH550, KH560, CTAB, and F127 were adopted to modify silicon (Si) to improve the dispersity and stability of Si in the polyacrylonitrile/dimethyl sulfoxide (PAN/DMSO) polymer solutions. The influence of surfactants on rheological behaviors of PAN/DMSO/Si blending polymer solutions was investigated by an advanced solution and melt rotation rheometer. The homogeneity and stability were also studied. The results showed that the surfactants could change the viscosity dependence of blending polymer solutions on shear rate, temperature and storage time by increase the steric hindrance of Si. Among the four solutions, PAN/DMSO/Si blending polymer solution with F127 exhibited the lowest viscosity, activation energy and the smallest structural viscosity index and exhibited the trend close to the Newtonian fluids. Moreover, PAN/DMSO/Si blending polymer solution with F127 exhibited the best dispersity and stability, indicating its best physical properties and machinability.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Electrospun Zn-doped Ga2O3 nanofibers and their application in photodegrading rhodamine B dye

Ultrawide band gap semiconductor materials have attracted considerable attention in recent years owing to their great potential in the photocatalytic field. In this study, Zn-doped Ga₂O₃ nanofibers with various concentrations were synthesized via electrospinning; they exhibited a superior photocatalytic degradation performance of rhodamine B dye compared to that of undoped Ga₂O₃ nanofibers. The Zn dopant replaced Ga sites via replacement doping, which could increase the concentration of oxygen vacancies and lead to enhanced photocatalytic properties. When the Zn concentration increased, a Ga₂O₃/ZnGa₂O₄ hybrid structure formed, which could further enhance the photocatalytic performance. The separation of photogenerated carriers due to Zn doping and heterojunctions were the primary causes of the enhanced photocatalytic performance. This study provides experimental data for the fabrication of high-performance photocatalysts based on Ga₂O₃ nanomaterials.