Life cycle cost of conventional,battery electric,and fuel cell electric vehicles considering traffic and environmental policies in China

Electric vehicles (EVs) are considered a promising alternative to conventional vehicles (CVs) to alleviate the oil crisis and reduce urban air pollution and carbon emissions. Consumers usually focus on the tangible cost when choosing an EV or CV but overlook the time cost for restricting purchase or driving and the environmental cost from gas emissions, falling to have a comprehensive understanding of the economic competitiveness of CVs and EVs. In this study, a life cycle cost model for vehicles is conducted to express traffic and environmental policies in monetary terms, which are called intangible cost and external cost, respectively. Battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), and CVs are compared in four first-tier, four new first-tier, and 4 s-tier and below cities in China. The comparison shows that BEVs and FCEVs in most cities are incomparable with CVs in terms of tangible cost. However, the prominent traffic and environmental policies in first-tier cities, especially in Beijing and Shanghai, greatly increase the intangible and external costs of CVs, making consumers more inclined to purchase BEVs and FCEVs. The main policy benefits of BEVs and FCEVs come from three aspects: government subsidies, purchase and driving restrictions, and environmental taxes. With the predictable reduction in government subsidies, traffic and environmental policies present important factors influencing the competitiveness of BEVs and FCEVs. In first-tier cities, BEVs and FCEVs already have a competitive foundation for large-scale promotion. In new first-tier and second-tier and below cities, stricter traffic and environmental policies need to be formulated to offset the negative impact of the reduction in government subsidies on the competitiveness of BEVs and FCEVs. Additionally, a sensitivity analysis reveals that increasing the mileage and reducing fuel prices can significantly improve the competitiveness of BEVs and FCEVs, respectively.     

Efficient Visible-to-UV Photon Upconversion Systems Based on CdS Nanocrystals Modified with Triplet Energy Mediators

Developing high-performance visible-to-UV photon upconversion systems based on triplet–triplet annihilation photon upconversion (TTA-UC) is highly desired, as it provides a potential approach for UV light-induced photosynthesis and photocatalysis. However, the quantum yield and spectral range of visible-to-UV TTA-UC based on nanocrystals (NCs) are still far from satisfactory. Here, three different sized CdS NCs are systematically investigated with triplet energy transfer to four mediators and four annihilators, thus substantially expanding the available materials for visible-to-UV TTA-UC. By improving the quality of CdS NCs, introducing the mediator via a direct mixing fashion, and matching the energy levels, a high TTA-UC quantum yield of 10.4% (out of a 50% maximum) is achieved in one case, which represents a record performance in TTA-UC based on NCs without doping. In another case, TTA-UC photons approaching 4 eV are observed, which is on par with the highest energies observed in optimized organic systems. Importantly, the in-depth investigation reveals that the direct mixing approach to introduce the mediator is a key factor that leads to close to unity efficiencies of triplet energy transfer, which ultimately governs the performance of NC-based TTA-UC systems. These findings provide guidelines for the design of high-performance TTA-UC systems toward solar energy harvesting.     

A Smart Hyperthermia Nanofiber-Platform-Enabled Sustained Release of Doxorubicin and 17AAG for Synergistic Cancer Therapy

This study demonstrates the rational fabrication of a magnetic composite nanofiber mesh that can achieve mutual synergy of hyperthermia, chemotherapy, and thermo-molecularly targeted therapy for highly potent therapeutic effects. The nanofiber is composed of biodegradable poly(ε-caprolactone) with doxorubicin, magnetic nanoparticles, and 17-allylamino-17-demethoxygeldanamycin. The nanofiber exhibits distinct hyperthermia, owing to the presence of magnetic nanoparticles upon exposure of the mesh to an alternating magnetic field, which causes heat-induced cell killing as well as enhanced chemotherapeutic efficiency of doxorubicin. The effectiveness of hyperthermia is further enhanced through the inhibition of heat shock protein activity after hyperthermia by releasing the inhibitor 17-allylamino-17-demethoxygeldanamycin. These findings represent a smart nanofiber system for potent cancer therapy and may provide a new approach for the development of localized medication delivery.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

原子吸收光谱法测定保护渣中锰含量

采用原子吸收光谱法测定保护渣中锰含量,进行了酸度对测定的影响、试样分解、共存离子干扰、加标回收、精密度分析等试验。结果表明,锰可完全溶解于混合酸溶液中;加入氯化锶,可以消除钠、钙对锰测定的干扰;锰质量浓度在0~12.0μg/mL的范围,工作曲线线性关系良好;加标回收率较高,在97%~102%;测定结果准确度较高,与高碘酸钠光度法分析结果一致性较好。     

发挥设备专业化优势探索项目建设设备综合管理标准化工作

设备综合管理工作始终贯穿在项目建设整个过程中.从项目立项审查、基础设计审查、设备订货前的技术把关,到工程施工环节的专业技术检查,再到项目中交、联动试车、投料试车,处处可见设备综合管理的内容.本文梳理出设备综合管理的主要节点内容、现状和存在的问题,针对镇海基地项目群的建设,就如何发挥设备专业化的优势、如何对设备综合管理工作进行创新、如何优化工作流程进行了探索.旨在通过设备综合管理工作的统筹和协调,将专业化优势形成合力,更高质量、更高效率地为项目建设服务.     

Structural,optical and electrical properties of indium doped Cu2ZnSn(S,Se)4 thin films synthesized by the DC and RF reactive magnetron cosputtering

Element doping into the Cu₂ZnSn(S,Se)₄ (CZTSSe) absorber is an effective method to optimize the performance of thin film solar cells. In this study, the Cu₂In_xZn_1-xSn(S,Se)₄ (CIZTSSe) precursor film was deposited by magnetron cosputtering technique using indium (In) and quaternary Cu₂ZnSnS₄ (CZTS) as targets. Meanwhile, the In content was controlled using the direct current (DC) power on In target (P_In). A single kesterite CIZTSSe alloy was formed by successfully doping a small number of In³⁺ into the main lattice of CZTSSe. The partial Zn²⁺ cations were substituted by In³⁺ ions, resulting in improving properties of CZTSSe films. Morphological analysis showed that large grain CIZTSSe films could be obtained by doping In. The well-distributed, smooth, and dense film was obtained when the P_In was 30 W. The band gap of CIZTSSe could be continuously adjusted from 1.27 to 1.05 eV as P_In increased from 0 to 40 W. In addition, the CIZTSSe alloy thin film at P_In = 30 W exhibited the best p-type conductivity with Hall mobility of 6.87 cm²V^?1s^?1, which is a potential material as the absorption layer of high-performance solar cells.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.