Bond graph modeling,design and experimental validation of a photovoltaic/fuel cell/ electrolyzer/battery hybrid power system

This work presents a complete bond graph modeling of a hybrid photovoltaic-fuel cell-electrolyzer-battery system. These are multi-physics models that will take into account the influence of temperature on the electrochemical parameters. A bond graph modeling of the electrical dynamics of each source will be introduced. The bond graph models were developed to highlight the multi-physics aspect describing the interaction between hydraulic, thermal, electrochemical, thermodynamic, and electrical fields. This will involve using the most generic modeling approach possible for managing the energy flows of the system while taking into account the viability of the system. Another point treated in this work is to propose. In this work, a new strategy for the power flow management of the studied system has been proposed. This strategy aims to improve the overall efficiency of the studied system by optimizing the decisions made when starting and stopping the fuel cell and the electrolyzer. It was verified that the simulation results of the proposed system, when compared to simulation results presented in the literature, that the hydrogen demand is increased by an average of 8%. The developed management algorithm allows reducing the fuel cell degradation by 87% and the electrolyzer degradation by 65%. As for the operating time of the electrolyzer, an increment of 65% was achieved, thus improving the quality of the produced hydrogen. The Fuel Cell's running time has been decreased by 59%. With the ambition to validate the models proposed and the associated commands, the development of this study gave rise to the creation of an experimental platform. Using this high-performance experimental platform, experimental tests were carried out and the results obtained are compared with those obtained by simulation under the same metrological conditions.     

Quantifying the limits of CAR T-cell delivery in mice and men

CAR (Chimeric Antigen Receptor) T cells have demonstrated clinical success for the treatment of multiple lymphomas and leukaemias, but not for various solid tumours, despite promising data from murine models. Lower effective CAR T-cell delivery rates to human solid tumours compared to haematological malignancies in humans and solid tumours in mice might partially explain these divergent outcomes. We used anatomical and physiological data for human and rodent circulatory systems to calculate the typical perfusion of healthy and tumour tissues, and estimated the upper limits of immune cell delivery rates across different organs, tumour types and species. Estimated maximum delivery rates were up to 10 000-fold greater in mice than humans yet reported CAR T-cell doses are typically only 10–100-fold lower in mice, suggesting that the effective delivery rates of CAR T cells into tumours in clinical trials are far lower than in corresponding mouse models. Estimated delivery rates were found to be consistent with published positron emission tomography data. Results suggest that higher effective human doses may be needed to drive efficacy comparable to mouse solid tumour models, and that lower doses should be tested in mice. We posit that quantitation of species and organ-specific delivery and homing of engineered T cells will be key to unlocking their potential for solid tumours.     

High-efficiency Silicon Solar Cells: A Review

Over the past few decades, crystalline silicon solar cells have been extensively studied due to their high efficiency, high reliability, and low cost. In addition, these types of cells lead the industry and account for more than half of the market. For the foreseeable future, Si will still be a critical material for photovoltaic devices in the solar cell industry. In this paper, we discuss key issues, cell concepts, and the status of recent high-efficiency crystalline silicon solar cells.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Single chamber Solid Oxide Fuel Cells selective electrodes: A real chance with brownmillerite-based nanocomposites

In this contribution brownmillerite-based nanocomposite cathode for Single-Chamber Solid Oxide Fuel Cells is developed. These cells can be very attractive especially for small and cheap devices because of the absence of seals. The efficiency of SC-SOFCs is strictly connected to the selectivity of anode and cathode, the bottleneck for this technology. The development of a cathode inert in fuel oxidation is particularly challenging. Our strategy is to start from a catalytically un-active support (CFA = Ca₂FeAl_0.95Mg_0.05O₅) and induce the formation of iron oxide based nanoparticles, expected to activate oxygen. Symmetric (CFA + FeO_x/CGO/CFA + FeO_x) and complete cells (CFA + FeO_x/CGO/Ni-CGO) are studied in air and methane/oxygen 2:1 mixture. The Area Specific Resistance of CFA + FeO_x is less than 1/3 that of CFA. The high selectivity allows to reach an efficiency of 25%; power still needs to be increased but we demonstrated the possibility to develop selective low cost electrodes. The effect of air, methane/oxygen exposure and the heat treatments were carefully investigated.     

CO2激光治疗皮肤基底细胞癌14例临床观察

目的 :探求一种简单 ,安全 ,效果好的基底细胞癌的治疗方法。方法 :对 1 4例基底细胞癌患者在局麻下用CO2 激光行基底细胞癌切除术或切除 +气化术。结果 :患者术中、术后出血少 ,伤口恢复快 ,愈合良好 ,疤痕表浅 ,随访未见复发。结论 :CO2 激光用于治疗基底细胞癌效果良好 ,无明显副作用 ,操作简单值得推广。     

柴油蜡晶的理论形态预测与显微实际形态的比较

采用BFDH模型和AE模型预测柴油中蜡晶的理论形态，与通过相衬光学显微镜在冷环境平台上观察柴油蜡晶在低温下析出的实际形态。以及加入低温流动性改进剂T1804的柴油蜡晶形态进行比较研究。以十八烷晶体和二十三烷晶体作为柴油蜡晶中偶数正构烷烃和奇数正构烷烃的模型化合物，得到它们的晶体理论形态为六面体薄片状晶体。不同降温速率下得到的蜡晶的实际形态与大小均不同。快速降温条件下得到的晶体形态主要为六边形、菱形和其它少数不规则多边形薄片状集合体；慢速降温条件下得到的柴油蜡晶的形态比较完整，为六边形片状，与通过BFDH和AE模型得到的十八烷即偶数正构烷烃的形态比较接近。柴油加T1804后，快速降温时，出现更多细小的无规则晶体，且很快聚集成片状晶体；慢速降温时，出现晶体的数目要多于未加剂柴油，形状不规则，且尺寸小于未加剂柴油。     

基于形态学top-hat算子的多传感器图像融合

本文根据形态学top-hat算子能够提取图像中极大值与极小值区域的特点,将其应用于多传感器图像融合的两个重要领域——多聚焦图像融合和高分辨、多光谱图像融合.实验中将本文方法与Laplacian塔型变换、子波变换、主分量分析等方法进行了比较,结果表明本文所提的基于top-hat算子的融合方法具有优越的性能,拓广了top-hat算子的应用范围.     

卟啉类光电功能材料的研究进展

卟啉及其衍生物是一类具有优良的光电性能的有机半导体材料．引起人们广泛的关注。本文对卟啉类光电材料在模拟生物光合作用中心的光致电荷转移和能量转移，有机太阳能电池．分子光电器件。有机电致发光和光存储等领域的研究进展做一简要介绍。