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Interfacial Dynamics and Contact Passivation in Perovskite Solar Cells(Wiley, 2018-11-15)Charge accumulation at the electron and hole transport layers generates anomalous electrical behavior in perovskite solar cells (PSCs). Hysteresis in the current–voltage characteristic and recombination at the interfaces are the clearest manifestations of this phenomenon, which compromises device performance and stability. Here, the underlying charge-carrier dynamics of a variety of PSCs are investigated by analyzing their transient photocurrent response. Towards shorter time scales, PSCs often show increasingly severe hysteretic responses. This phenomenon is correlated with the presence of interfacial accumulated charges that hinders the photogenerated carrier extraction process. However, introducing passivating contacts improves the carrier-injection properties and the devices become completely hysteresis free. These results underline the importance of contact passivation for PSCs and the need to further develop new passivating interlayers that simultaneously eliminate charge-carrier recombination and provide selective transport for each carrier type at the PSC's contacts.
A Comparative Study of Interdigitated Electrode and Quartz Crystal Microbalance Transduction Techniques for Metal–Organic Framework-Based Acetone Sensors(MDPI AG, 2018-11-14)We present a comparative study of two types of sensor with different transduction techniques but coated with the same sensing material to determine the effect of the transduction mechanism on the sensing performance of sensing a target analyte. For this purpose, interdigitated electrode (IDE)-based capacitors and quartz crystal microbalance (QCM)-based resonators were coated with a zeolitic⁻imidazolate framework (ZIF-8) metal⁻organic framework thin films as the sensing material and applied to the sensing of the volatile organic compound acetone. Cyclic immersion in methanolic precursor solutions technique was used for depositing the ZIF-8 thin films. The sensors were exposed to various acetone concentrations ranging from 5.3 to 26.5 vol % in N₂ and characterized/compared for their sensitivity, hysteresis, long-term and short-term stability, selectivity, detection limit, and effect of temperature. Furthermore, the IDE substrates were used for resistive transduction and compared using capacitive transduction.
Reduced ion migration and enhanced photoresponse in cuboid crystals of methylammonium lead iodide perovskite(IOP Publishing, 2018-11-10)The optoelectronic and photocatalytic properties of a number of semiconductor materials, including halide perovskites, have recently been found to be facet-dependent. While methylammonium lead iodide (CH3NH3PbI3) perovskite – an important material for energy applications – has shown facet-dependent electronic properties as well, most studies on CH3NH3PbI3 perovskite were performed on rhombo-dodecahedral (or rhombic) single crystals with the (200) and (112) facets exposed. In contrast, less is known about the electronic properties, including mixed conductivity behavior and possible in-plane anisotropy, of the (002) facet. Thus, we report a facile method for the growth of cuboid crystals of CH3NH3PbI3 perovskite with the (002) and (110) facets exposed. Two-terminal devices fabricated on the (002) facet demonstrate significantly improved charge transport and optoelectronic characteristics compared to those on the (200) facet of typical rhombic crystals, including: reduced ion migration, low dark current, and temporally-stable high photocurrents. These desirable characteristics of cuboid crystals are linked to their favorable growth conditions and preferred facet orientations. Our results provide a guidance for utilizing facets and crystal growth to achieve more efficient in-plane halide perovskite devices.
Statistical Analysis and Bayesian Methods for Fatigue Life Prediction and Inverse Problems in Linear Time Dependent PDEs with Uncertainties(2018-11-10)This work employs statistical and Bayesian techniques to analyze mathemati- cal forward models with several sources of uncertainty. The forward models usu- ally arise from phenomenological and physical phenomena and are expressed through regression-based models or partial differential equations (PDEs) associated with un- certain parameters and input data. One of the critical challenges in real-world ap- plications is to quantify uncertainties of the unknown parameters using observations. To this purpose, methods based on the likelihood function, and Bayesian techniques constitute the two main statistical inferential approaches considered here. Two problems are studied in this thesis. The first problem is the prediction of fatigue life of metallic specimens. The second part is related to inverse problems in linear PDEs. Both problems require the inference of unknown parameters given certain measurements. We first estimate the parameters by means of the maximum likelihood approach. Next, we seek a more comprehensive Bayesian inference using analytical asymptotic approximations or computational techniques. In the fatigue life prediction, there are several plausible probabilistic stress-lifetime (S-N) models. These models are calibrated given uniaxial fatigue experiments. To generate accurate fatigue life predictions, competing S-N models are ranked according to several classical information-based measures. A different set of predictive information criteria is then used to compare the candidate Bayesian models. Moreover, we propose a spatial stochastic model to generalize S-N models to fatigue crack initiation in general geometries. The model is based on a spatial Poisson process with an intensity function that combines the S-N curves with an averaged effective stress that is computed from the solution of the linear elasticity equations.
Interaction of amylin species with transition metals and membranes(Elsevier BV, 2018-11-10)Islet Amyloid Polypeptide (IAPP), also known as amylin, is a 37-amino-acid peptide hormone that is secreted by pancreatic islet β-cells. Amylin is complementary to insulin in regulating and maintaining blood glucose levels in the human body. The misfolding and aggregation of amylin is primarily associated with type 2 diabetes mellitus, which is classified as an amyloid disease. Recently, the interactions between amylin and specific metal ions, e.g., copper(II), zinc(II), and iron(II), were found to impact its performance and aggregation processes. Therefore, the focus in this review will be on how the chemistry and structural properties of amylin are affected by these interactions. In addition, the impact of amylin and other amyloidogenic peptides interacting with metal ions on the cell membranes is discussed. In particular, recent studies on the interactions of amylin with copper, zinc, iron, nickel, gold, ruthenium, and vanadium are discussed.