Quantitative modeling of \textit{in situ} x-ray reflectivity during organic molecule thin film growth

Synchrotron-based x-ray reflectivity is increasingly employed as an \textit{in situ} probe of surface morphology during thin film growth, but complete interpretation of the results requires modeling the growth process. Many models have been developed and employed for this purpose, yet no detailed, comparative studies of their scope and accuracy exists in the literature. Using experimental data obtained from hyperthermal deposition of pentane and diindenoperylene (DIP) on SiO$_2$, we compare and contrast three such models, both with each other and with detailed characterization of the surface morphology using ex-situ atomic force microscopy (AFM). These two systems each exhibit particular phenomena of broader interest: pentacene/SiO$_2$ exhibits a rapid transition from rough to smooth growth. DIP/SiO$_2$, under the conditions employed here, exhibits growth rate acceleration due to a different sticking probability between the substrate and film. In general, \textit{independent of which model is used}, we find good agreement between the surface morphology obtained from fits to the \insitu x-ray data with the actual morphology at early times. This agreement deteriorates at later time, once the root-mean squared (rms) film roughness exceeds about 1 ML. A second observation is that, because layer coverages are under-determined by the evolution of a single point on the reflectivity curve, we find that the best fits to reflectivity data --- corresponding to the lowest values of $\chi_\nu^2$ --- do not necessarily yield the best agreement between simulated and measured surface morphologies. Instead, it appears critical that the model reproduce all local extrema in the data. In addition to showing that layer morphologies can be extracted from a minimal set of data, the methodology established here provides a basis for improving models of multilayer growth by comparison to real systems.Comment: 34 pages (double-spaced, including figures and references), 10 figures, 3 appendice

Prioritizing consumers in smart grid: A game theoretic approach

This paper proposes an energy management technique for a consumer-to-grid system in smart grid. The benefit to consumers is made the primary concern to encourage consumers to participate voluntarily in energy trading with the central power station (CPS) in situations of energy deficiency. A novel system model motivating energy trading under the goal of social optimality is proposed. A single-leader multiple-follower Stackelberg game is then studied to model the interactions between the CPS and a number of energy consumers (ECs), and to find optimal distributed solutions for the optimization problem based on the system model. The CPS is considered as a leader seeking to minimize its total cost of buying energy from the ECs, and the ECs are the followers who decide on how much energy they will sell to the CPS for maximizing their utilities. It is shown that the game, which can be implemented distributedly, possesses a socially optimal solution, in which the sum of the benefits to all consumers is maximized, as the total cost to the CPS is minimized. Numerical analysis confirms the effectiveness of the game. © 2010-2012 IEEE

Management of Renewable Energy for a Shared Facility Controller in Smart Grid

© 2016 IEEE. This paper proposes an energy management scheme to maximize the use of solar energy in the smart grid. In this context, a shared facility controller (SFC) with a number of solar photovoltaic panels in a smart community is considered that has the capability to schedule the generated energy for consumption and trade to other entities. In particular, a mechanism is designed for the SFC to decide on the energy surplus, if there is any, that it can use to charge its battery and sell to the households and the grid based on the offered prices. In this regard, a hierarchical energy management scheme is proposed with a view to reduce the total operational cost to the SFC. The concept of a virtual cost is introduced that aids the SFC to estimate its future operational cost based on some available current information. The energy management is conducted for three different cases, and the optimal cost to the SFC is determined for each case by the theory of maxima and minima. A real-time algorithm is proposed to reach the optimal cost for all cases, and some numerical examples are provided to demonstrate the beneficial properties of the proposed scheme

The Effect of Stress on Battery-Electrode Capacity

Constraint-induced stresses develop during Li-ion battery cycling, because anode and cathode materials expand and contract as they intercalate or de-intercalate Li. We show in this manuscript that these stresses, in turn, can significantly modify the maximum capacity of the device at a given cell voltage. All-solid-state batteries impose an external elastic constraint on electrode particles, promoting the development of large stresses during cycling. We employ an analytic and a finite element model to study this problem, and we predict that the electrode's capacity decreases with increasing matrix stiffness. In the case of lithiation of a silicon composite electrode, we calculate 64% of capacity loss for stresses up to 2 GPa. According to our analysis, increasing the volume ratio of Si beyond 25-30% has the effect of decreasing the total capacity, because of the interaction between neighboring particles. The stress-induced voltage shift depends on the chemical expansion of the active material and on the constraint-induced stress. However, even small voltage changes may result in very large capacity shift if the material is characterized by a nearly flat open-circuit potential curve. Keywords: Finite element modeling; Li-ion battery; Solid electrolyte; Stress-potential coupling; ThermodynamicsUnited States. Department of Energy (Grant DE-SC0002633)United States. Department of Energy. Office of Basic Energy Sciences (Contract DE-FG02-10ER46771

Large Differences in Small RNA Composition Between Human Biofluids.

Extracellular microRNAs (miRNAs) and other small RNAs are implicated in cellular communication and may be useful as disease biomarkers. We systematically compared small RNAs in 12 human biofluid types using RNA sequencing (RNA-seq). miRNAs and tRNA-derived RNAs (tDRs) accounted for the majority of mapped reads in all biofluids, but the ratio of miRNA to tDR reads varied from 72 in plasma to 0.004 in bile. miRNA levels were highly correlated across all biofluids, but levels of some miRNAs differed markedly between biofluids. tDR populations differed extensively between biofluids. Y RNA fragments were seen in all biofluids and accounted for >10% of reads in blood plasma, serum, and cerebrospinal fluid (CSF). Reads mapping exclusively to Piwi-interacting RNAs (piRNAs) were very rare, except in seminal plasma. These results demonstrate extensive differences in small RNAs between human biofluids and provide a useful resource for investigating extracellular RNA biology and developing biomarkers

Lithium metal penetration induced by electrodeposition through solid electrolytes: Example in single-crystal Li6La3ZrTaO12 garnet

Solid electrolytes potentially enable rechargeable batteries with lithium metal anodes possessing higher energy densities than today’s lithium ion batteries. To do so the solid electrolyte must suppress instabilities that lead to poor coulombic efficiency and short circuits. In this work, lithium electrodeposition was performed on single-crystal Li6La3ZrTaO12 garnets to investigate factors governing lithium penetration through brittle electrolytes. In single crystals, grain boundaries are excluded as paths for lithium metal propagation. Vickers microindentation was used to introduce surface flaws of known size. However, operando optical microscopy revealed that lithium metal penetration propagates preferentially from a different, second class of flaws. At the perimeter of surface current collectors smaller in size than the lithium source electrode, an enhanced electrodeposition current density causes lithium filled cracks to initiate and grow to penetration, even when large Vickers defects are in proximity. Modeling the electric field distribution in the experimental cell revealed that a 5-fold enhancement in field occurs within 10 micrometers of the electrode edge and generates high local electrochemomechanical stress. This may determine the initiation sites for lithium propagation, overriding the presence of larger defects elsewhere

Association of NCF2, IKZF1, IRF8, IFIH1, and TYK2 with Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a complex trait characterised by the production of a range of auto-antibodies and a diverse set of clinical phenotypes. Currently, ∼8% of the genetic contribution to SLE in Europeans is known, following publication of several moderate-sized genome-wide (GW) association studies, which identified loci with a strong effect (OR>1.3). In order to identify additional genes contributing to SLE susceptibility, we conducted a replication study in a UK dataset (870 cases, 5,551 controls) of 23 variants that showed moderate-risk for lupus in previous studies. Association analysis in the UK dataset and subsequent meta-analysis with the published data identified five SLE susceptibility genes reaching genome-wide levels of significance (Pcomb<5×10−8): NCF2 (Pcomb = 2.87×10−11), IKZF1 (Pcomb = 2.33×10−9), IRF8 (Pcomb = 1.24×10−8), IFIH1 (Pcomb = 1.63×10−8), and TYK2 (Pcomb = 3.88×10−8). Each of the five new loci identified here can be mapped into interferon signalling pathways, which are known to play a key role in the pathogenesis of SLE. These results increase the number of established susceptibility genes for lupus to ∼30 and validate the importance of using large datasets to confirm associations of loci which moderately increase the risk for disease

Genetic Modifiers of Age at Onset in Carriers of the G206A Mutation in PSEN1 With Familial Alzheimer Disease Among Caribbean Hispanics

IMPORTANCE The present study identified potential genetic modifiers that may delay or accelerate age at onset of familial Alzheimer disease (AD) by examining age at onset in PSEN1 mutation carrier families, and further investigation of these modifiers may provide insight into the pathobiology of AD and potential therapeutic measures. DESIGN, SETTING, AND PARTICIPANTS Using a subset of Caribbean Hispanic families that carry the PSEN1 p.G206A mutation, we performed a 2-stage genome study. The mutation carrier families from an ongoing genetic study served as a discovery set, and the cohort of those with LOAD served as a confirmation set. To identify candidate loci, we performed linkage analysis using 5 p.G206A carrier families (n = 56), and we also performed whole-exome association analysis using 31 p.G206A carriers from 26 families. To confirm the genetic modifiers identified from the p.G206A carrier families, we analyzed the GWAS data for 2888 elderly individuals with LOAD. All study participants were Caribbean Hispanics. RESULTS Linkage analysis of AD identified the strongest linkage support at 4q35 (LOD [logarithm of odds] score, 3.69), and the GWAS of age at onset identified variants on 1p13.1, 2q13, 4q25, and 17p11. In the confirmation stage, genewise analysis identified SNX25, PDLIM3, and 3 SH3 domain genes (SORBS2, SH3RF3, and NPHP1) to be significantly associated with LOAD. Subsequent allelic association analysis confirmed SNX25, PDLIM3, and SORBS2 as genetic modifiers of age at onset of EOAD and LOAD and provided modest support for SH3RF3 and NPHP1. CONCLUSIONS AND RELEVANCE Our 2-stage analysis revealed that SNX25, PDLIM3, and SORBS2 may serve as genetic modifiers of age at onset in both EOAD and LOAD