pinecone/core-2020-05-10-deduplication huggingface dataset:
Printed Nanostructures for Organic Photovoltaic Cells and Solution‐Processed Polymer Light‐Emitting Diodes

We review the progress on printing‐based technologies for organic electronic devices, especially organic photovoltaic (OPV) cells and polymer light‐emitting diodes (PLEDs). First we discuss recent efforts to introduce interdigitated nanostructures on the order of tens of nanometers to the photoactive layers of OPV cells using nanoimprint lithography including a soft‐printing process developed in our research group that can easily produce sub‐20 nm scale organic semiconductor nanopillars. Second, we review solution‐processible printing technologies such as gravure printing, screen printing, blade coating, and slot–die coating for high‐throughput manufacturing of PLEDs.Illuminating results: This article reviews the progress on printing‐based technologies for organic electronic devices, especially organic photovoltaic (OPV) cells and polymer light‐emitting diodes (PLEDs), including solution‐processible printing technologies such as gravure printing, screen printing, blade coating, and slot–die coating for high‐throughput manufacturing
Inkjet printed TiO2 nanoparticles from aqueous solutions for dye sensitized solar cells (DSSCs)

This is the accepted  version  of  the  following  article: Cherrington, R., Hughes, D. J., Senthilarasu, S. and Goodship, V. (2015), Inkjet-Printed TiO2 Nanoparticles from Aqueous Solutions for Dye-Sensitized Solar Cells (DSSCs). Energy Technology., which has been published in final form at http://dx.doi.org/10.1002/ente.201500096This work reports on the formulation of suitable ink for inkjet printing of TiO2 by investigating the critical parame- ters of particle size, pH, viscosity, and stability. Aqueous sus- pensions of TiO2 nanoparticles (Degussa, P25) were pre- pared with the addition of 25 wt % polyethylene glycol 400 as a humectant to minimize drying at the printer nozzles and reduce the likelihood of nozzle blockage. The inkjet-printed TiO2 layers were assembled into dye-sensitized solar cells. The current–voltage (I–V) characteristics were measured under one sun (air mass 1.5, 100 mW cm 2) using a source meter (Model 2400, Keithley Instrument, Inc.), and the active area of the cell was 0.25 cm2. The inkjet-printed TiO2 photoanode produced a device with a short-circuit current (Isc) of 9.42 mA cm 2, an open-circuit voltage (Voc) of 0.76 V, and a fill factor (FF) of 0.49, resulting in a power conversion efficiency (PCE) of 3.50 %.Engineering and Physical Sciences Research Council (EPSRC
Organic semiconductor g-C3N4 modified TiO2 nanotube arrays for enhanced photoelectrochemical performance in wastewater treatment

This work was supported by China Scholarship Council (CSC), Royal Society of Edinburgh (RSE) and Engineering and Physical Sciences Research Council (EPSRC). Date of Acceptance: 27/05/2015g-C3N4 sensitized TiO2 nanotube arrays (g-C3N4/TNTs) were fabricated by a simple solid sublimation and transition (SST) method using urea as precursor. The photoelectrochemical (PEC) performances were evaluated in this work. It is proposed that the g-C3N4 layer can play dual roles: surface sensitization and passivation of TNTs surface trap states to inhibit charge recombination. The g-C3N4/TNTs exhibited significantly improved PEC performance compared with TNTs under blue light (460 nm) irradiation. The g-C3N4/TNTs prepared from 3 g urea showed the highest photocurrent density of ca. 65 μA cm-2, which is almost 10 times as high as that of TNTs. Furthermore, g-C3N4/TNTs showed enhanced photoelectrocatalytic degradation of methylene blue (MB) under the blue light irradiation. The stable performance of degradation of MB in the multicycle tests suggests that the hybrid g-C3N4/TNTs electrode could be used as a low-cost photoelectrode material in wastewater treatment process.Publisher PDFPeer reviewe
The Composite Supercapacitor

Inspired by the design of composite materials, we propose a new composite supercapacitor that comprises an integrated cell with high-power- and high-energy-related electrode materials. The composite electrochemical double-layer capacitor (EDLC) is the equivalent circuit of a high-power EDLC of power P1 and energy E1 and a high-energy EDLC of power P2 and energy E2 connected in parallel. A methodology is proposed and validated in this study for the design of an application-specific composite supercapacitor of power P and energy E with P1/E1>P/E>P2/E2. The methodology was tested successfully in medium- and large-sized application-specific composite supercapacitors, which were fabricated in the form of pouch cells using an organic electrolyte. The application-specific composite supercapacitors offered weight reductions of 40–60 % compared with supercapacitors based on the high-power- or on high-energy-related electrode materials only
Synthesis of Bio-Dimethyl Ether Based on Carbon Dioxide-Enhanced Gasification of Biomass: Process Simulation Using Aspen Plus

YesProcess simulation of a single-step synthesis of DME based on CO2-enhanced gasification of rice straw was conducted using Aspen PlusTM. The process consists of gasification unit, heat recovery unit, gas purification unit, single-step DME synthesis, and DME separation unit. In the simulation, highly pure DME was produced by the control of CO2 concentration in syngas to a very low level prior to synthesis. A gasification system efficiency of 36.7% and CO2 emission of 1.31 kg/kg of DME were achieved. Bio-DME production based on CO2-enhanced gasification of biomass was found to be more cost-effective as it required 19.6% less biomass than that of DME production based on conventional biomass gasification. The performance and environmental benefits of the proposed process could be further improved by the utilization of unreacted gases and the handling of CO2 generated via incorporating poly-generation concept or carbon storage, which could also potentially improve process economics.Ningbo Bureau of Science and Technology; Innovation Team Scheme; Major R&D Programme; Provincial Innovation Team on the Commercialisation of SOx and NOx Removal Technologies; University of Nottingham Ningbo Chin
Tin oxide light-scattering layer for Titania Photoanodes in dye-sensitized solar cells

This is the peer reviewed version of the following article: BATMUNKH, M. ...et al., 2016. Tin oxide light-scattering layer for Titania Photoanodes in dye-sensitized solar cells. Energy Technology, 4(8), pp. 959-966, which has been published in final form at http://dx.doi.org/10.1002/ente.201600008. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.High-performance dye-sensitized solar cell (DSSC) devices rely on photoanodes that possess excellent light-harvesting capability and high surface area for sufficient dye adsorption. In this work, morphologically controlled SnO2 microstructures have been synthesized and used as an efficient light backscattering layer on top of the nanocrystalline TiO2 layer to prepare a double-layered photoanode. By optimizing the thickness of both the TiO2 bottom layer and SnO2 top layer, a high power conversion efficiency (PCE) of 7.8% is achieved, demonstrating a ~38% enhancement in the efficiency when compared to a nanocrystalline TiO2-only photoanode (5.6%). We attribute this efficiency improvement to the superior light backscattering capability of SnO2 microstructures
Combined calcium looping and chemical looping combustion for post‐combustion carbon dioxide capture: process simulation and sensitivity analysis

In this work, a combined calcium looping and chemical looping combustion (CaL--CLC)
technology is simulated at thermodynamic equilibrium conditions and the results in terms of
efficiency, power production, and solids circulation rates are compared with the case of using
CaL alone. In addition, a new solids looping configuration in the CaL--CLC process is
proposed with the purpose of mitigating the loss of calcium oxide conversion after high cycle
numbers. Simulations show an improved process efficiency of the CaL--CLC method
compared with CaL alone (34.2 vs. 31.2 % higher heat value) and an increased power output
(136 vs. 110 MWe additional power) due to the higher energy requirement to preheat the
reactants. A sensitivity analysis of the process operating parameters highlights the particular
importance of the temperature difference between reactors, which has a strong impact on the
required mass of solids circulating in the loops. Finally, partial carbon dioxide capture
scenarios are considered and indicate that lower capture levels are suitable to match regulation
targets
A hydrodynamic study of a fast‐bed dual circulating fluidized bed for chemical looping combustion

This study explores the use of a dual interconnected circulating fluidized bed (CFB) for chemical looping combustion. This design can enhance gas–solid interactions, but it is difficult to control the solid transfer and circulation rates. With the use of a 1:1 scale cold-flow model, an investigation determining the hydrodynamic behavior of the dual CFB system has been conducted. The cold-flow system consists of two identical fast-bed risers, each with an internal diameter of 100 mm and a height of 7 m. The simplified cold-flow model is based on the chemical looping Pilot-Scale Advanced CO2 Capture Technology (PACT) facility at Cranfield. Here, we have determined the minimum fluidization and transport velocities, and we have assessed the solid density profiles, transport capacity, and potential for the dilution by air/N2 leakage into the CO2 stream exiting the fuel reactor. The experimental procedure uses two different bed materials, molochite (ceramic clay) and FE100 (iron particles), and it satisfies the dynamic scaling laws to model the bed inventory within the system. The results indicate that the two fast-bed risers share similar density and pressure profiles. Stable circulation can be achieved through pneumatic transport. The circulation rate of the system is flexible and can be adjusted by altering the fluidization velocity in the riser and by altering the bed inventory. The gas leakage from the loop seal to the cyclone was found to be sensitive to the bed height and fluidization velocity in the loop seal. However, by maintaining a loop-seal bed height above 600 mm during operation, the outlet stream remains undiluted
Analytical approach for evaluation of lithium-ion battery cells

A new method for evaluation of battery cells containing porous thin-layer electrodes is developed. For this purpose, a typical concept of chemical reaction engineering to classify reactors by dimensionless characteristic values is used. Therefore, the system of equations describing the porous electrodes in a battery cell is transferred to dimensionless notation and corresponding dimensionless properties are developed. The required kinetic data are measured with the help of electrochemical test cells. A complete set of parameters for the description of the lithium-ion battery is determined and the characteristic properties for the chosen example are calculated and analyzed. Finally, the performance of the anode and cathode using lithium manganese oxide and surface-modified graphite as active materials is compared with the aid of the newly developed dimensionless parameters
Use of a Chemical-Looping Reaction to Determine the Residence Time Distribution of Solids in a Circulating Fluidized Bed

The residence time distribution (RTD) of solids in various sections of a circulating fluidized bed (CFB) is of great importance for design and operation but is often difficult to determine experimentally. A noninvasive method is described, for which the RTD was derived from temporal measurements of the temperature following the initiation of a chemical-looping reaction. To demonstrate the method, a CuO-based oxygen carrier was used in a small-scale CFB, and measurements were made in the fuel reactor, operated as a bubbling fluidized bed. The measurements were fitted to the tanks-in-series model, modified to account for heat losses from the reactor. There was excellent agreement between the model and the experiment. Limitations and further improvements of the method are discussed, also with respect to larger reactors.This work is supported by the Engineering and Physical Sciences Research Council (EPSRC Grant EP/I010912/1).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/ente.20160014
Improved Performance of Polymer Electrolyte Membrane Fuel Cells with Modified Microporous Layer Structures

A possible method to improve membrane humidity conditions in polymer electrolyte membrane fuel cells and, therefore, the cell performance is the optimization of microporous layer  MPL  structures. In this work, water transport in modified MPL materials in polymer electrolyte membrane fuel cells  PEMFCs  was investigated by in amp; 8197;operando synchrotron X ray tomography. Three different types of MPLs are compared  A reference standard MPL material, an MPL material with a special wavy structure, and an MPL with randomly distributed holes. We found a strong impact of the modified MPL structure on the water distribution at operating temperatures of 40 and 55 amp; 8201; C and an increase of cell performance up to 14 amp; 8201;  compared to the reference cell. We assume the water distribution at the membrane to be responsible for the performance increase and provide a detailed discussion
Powering lights with piezoelectric energy harvesting floors

This is the peer reviewed version of the following article: Onoriu Puscasu, Nathan Counsell, Mohammad R. Herfatmanesh, Richard Peace, John Patsavellas, and Rodney Day, ???Powering Lights with Piezoelectric Energy???Harvesting Floors???, Energy Technology, Vol. 6 (5): 906-916, May 2018, which has been published in final form at https://doi.org/10.1002/ente.201700629. Under embargo until 6 March 2019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The present work introduces a new technology for converting energy from steps into electricity. It starts with a study on the mechanical energy available from steps in a busy corridor. The subsequent development efforts and devices are presented, with an iterative approach to prototyping. Methods for enhancing piezoelectric conversion efficiency have been found as part of the process, and are introduced in the present article. Capitalising on these findings, we have fabricated energy harvesting demonstrators for stairs that power embedded emergency lighting. The typical working unit comprises an energy harvesting stair nosing, a power management circuit, and an embedded LED that lights the tread in front of the user with an illuminance corresponding to emergency standards. The stair nosing generates up to 17.7 mJ of useful electrical energy per activation to provide up to 10.6 seconds of light. The corresponding energy density is 0.49 J per meter square and per step, with an 8.5 mm thick active layer
Compatibility of NiO/CuO in Ca‐Cu chemical looping for high‐purity H2 production with CO2 capture

Ca‐Cu chemical looping is a novel and promising approach in converting methane into pure H2 following the principle of sorption‐enhanced reforming. Its operational efficiency is largely determined by an appropriate coexistence of Cu‐based oxygen carriers and Ni‐based catalysts. In this work, NiO/CuO composites were synthesized and their catalytic activity for H2 production was measured using a fixed‐bed reactor system equipped with an online gas analyzer. It is reported for the first time that the presence of CuO could hinder the activity of Ni‐based catalysts in H2 production, and experimental results show that the negative effect of CuO is strengthened with increasing CuO content and calcination temperature during sample preparation. With the help of a series of specific test and characterization techniques (SEM‐EDS, BET, XRD, TPR and XPS), interaction rules between NiO and CuO was further investigated and understood, and based on that an action mechanism model was proposed. Furthermore, an arrangement of mixed particles that avoiding the intimate contact of CuO/NiO was suggested and tested, and a superior performance was demonstrated while observing no restrictions of CuO on Ni‐based catalysts in sorption‐enhanced steam‐methane reforming under the conditions of Ca‐Cu chemical looping
Adjustment of state space models in view of area rainfall estimation

This paper uses state space models and the Kalman filter to merge weather radar and rain gauge measurements in order to improve area rainfall estimates. Particular attention is given to the estimation of state space model parameters because precipitation data clearly deviates from the normal distribution, and the commonly used maximum likelihood method is difficult to apply and does not perform well. This work is based on 17 storms occurring between September 1998 and November 2000 in an area including part of the Alenquer river hydrographical basin. Based on these data, the work aims to investigate the importance of the parameters estimation method to the accuracy of mean area precipitation estimates. It was possible to conclude that the distribution-free estimation methods produce, in general, better mean area rainfall estimates than the maximum likelihood. Copyright (C) 2010 John Wiley & Sons, Ltd
Analysis of non-stationary climate-related extreme events considering climate change scenarios: an application for multi-hazard assessment in the Dar es Salaam region, Tanzania

In this paper we have put forward a Bayesian framework for the analysis and testing of possible non-stationarities in extreme events. We use the extreme value theory to
model temperature and precipitation data in the Dar es Salaam region, Tanzania. Temporal
trends are modeled writing the location parameter of the generalized extreme value distribution in terms of deterministic functions of explanatory covariates. The analyses are performed using synthetic time series derived from a Regional Climate Model. The simulations, performed in an area around the Dar es Salaam city, Tanzania, take into account two Representative Concentration Pathways scenarios from the Intergovernmental Panel on Climate Change. Our main interest is to analyze extremes with high spatial and temporal resolution and to pursue this requirement we have adopted an individual grid box analysis approach. The approach presented in this paper is composed of the following key
elements: (1) an advanced Bayesian method for the estimation of model parameters, (2) a
rigorous procedure for model selection, and (3) uncertainty assessment and propagation.
The results of our analyses are intended to be used for quantitative hazard and risk
assessment and are presented in terms of hazard curves and probabilistic hazard maps. In the case study we found that for both the temperature and precipitation data, a linear trend in the location parameter was the only model performing better than the stationary one in the areas where evidence against the stationary model exists
Forecast verification for extreme value distributions with an
  application to probabilistic peak wind prediction

Predictions of the uncertainty associated with extreme events are a vital
component of any prediction system for such events. Consequently, the
prediction system ought to be probabilistic in nature, with the predictions
taking the form of probability distributions. This paper concerns probabilistic
prediction systems where the data is assumed to follow either a generalized
extreme value distribution (GEV) or a generalized Pareto distribution (GPD). In
this setting, the properties of proper scoring rules which facilitate the
assessment of the prediction uncertainty are investigated and closed-from
expressions for the continuous ranked probability score (CRPS) are provided. In
an application to peak wind prediction, the predictive performance of a GEV
model under maximum likelihood estimation, optimum score estimation with the
CRPS, and a Bayesian framework are compared. The Bayesian inference yields the
highest overall prediction skill and is shown to be a valuable tool for
covariate selection, while the predictions obtained under optimum CRPS
estimation are the sharpest and give the best performance for high thresholds
and quantiles
Bayesian Nonstationary Spatial Modeling for Very Large Datasets

With the proliferation of modern high-resolution measuring instruments
mounted on satellites, planes, ground-based vehicles and monitoring stations, a
need has arisen for statistical methods suitable for the analysis of large
spatial datasets observed on large spatial domains. Statistical analyses of
such datasets provide two main challenges: First, traditional
spatial-statistical techniques are often unable to handle large numbers of
observations in a computationally feasible way. Second, for large and
heterogeneous spatial domains, it is often not appropriate to assume that a
process of interest is stationary over the entire domain.
  We address the first challenge by using a model combining a low-rank
component, which allows for flexible modeling of medium-to-long-range
dependence via a set of spatial basis functions, with a tapered remainder
component, which allows for modeling of local dependence using a compactly
supported covariance function. Addressing the second challenge, we propose two
extensions to this model that result in increased flexibility: First, the model
is parameterized based on a nonstationary Matern covariance, where the
parameters vary smoothly across space. Second, in our fully Bayesian model, all
components and parameters are considered random, including the number,
locations, and shapes of the basis functions used in the low-rank component.
  Using simulated data and a real-world dataset of high-resolution soil
measurements, we show that both extensions can result in substantial
improvements over the current state-of-the-art.Comment: 16 pages, 2 color figure
Joint probabilistic forecasting of wind speed and temperature using
  Bayesian model averaging

Ensembles of forecasts are typically employed to account for the forecast
uncertainties inherent in predictions of future weather states. However, biases
and dispersion errors often present in forecast ensembles require statistical
post-processing. Univariate post-processing models such as Bayesian model
averaging (BMA) have been successfully applied for various weather quantities.
Nonetheless, BMA and many other standard post-processing procedures are
designed for a single weather variable, thus ignoring possible dependencies
among weather quantities. In line with recently upcoming research to develop
multivariate post-processing procedures, e.g., BMA for bivariate wind vectors,
or flexible procedures applicable for multiple weather quantities of different
types, a bivariate BMA model for joint calibration of wind speed and
temperature forecasts is proposed based on the bivariate truncated normal
distribution. It extends the univariate truncated normal BMA model designed for
post-processing ensemble forecast of wind speed by adding a normally
distributed temperature component with a covariance structure representing the
dependency among the two weather quantities.
  The method is applied to wind speed and temperature forecasts of the
eight-member University of Washington mesoscale ensemble and of the
eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service
and its predictive performance is compared to that of the general Gaussian
copula method. The results indicate improved calibration of probabilistic and
accuracy of point forecasts in comparison to the raw ensemble and the overall
performance of this model is able to keep up with that of the Gaussian copula
method.Comment: 22 pages, 4 figures. arXiv admin note: substantial text overlap with
  arXiv:1305.118