DIFFER: Publications
Not a member yet
3526 research outputs found
Sort by
A simple and fast high-yield synthesis of silver nanowires
Get PDFSilver nanowires (AgNWs) combine high electrical conductivity with low light extinction in the visible and are used in a wide range of applications, from transparent electrodes, to temperature and pressure sensors. The most common strategy for the production of AgNWs is the polyol synthesis, which always leads to the formation of silver nanoparticles as byproducts. These nanoparticles degrade the performance of AgNWs’ based devices and have to be eliminated by several purification steps. Here, we report a simple and fast synthesis of AgNWs with minimal formation of byproducts, as confirmed by the spectral purity of the final solution. Our synthetic strategy relies on the use of freshly prepared AgCl and on the minimization of gas evolution inside the reaction vessel. The observed synthetic improvements can be of general validity for the polyol synthesis of metallic nanostructures of different shapes and compositions.</p
Enhancing the Electrocatalytic Activity of Redox Stable Perovskite Fuel Electrodes in Solid Oxide Cells by Atomic Layer-Deposited Pt Nanoparticles
Get PDFThe carbon dioxide and steam co-electrolysis in solid oxide cells offers an efficient way to store the intermittent renewable electricity in the form of syngas (CO + H2), which constitutes a key intermediate for the chemical industry. The co-electrolysis process, however, is challenging in terms of materials selection. The cell composites, and particularly the fuel electrode, are required to exhibit adequate stability in redox environments and coking that rules out the conventional Ni cermets. La0.75Sr0.25Cr0.5Mn0.5O3 (LSCrM) perovskite oxides represent a promising alternative solution, but with electrocatalytic activity inferior to the conventional Ni-based cermets. Here, we report on how the electrochemical properties of a state-of-the-art LSCrM electrode can be significantly enhanced by introducing uniformly distributed Pt nanoparticles (18 nm) on its surface via the atomic layer deposition (ALD). At 850 °C, Pt nanoparticle deposition resulted in a ∼62% increase of the syngas production rate during electrolysis mode (at 1.5 V), whereas the power output was improved by ∼84% at fuel cell mode. Our results exemplify how the powerful ALD approach can be employed to uniformly disperse small amounts (∼50 μg·cm–2) of highly active metals to boost the limited electrocatalytic properties of redox stable perovskite fuel electrodes with efficient material utilization.</p
Low-temperature, high-performance thin-film solid oxide fuel cells with tailored nano-column structures of a sputtered Ni anode
No full textA nanostructured electrode for use in low-temperature solid oxide fuel cells has drawn attention due to its high activity. Among various nanostructure fabrication processes, sputtering has shown superior characteristics for nanostructured electrode fabrication and does not require high temperatures. However, the limited performance of sputtered Ni-based anodes and the current lack of a fundamental understanding of nanostructural control remain significant issues. Here, the fabrication process for a high-performance nanostructured Ni anode that works by tailoring a nano-column structure is presented. Controlling the sputtering deposition angle and rotation speed of the substrate significantly improves the in-plane connectivity of the nanostructured Ni anode, resulting in a 50% enhancement in the peak power density of the cell. The maximum performance of the cell with the tailored anode nanostructure was 304 and 477 mW cm−2 at 450 and 500 °C, respectively, which represents the best recorded performance of an anodic aluminum oxide (AAO)-supported Ni-based thin-film SOFC. Further investigation via 1-dimensional simulation showed that the enhancement in the in-plane continuity of the columnar anode structure dominantly affects the performance of TF-SOFCs, which means that the novel process is promising for practical applications of nano-energy devices fabricated by sputtering
Power Pulsing To Maximize Vibrational Excitation Efficiency in N2 Microwave Plasma: A Combined Experimental and Computational Study
No full textPlasma is gaining increasing interest for N2 fixation, being a flexible, electricity-driven alternative for the current conventional fossil fuel-based N2 fixation processes. As the vibrational-induced dissociation of N2 is found to be an energy-efficient pathway to acquire atomic N for the fixation processes, plasmas that are in vibrational nonequilibrium seem promising for this application. However, an important challenge in using nonequilibrium plasmas lies in preventing vibrational-translational (VT) relaxation processes, in which vibrational energy crucial for N2 dissociation is lost to gas heating. We present here both experimental and modeling results for the vibrational and gas temperature in a microsecond-pulsed microwave (MW) N2 plasma, showing how power pulsing can suppress this unfavorable VT relaxation and achieve a maximal vibrational nonequilibrium. By means of our kinetic model, we demonstrate that pulsed plasmas take advantage of the long time scale on which VT processes occur, yielding a very pronounced nonequilibrium over the whole N2 vibrational ladder. Additionally, the effect of pulse parameters like the pulse frequency and pulse width are investigated, demonstrating that the advantage of pulsing to inhibit VT relaxation diminishes for high pulse frequencies (around 7000 kHz) and long power pulses (above 400 μs). Nevertheless, all regimes studied here demonstrate a clear vibrational nonequilibrium while only requiring a limited power-on time, and thus, we may conclude that a pulsed plasma seems very interesting for energy-efficient vibrational excitation.</p
Time series forecasting on multi-variate solar radiation data using deep learning (LSTM)
No full textEnergy management is an emerging problem nowadays and utilization of renewable energy sources is an efficient solution. Solar radiation is an important source for electricity generation. For effective utilization, it is important to know precisely the amount from different sources and at different horizons: minutes, hours, and days. Depending on the horizon, two main classes of methods can be used to forecast the solar radiation: statistical time series forecasting methods for short to midterm horizons and numerical weather prediction methods for medium- to long-term horizons. Although statistical time series forecasting methods are utilized in the literature, there are a limited number of studies that utilize deep artificial neural networks. In this study, we focus on statistical time series forecasting methods for short-term horizons (1 h). The aim of this study is to discover the effect of using multivariate data on solar radiation forecasting using a deep learning approach. In this context, we propose a multivariate forecast model that uses a combination of different meteorological variables, such as temperature, humidity, and nebulosity. In the proposed model, recurrent neural network (RNN) variation, namely a long short-term memory (LSTM) unit is used. With an experimental approach, the effect of each meteorological variable is investigated. By hyperparameter tuning, optimal parameters are found in order to construct the best models that fit the global solar radiation data. We compared the results with those of previous studies and we found that the multivariate approach performed better than the previous univariate models did. In further experiments, the effect of combining the most effective parameters was investigated and, as a result, we observed that temperature and nebulosity are the most effective parameters for predicting future solar radiance
Terahertz Time-Domain Spectroscopy and Near-Field Microscopy of Transparent Silver Nanowire Networks
No full textTransparent conductive layers are key components of optoelectronic devices. Here, a polyol method is used to synthesize large quantities of monodisperse silver nanowires (AgNWs) and these are used to fabricate transparent conducting networks over large areas. The optical extinction and terahertz (THz) conductance of these networks are simultaneously investigated, using optical and THz spectroscopy, and THz near‐field microscopy. The combination of optical and THz measurements allows the identification of transparent regions with high conductance. The THz near‐field measurements reveal local variations in the THz transmission and conductance that are averaged in far‐field measurements. These results demonstrate that THz near‐field microscopy is a powerful tool for the quantitative investigation of new conductive transparent electrodes
Understanding the Film Formation Kinetics of Sequential Deposited Narrow-Bandgap Pb–Sn Hybrid Perovskite Films
No full textCorrecting for non-periodic behaviour in perturbative experiments: application to heat pulse propagation and modulated gas-puff experiments
Get PDFThis paper introduces a recent innovation in dealing with non-periodic behavior often referred to as transients. These transients can be the result from unforced response due to the initial condition and other drifts which are a source of error when performing and interpreting Fourier analysis on measurement data. Fourier analysis is particularly relevant in system identification used to build feedback controllers and the analysis of various pulsed experiments such as heat pulse propagation studies. The basic idea behind the methodology is that transients are continuous complex-valued smooth functions in the Fourier domain which can be estimated from the Fourier data. Then, these smooth functions can be approximately subtracted from the data such that only periodic components are retained. The merit of the approach is shown in two experimental examples, i.e., heat pulse propagation (core transport analysis) and radiation front movement due to gas puffing. The examples show that the quality of the data is significantly improved such that it allows new interpretation of the results even for non-ideal measurements.</p