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SRMs have high torque ripples. Modifying the stator and rotor shape of SRMs is one of their methods to remove torque ripples. In this study, new rotor and stator geometries have been proposed for SRM. Performance characteristics are obtained and dynamic analyses are carried out for both novel and classical 6/4 SRMs. FFT analyses of the torque characteristics are also performed for the both SRMs. The changes in performance and the FFT results of torque characteristics are determined for both the current-controlled and uncontrolled operations in both SRMs. 23.60% and 15.20% improvements in torque ripples are achieved for the uncontrolled and current-controlled operations in SRMs respectively. When the FFT analyses are applied to the torque characteristics, the THD values are obtained as 21.19% and 8.31% in the uncontrolled and controlled motor current operations respectively. A 122 W three-phase 6/4 SRM simulation based on the MATLAB–SIMULINK environment is performed to validate the improvement of the torque ripple of the proposed model.

Poly(ethylene oxide) (PEO)-based polymer electrolytes are a promising class of materials for use in lithium-ion batteries due to their high ionic conductivity and flexibility. In this study, the effects of polymer architecture including linear, star, and hyperbranched and salt (lithiumbis(trifluoromethanesulfonyl)imide (LiTFSI)) concentration on the glass transition (Tg), microstructure, phase diagram, free volume, and bulk viscosity, all of which play a significant role in determining the ionic conductivity of the electrolyte, have been systematically studied for PEO-based polymer electrolytes. The branching of PEO widens the liquid phase toward lower salt concentrations, suggesting decreased crystallization and improved ion coordination. At high salt loadings, ion clustering is common for all electrolytes, yet the cluster size and distribution appear to be strongly architecture-dependent. Also, the ionic conductivity is maximized at a salt concentration of [Li/EO ≈ 0.085] for all architectures, and the highly branched polymers displayed as much as three times higher ionic conductivity (with respect to the linear analogue) for the same total molar mass. The architecture-dependent ionic conductivity is attributed to the enhanced free volume measured by positron annihilation lifetime spectroscopy. Interestingly, despite the strong architecture dependence of ionic conductivity, the salt addition in the highly branched architectures results in accelerated yet similar monomeric friction coefficients for these polymers, offering significant potential toward decoupling of conductivity from segmental dynamics of polymer electrolytes, leading to outstanding battery performance.

© 2022 The Author(s)Battery energy storage systems (BESS) are essential for flexible and reliable grid performance as the number of renewable energy sources in grids rises. The operational life of the batteries in BESS should be taken into account for maximum cost savings, despite the fact that they are beneficial for economical grid operation. In this context, this paper present a new battery cycle counting perspective for energy management of grid-connected BESS. For this purpose battery\"s one full charge–discharge cycle characteristic is compared with the operating battery charge–discharge cycle every time step. This comparison was explained mathematically and graphically in detail. The results are compared with the rain flow counting method which is the most popular cycle counting algorithm. Consequently, this cycle counting approach successfully counts the battery charge/discharge cycles and it has shown that has an advantage for BESSs due to being specifically developed just for batteries.

The cold filter plugging point (CFPP) value of biodiesel fuel blends need to be improved because of it has been reported that utilizing high concentrations of biodiesel blends in cold climates can cause major issues. Therefore, the main objective of the study is to improve CFPP value of biodiesel blends using ethyl proxitol additive. It is also to examine combustion and emission of the blends behavior. Biodiesel blends were prepared as; 5% ethyl proxitol-10% biodiesel-85% ultra-low sulfur diesel (ULSD) named as E5B10 and 5% ethyl proxitol-20% biodiesel-75% ULSD named as E5B20 fuel. These fuel blends were compared with ULSD fuel in a compression ignition engine at a constant engine speed of 1500 rev/min and four different loads (idle, 1, 2, and 3 bar BMEP) of eddy current dynamometer. The addition of ethyl proxitol led to a decrease in in-cylinder pressure and temperature due to an about 1˚ later SOC and 2˚ earlier EOC compared to ULSD. The pressure rise rate was slightly higher compared to ULSD at both low and high loads, with a difference of about 1 bar per degree. As a result, these blends with improved CFPP value can be used in cold climates.

ispartof: ENERGY REPORTS vol:9 pages:2169-2184 status: accepted

Hybrid inorganic-organic perovskites have attracted considerable attention over recent years as promising processable electronic materials. In particular, the rich structural dynamics of these ‘soft’ materials has become a subject of investigation and debate due to their direct influence on the perovskites' optoelectronic properties. Significant effort has focused on understanding the role and behaviour of the organic cations within the perovskite, as their rotational dynamics may be linked to material stability, heterogeneity and performance in (opto)electronic devices. To this end, we use two-dimensional IR spectroscopy (2DIR) to understand the effect of partial caesium alloying on the rotational dynamics of the methylammonium cation in the archetypal hybrid perovskite CH3NH3PbI3. We find that caesium incorporation primarily inhibits the slower ‘reorientational jump’ modes of the organic cation, whilst a smaller effect on the fast ‘wobbling time’ may be due to distortions and rigidisation of the inorganic cuboctahedral cage. 2DIR centre-line-slope analysis further reveals that while static disorder increases with caesium substitution, the dynamic disorder (reflected in the phase memory of the N-H stretching mode of methylammonium) is largely independent of caesium addition. Our results contribute to the development of a unified model of cation dynamics within organohalide perovskites.

In typical vehicle-to-vehicle (V2V) charging systems, energy transfer is provided from a battery electric vehicle (BEV) to charge the energy storage unit of another BEV. In this study, the utilization of a fuel cell electric vehicle (FCEV) as an energy provider is purposed to charge the energy storage unit of a BEV in V2V interaction. Since FCEVs are filled with hydrogen, it also eliminates the disadvantages of traditional BEV energy providers, such as a reduction in the amount of stored energy and the need for more time to charge fully. In the designed system, a new plug-in external V2V battery charger topology supported by an FCEV has been proposed to supply electrical energy. In order to control the energy transfer between electric vehicles (EVs), a sliding mode controller is adapted to manage the external converter interface located between vehicles. The designed controller shows improved robustness against the system dynamics uncertainties and disturbances generated by a variety of internal and external causes. In the designed section, a proton exchange membrane fuel cell with the maximum operational rating of 75 kW is used as an energy provider to feed consumer loads. The proposed system has been designed and analyzed for several loading situations from 20% to 100% loading and obtained performance results have been compared with a conventional controlled V2V battery charger system. The case studies validate that the proposed V2V charger system gives better results than the conventional controlled FC-supported V2V. The stability and robustness of output electrical waveforms are better for the designed system. In this context, the tracking error of the conventional controller is about 8% larger than that of the designed sliding mode control for dynamic load changes. The sliding mode controller has a faster settling time (approximately 0.12 s) in comparison with the conventional controlled V2V charger system. Also, mean absolute error values verify that the designed sliding mode controller operates smoothly under all cases except load transition compared to the typical control method. As a result, the case studies show that satisfactory results have been obtained for the designed system.

ispartof: IET RENEWABLE POWER GENERATION vol:17 issue:9 pages:2411-2432 status: published

We report the results of modelling the transport of n-octane and n-hexadecane and their mixtures through carbonaceous nanopores at high-pressure conditions. Pores are modelled as smooth slit sheets with perturbations added as ridges and steps and a version of the Statistical Associating Fluid Theory (SAFT-γ Mie) is used both as equation of state and as a coarse-grained force field to account for fluid-fluid and fluid-solid molecular interactions. Molecular simulation allowed the description of transport diffusivities in terms of molecular flow, using boundary driven non-equilibrium molecular dynamics (BD-NEMD). Transport diffusivities are also independently calculated using equilibrium and external force non-equilibrium molecular dynamics (EF-NEMD) simulations, after accounting for the adsorption on the pores. We show consistency between the approaches for quantifying transport in terms of permeabilities (Darcy flows) and transport diffusivities. We find that smooth slit carbon pore models, which are commonly employed in literature as surrogates for kerogen regions in shale, are an inadequate representation of ultra-confined natural pores. For slit pores, the flow patterns are characterized by a fully-mutualized plug-like flow and fast transport. However, by incorporating even a small amount of rugosity (roughness) to the solid walls, the diffusion coefficients decrease dramatically with surface roughness significantly affecting the characteristic transport and velocity profiles inside the pores. In all cases, it is seen that there are important cross-correlation effects, influencing the way components of the mixture flow together. Calculated self-diffusivities are orders of magnitude smaller than the observed transport diffusivities for liquid mixtures. This work has a direct impact on the understanding and modelling of unconventional hydrocarbon recovery and flow in organic shale rocks.

ispartof: ENERGY REPORTS vol:8 pages:847-856 ispartof: location:PEOPLES R CHINA, Nanning status: published

In recent years, higher penetrations of renewable energy generations helped persuade sustainable energy and environmental targets, although their intermittent and fluctuated nature raised technical challenges. However, hybrid power system can minimize these technical issues by integrating flexible generation capable renewable energy sources like biomass. This study deals with optimizing gridintegrated and stand-alone biomass-based hybrid power system for the energy demand of a rural region containing poultry farms. Besides solar and wind energy, energy storage integration is evaluated regarding overall technical-environmental-economic performance, considering the actual manure potential using HOMER Pro. In addition, sensitivity analyses are performed, considering the estimated load and inflations using an artificial neural network method. Using biomass and solar hybrid options offers more autonomous, environmentally friendly, and economic advantages. Biomass-based hybrid power system with solar energy reduced net present cost by around 12% and increased renewable fraction by 7%, and grid-connected options can provide 88.9% renewable fraction. In addition, the energy storage integration increased renewable fraction by around 10% and reduced excess energy by 16%. The proposed biomass-based hybrid power system achieves cost-effective sizing of solar or wind-based hybrid systems, empowers the reliability of renewable energy and presents good consistency of decarbonization targets.

ispartof: JOURNAL OF ENERGY CHEMISTRY vol:70 pages:492-501 status: published

The main outdoor factors that reduce the efficiency of the photovoltaic (PV) panel are the reflection and refraction of light, dirt, dust, and organic waste accumulating on the panel surface. In this article, an antireflection, self-cleaning coating was applied on the PV panel cover glass with a new method. With the coating, the surface has been given a hydrophobic feature. As a coating method, a 3-D printer has not been seen in the literature and used as a new method. The electrospinning method has also been tried as an alternative method. Solutions in different combinations were developed using polylactic acid or polymethylmethacrylate polymer, chloroform ($\text{CHCl}_3$) as a solvent, and silicon dioxide ($\text{SiO}_2$) and titanium dioxide ($\text{TiO}_2$) nanoparticles as primary materials in a modified 3-D printer for bioprinting. Five PV panels were obtained by applying different 3-D parameters from three solutions, which have the best results. Coating thicknesses are in the range of 3.12-8.47 mu m. Coated and uncoated PV panels were tested in outdoor conditions for ten-day periods. The power outputs of the PV panels were measured, and their ten-day average efficiency was presented. According to the results, the highest efficiency increase is 8.7%. The highest light transmittance is 88.2% at 550 nm. In addition, hydrophobic properties were observed on all surfaces and the water contact angle was measured as 96.18 degrees.

Injecting hydrogen into the natural gas network to reduce CO2 emissions in the EU residential sector is considered a critical element of the zero CO2 emissions target for 2050. Burning natural gas and hydrogen mixtures has potential risks, the main one being the flame flashback phenomenon that could occur in home appliances using premixed laminar burners. In the present study, two-dimensional transient computations of laminar CH4- + air and CH4 + H-2 + air flames are performed with the open-source CFD code OpenFOAM. A finite rate chemistry based solver is used to compute reaction rates and the laminar reacting flow. Starting from a flame stabilized at the rim of a cylindrical tube burner, the inlet bulk velocity of the premixture is gradually reduced to observe flashback. The results of the present work concern the effects of wall temperature and hydrogen addition on the flashback propensity of laminar premixed methane-hydrogen-air flames. Complete sequences of flame dynamics with gradual increases of premixture velocity are investigated. At the flame flashback velocities, strong oscillations at the flame leading edge emerge, causing broken flame symmetry and finally flame flashback. The numerical results reveal that flashback tendency increase with increasing wall temperature and hydrogen addition rate. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

The interaction between wind turbine wakes and atmospheric turbulence is characterised by complex dynamics. In this study, two major components of the atmospheric boundary layer dynamics have been isolated, namely, the mean velocity profile shear and the thermal stratification, to examine their impact on the near-wake development by undertaking a series of highly resolved large-eddy simulations. Subsequently, instantaneous flow fields are extracted from the simulations and used to conduct Fourier analysis and proper orthogonal decomposition (POD) and compute the mean kinetic energy fluxes by different POD modes to better understand the tip-vortex instability mechanisms. Our findings indicate that shear can significantly affect the breakup of the wind turbine tip-vortices as well as the shape and stable length of the wake, whereas thermal stratification seems to only have limited contribution to the spatial development of the near-wake field. Finally, our analysis shows that the applied perturbation frequency determines the tip-vortex breakup location as it controls the onset of the mutual inductance instability.

ispartof: ADVANCED ENERGY MATERIALS status: Published online

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in 2019, cut the epoch that will make profound fluctuates in the history of the world in social, economic, and scientific fields. Urgent needs in public health have brought with them innovative approaches, including diagnosis, prevention, and treatment. To exceed the coronavirus disease 2019 (COVID-19) pandemic, various scientific authorities in the world have procreated advances in real time polymerase chain reaction (RT-PCR) based diagnostic tests, rapid diagnostic kits, the development of vaccines for immunization, and the purposing pharmaceuticals for treatment. Diagnosis, treatment, and immunization approaches put forward by scientific communities are cross-fed from the accrued knowledge of multidisciplinary sciences in health biotechnology. So much so that the pandemic, urgently prioritized in the world, is not only viral infections but also has been the pulsion in the development of novel approaches in many fields such as diagnosis, treatment, translational medicine, virology, microbiology, immunology, functional nano- and bio-materials, bioinformatics, molecular biology, genetics, tissue engineering, biomedical devices, and artificial intelligence technologies. In this review, the effects of the COVID-19 pandemic on the development of various scientific areas of health biotechnology are discussed.

The expected growth in wind energy capacity requires efficient and accurate models for wind farm layout optimization, control, and annual energy predictions. Although analytical wake models are widely used for these applications, several model components must be better understood to improve their accuracy. To this end, we propose a Bayesian uncertainty quantification framework for physics-guided data-driven model enhancement. The framework incorporates turbulence-related aleatoric uncertainty in historical wind farm data, epistemic uncertainty in the empirical parameters, and systematic uncertainty due to unmodelled physics. We apply the framework to the wake expansion parameterization in the Gaussian wake model and employ historical power data of the Westermost Rough offshore wind farm. We find that the framework successfully distinguishes the three sources of uncertainty in the joint posterior distribution of the parameters. On the one hand, the framework allows for wake model calibration by selecting the maximum a posteriori estimators for the empirical parameters. On the other hand, it facilitates model validation by separating the measurement error and the model error distribution. In addition, the model adequacy and the effect of unmodelled physics are assessable via the posterior parameter uncertainty and correlations. Consequently, we believe that the Bayesian uncertainty quantification framework can be used to calibrate and validate existing and upcoming physics-guided models.

The Thrace Basin in northwestern Turkey is a deep Eocene–Oligocene hydrocarbon-bearing sedimentary basin. The basin has potential for geothermal energy utilization in the future due to its favorable geological conditions. In this study, we combined the available bottom hole temperature (BHT) data from 70 points with the thermal conductivity and radiogenic heat productions of the basin formations, and generated a detailed thermal model of the northern part of the basin. For heat flow determinations from the BHT data, we applied Bullard’s thermal resistance method on formation thermal conductivities and thicknesses. The results give an average surface heat flow of 65.8 ± 11.3 mW/m2. We obtained high heat flow values (75–80 mW/m2) in the eastern and western sides, and the central part of the study area. These relatively high heat flow values can be explained by the combined effect of basement topography and the variations in the radiogenic heat production of the basement rocks. The calculated subsurface temperatures in selected hydrocarbon fields vary in the range of 45–64°C at 1km depth, 99–136°C at 3km depth, and 155–208°C at 5km depth as a result of local variations of the surface heat flow and formation thermal resistances. These variations in subsurface temperatures can have significant effects on the cost of geothermal energy production in future.

We synthesized molecular weight-controlled and fluorine-containing PAEs (MWCPAEs) using decafluorobiphenyl (DFBP), 2-bis (4-hydroxyphenyl) propane (Bis A), and 2,2-Bis (4-hydroxyphenyl) hexafluoropropane (Bis AF). Later, commercially available PEEK and the MWCPAEs were sulfonated (SPEEK and SMWCPAE) and blended to fabricate blend membranes (BMs). All BMs have been prepared by solution casting method in 5 wt%-20 wt% concentrations using N,N-dimethylacetamide. The effects of chemical structures, sulfonation levels, MW and compositions on the membrane properties are discussed. We obtained miscible and mechanically compatible BMs. The highest proton conductivity (238.9 mS/cm) was determined for SPEEK70/S-DFBP-Bis-A based blend membrane (Mw: 48.355, 5wt. %). All chemical, mechanical, thermal, and hydrolytic properties of the BMs are comparable with, or better than, that of Nafion. We suggest that designing polymeric structures with desired MWs and sulfonation levels may enable enhanced properties and can help to design materials with on demand properties.

Organic semiconductor photocatalysts for the production of solar fuels are attractive as they can be synthetically tuned to absorb visible light while simultaneously retaining suitable energy levels to drive a range of processes. However, a greater understanding of the photophysics that determines the function of organic semiconductor heterojunction nanoparticles is needed to optimize performance. Here, we show that such materials can intrinsically generate remarkably long-lived reactive charges, enabling them to efficiently drive sacrificial hydrogen evolution. Our optimized hetereojunction photocatalysts comprise the conjugated polymer PM6 matched with Y6 or PCBM electron acceptors, and achieve external quantum efficiencies of 1.0% to 5.0% at 400 to 900 nm and 8.7% to 2.6% at 400 to 700 nm, respectively. Employing transient and operando spectroscopies, we find that the heterojunction structure in these nanoparticles greatly enhances the generation of long-lived charges (millisecond to second timescale) even in the absence of electron/hole scavengers or Pt. Such long-lived reactive charges open potential applications in water-splitting Z-schemes and in driving kinetically slow and technologically desirable oxidations.

For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of $$3.05\,\hbox {m}/\hbox {s}$$ 3.05 m / s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

Biomass gasification technology is a promising process to produce a stable gas with a wide range of applications, from direct use to the synthesis of value-added biochemicals and biofuels. Due to the high capital/operating costs of the technology and the necessity for prudent management of thermal energy exchanges in the biomass gasification process, it is important to use advanced sustainability metrics to ensure that environmental and other sustainability factors are addressed beneficially. Consequently, various engineering techniques are being used to make decisions on endogenous and exogenous parameters of biomass gasification processes to find the most efficient, viable, and sustainable operations and conditions. Among available approaches, exergy methods have attracted much attention due to their scientific rigor in accounting for the performance, cost, and environmental impact of biomass gasification systems. Therefore, this review is devoted to critically reviewing and numerically scrutinizing the use of exergy methods in analyzing biomass gasification systems. First, a bibliometric analysis is conducted to systematically identify research themes and trends in exergy-based sustainability assessments of biomass gasification systems. Then, the effects of biomass composition, reactor type, gasifying agent, and operating parameters on the exergy efficiency of the process are thoroughly investigated and mechanistically discussed. Unlike oxygen, nitrogen, and ash contents of biomass, the exergy efficiency of the gasification process is positively correlated with the carbon and hydrogen contents of biomass. A mixed gasifying medium (CO2 and steam) provides higher exergy efficiency values. The downdraft fixed-bed gasifier exhibits the highest exergy efficiency among biomass gasification systems. Finally, opportunities and limitations of exergy methods for analyzing sustainability aspects of biomass gasification systems are outlined to guide future research in this domain.

The present study aims to investigate the origin, type, thermal maturity and hydrocarbon generation potential of organic matter and paleo-depositional environment of the Early Paleocene (Danian) Hangu Formation outcropped in the Kala-Chitta Range of Northwest Pakistan, Eastern Tethys. Organic-rich shale and coal intervals were utilized for geochemical analyses including TOC (total organic carbon) and Rock–Eval pyrolysis coupled with carbon (δ13Corg) and nitrogen (δ15Norg) stable isotopes. The organic geochemical results showed that the kerogen Type II (oil/gas prone) and Type III (gas prone) dominate the investigated rock units. The TOC (wt%) and S2 yield indicate that the rock unit quantifies sufficient organic matter (OM) to act as potential source rock. However, the thermal maturity Tmax°C marks the over maturation of the OM, which may be possibly linked with the effect attained from nearby tectonically active Himalayan Foreland Fold-and-Thrust Belt system and associated metamorphosed sequences. The organic geochemical analyses deciphered indigenous nature of the OM and resultant hydrocarbons. The δ13Corg and δ15Norg stable isotopic signatures illustrated enrichment of the OM from both marine and terrestrial sources accumulated into the Hangu Formation. The Paleo-depositional model established using organic geochemical and stable isotopic data for the formation supports its deposition in a shallow marine proximal inner shelf environment with prevalence of sub-oxic to anoxic conditions, a scenario that could enhance the OM preservation. Overall, the formation holds promising coal and shale intervals in terms of organic richness, but due to relatively over thermal maturation, it cannot act as an effective source rock for liquid hydrocarbon generation and only minor amount of dry gas can be expected. In implication, the results of this study suggest least prospects of liquid hydrocarbon generation potential within Hangu Formation at studied sections.

Understanding of the protonic defect transport mechanism in Ba(Ce,Zr)O3 perovskite oxides and defining the appropriate temperature range for ionic conductivity are fundamental to material design and application as electrolytes for solid oxide fuels and electrolyzer cells, isotopic separation membranes, and hydrogen sensors. Structural features of the material, and lattice distortions and proton diffusion are key factors that define the protonic conduction. The crystal structure of protonated and deuterated BaCe0.4Zr0.4Y0.2O3-? (BCZY) perovskite and its correlation with protonic transport was studied by in situ neutron powder diffraction (NPD) and complementary thermogravimetry (TG), quasi-elastic neutron scattering (QENS) and isotope exchange depth profiling (IEDP) techniques. A second order phase transition from rhombohedral to cubic symmetry takes place at intermediate temperatures (400-600 °C). Dynamic measurements of NPD allowed the detection of the temperature of the phase transition for BCZY at around 520 °C. Crystallographic and microstructural parameters, including deuterium occupancy and anisotropic thermal parameters, were determined from high resolution NPD data. The deuterium (and oxygen) occupancy for pre-hydrated BCZY was at its maximum at low temperature and decreased at temperatures greater than 400 °C, even through the phase transition and beyond 600 °C. By contrast, proton diffusion increased with temperature above the phase transition. The combination of both effects, i.e., deuterium content and diffusion coefficient, explains the previous results showing that the proton conductivity dominates the ionic conductivity over the oxygen vacancy mechanism until 600 °C. The phase transition is mainly related to oxygen sublattice relaxation and does not impact the protonic transport mechanism.

The use of dopants is an effective strategy to improve ZnO electron transport layers (ETLs) for application in solution-processed opto-electronic devices. Mg, in particular, has shown significant promise as a dopant and Mg-doped ZnO ETLs have been used to enhance the performance of a number of solution-processed light-emitting diodes and photovoltaics. However, such a use of Mg to dope ZnO ETLs for organic photovoltaics (OPVs) has remained limited, and only investigated in connection with annealing temperatures of 300 °C or so. In this work, with a view to increase sustainability and compatibility with soft and flexible or foldable substrates, we present OPVs incorporating Mg-doped ZnO ETLs fabricated with annealing temperatures of 150 °C. We demonstrate that Mg doping (≈1% at%) in the ZnO ETL reduces leakage currents and recombination losses in our devices, whilst leaving the morphology of the active layer and the work function of the ETL unaffected. A concomitant increase of the short circuit current density, open circuit voltage and fill factor is also observed, thereby leading to a relative enhancement of the power conversion efficiency by ≈18% compared to devices prepared using undoped ZnO.

Emerging technologies in solar energy will be critical in enabling worldwide society in overcoming the present energy challenges and reaching carbon net zero. Inefficient and unstable charge transport materials limit the current emerging energy conversion and storage technologies. Low-dimensional coordination polymers represent an alternative, unprecedented class of charge transport materials, comprised of molecular building blocks. Here, we provide a comprehensive study of mixed-valence coordination polymers from an analysis of the charge transport mechanism to their implementation as hole-conducting layers. CuII dithiocarbamate complexes afford morphology control of 1D polymer chains linked by (CuI2X2) copper halide rhombi. Concerted theoretical and experimental efforts identified the charge transport mechanism in the transition to band-like transport with a modeled effective hole mass of 6me. The iodide-bridged coordination polymer showed an excellent conductivity of 1 mS cm−1 and a hole mobility of 5.8 10−4 cm2 (V s)−1 at room temperature. Nanosecond selective hole injection into coordination polymer thin films was captured by nanosecond photoluminescence of halide perovskite films. Coordination polymers constitute a sustainable, tunable alternative to the current standard of heavily doped organic hole conductors.

In situ phosphorus (P)-doped polycrystalline silicon (poly-Si) films by low pressure chemical vapor deposition (LPCVD) were studied in this work for the fabrication of poly-Si passivating contacts. In situ doping was targeted for enabling the full potential of the high-throughput LPCVD technique, as it could allow leaner fabrication of industrial solar cells featuring poly-Si passivating contacts than the more common ex situ doping routes. By careful optimization of the deposition temperature and the flows of the carrier gas (H-2) and the dopant precursor (PH3), high doping in the poly-Si layers was achieved with active P concentrations up to 1.3.10(20) cm(-3) . While reduction in the deposition rate (r(dep)) and thus in the throughput is a known problem when growing in situ P-doped films by LPCVD, this reduction could be limited, and the resulting r(dep) was equal to 0.078 nm/s. The developed poly-Si films were characterized both structurally and in terms of their passivation potential in poly-Si contacts. The latter yielded recombination current densities down to 1.5 fA/cm(2) in passivated (J(0, p)) and 25.6 fA/cm(2) in screen-printing metallized (J(0, m)) regions on saw-damage removed (SDR) Cz-Si surfaces, accompanied by a contact resistivity (rho(c,m)) of 4.9 m Omega.cm(2). On textured Cz-Si surfaces, the corresponding values were J(0, p) = 3.5 fA/cm(2), J(0,m )= 56.7 fA/cm(2), and rho(c,m) = 1.8 m Omega.cm(2). Optical impact of the developed poly-Si films was also assessed and a short circuit density loss of 0.41 mA/cm(2) is predicted per each 100 nm of poly-Si applied at the rear side of solar cells. The authors would like to acknowledge Rajiv Sharma from KU Leuven for his help with the interfacial oxide development, Sukhvinder Singh and Patrick Choulat from Imec for their help with the contact resistivity measurements and sample fabrication, Thomas Nuytten and Stefanie Sergeant from Imec for the Raman spectroscopy measurements, Bastien Douhard and Mustafa Ayyad from Imec for SIMS measurements, Maxim Korytov, Laura Nelissen, and Patricia van Marcke from Imec for the TEM specimen preparation and measurements, and Janusz Bogdanowicz from Imec for his help with the analysis of the Hall measurement data. This work was supported by the European Union’s Horizon2020 Programme for research, technological development, and demonstration [grant number 857793]; and by the Kuwait for the Advancement of Sciences [grant number CN18-15EE-01].

Non-equilibrium thermodynamics describe the current–voltage characteristics of electrochemical devices. For conventional electrode–electrolyte interfaces, the local activation overpotential is used to describe the electrostatic potential step between the two materials as a current is generated. However, the activation overpotential for the metal/mixed ionic-electronic conducting (MIEC) composite electrodes studied in this work originates at the MIEC–gas interface. Moreover, we have studied the effects of non-equilibrium on the electrostatic surface potential and evaluated its influence over electrode kinetics. By investigating two phase (2PB) and three phase boundary (3PB) reactions at the Ni/Ce1−xGdxO2−δ (Ni/CGO) electrode, we have demonstrated that the driving force for coupled ion-electron transfer is held at the CGO–gas interface for both reaction pathways. We also determined that the rate of coupled ion-electron transfer via the 3PB scales with the availability of free sites on the metallic surface, revealing a Sabatier-like relationship with regards to the selection of metallic phases. Finally, we demonstrated how the theory of the electrostatic surface potential can be applied to other systems outside of the well-studied H2/H2O electrode environment. These findings therefore provide an insight into the design of future electrode structures for a range of electrochemical devices.

© 2023 Elsevier LtdBiomass is the most widespread among renewable energy sources and offers many advantages. However, the heterogeneous structure of biomass brings many disadvantages. Therefore, characterization of thermal degradation of biopolymeric structures in biomass such as hemicellulose (HC), cellulose (CL), and lignin (LN) is very important for the efficiency of any biomass-based thermal process. On the other hand, the characterization of these biopolymers requires various experimental procedures that consume resources and time. Artificial neural networks (ANN) as a machine learning approach provide a remarkable opportunity to identify patterns in the complex structure of biomass fuels and their thermochemical degradation processes. In this study, a new model was developed for the first time to generate differential thermogravimetric analysis (DTG) curves for HC, CL and LN in biomass using proximate analysis results of raw biomass. DTG curves were evaluated using a ANN model developed with the open-source \"TensorFlow\" library in Python software. ANN model performed excellently with R2 values above 0.998. The results show that the newly developed model can estimate the thermal degradation for any temperature, so that biopolymer fractions in the degraded biomass can be calculated immediately, which has not been reported before.

ispartof: RENEWABLE & SUSTAINABLE ENERGY REVIEWS vol:173 status: published