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In this study, CO₂ conversion to acetate and CH₄ was achieved in a flow-through laboratory-scale microbial electrosynthesis (MES) cell composed of a 3D conductive polylactic acid (cPLA) lattice cathode with electrodeposited metal electrocatalyst coatings. The MES cell with a bare cPLA cathode showed the poorest performance with the lowest H₂ and CH₄ production rates and low Coulombic efficiency. This was ascribed to a poor electrocatalytic activity of cPLA towards H₂ production and high electrode resistivity. When the cPLA electrode was modified with metal coatings, the CH₄, acetate and H₂ production rate increased significantly, with the following trend: cPLA < Ni < NiFe < NiFeMn. The better performance of the metal-coated cPLA in terms of CH₄ production was attributed to the lower electrical resistance, enhanced H₂ production and enhanced electron transfer between the cathode and the biofilm. At the cell potential of 2.8 V, the best-performing NiFeMn cPLA cathode showed stable production of CH₄ (50 ± 6 mL d⁻¹), acetate (185 ± 27 mg d⁻¹), and H₂ (545 ± 175 mL d⁻¹) at close to 100% Coulombic efficiency.

Ranked as the major energy-consuming sector, the building industry continuously introduces enhanced energy-management systems towards more energy efficiency. Despite technological progress, high amounts of resources are still wasted worldwide due to the wrong usage of energy systems in existing building stock. As a response, this paper proposes a recommendation system that is based on information and communication technologies and that provides building users with hands-on executable recommendations to reduce their energy consumption. Indeed, because of their lack of energy awareness and knowledge, people may need guidance in their daily usage of a building to change their energy behaviour and to save energy. For that purpose, the recommendation system analyses building operation data in real time to identify energy wastes as well as suitable energy conservation measures that shall help in saving energy. One main challenge is to provide a highly scalable solution that can be easily applied in a wider range of buildings, thus enabling resource saving at a large scale or even worldwide. For that purpose, the system relies on a model-based expert system for easy adaptation in any building regardless of its type, size and usage.

This work demonstrated the promise of using industrial-grade sugar syrups derived from corn and wood, i.e., high fructose corn syrup (HFCS), glucose corn syrup (GCS) and wood-based sugar (TMP-Bio Sugar), as cheaper and competitive feedstocks for 5-HMF production using niobium phosphate as a heterogeneous solid acid catalyst in a biphasic continuous-flow tubular reactor. 5-HMF yield as high as 53.1% with 100% sugar (glucose and fructose) conversion was obtained from catalytic dehydration of HFCS-90 (containing 90 wt% fructose) at 150 °C, with feed concentration of 200 mg/ml (glucose and fructose) and aqueous to organic phase ratio of 1:5 (v/v). Catalyst stability with time was tested over 20 h of continuous-time on stream, and the reusability of the catalyst was studied after in-situ regeneration of the used catalyst by calcination in the air for removing the deposited humins and coke on the surface of the catalyst particles. The regenerated catalyst showed good activity with almost constant selectivity, although at lower glucose conversion and reduced 5-HMF yield compared to the fresh catalyst, indicating that the in-situ regeneration process could recover a part of the acid sites on the catalyst surface. The produced humins during the reaction were characterized by Fourier transform infrared spectrometry (FT-IR), thermogravimetric analysis (TGA) and elemental analysis (CHNS). The results showed high aromaticity and the presence of a high degree of unsaturated compounds in the structure of humins.

Full list of authors: Harra, Louise; Andretta, Vincenzo; Appourchaux, Thierry; Baudin, Frédéric; Bellot-Rubio, Luis; Birch, Aaron C.; Boumier, Patrick; Cameron, Robert H.; Carlsson, Matts; Corbard, Thierry; Davies, Jackie; Fazakerley, Andrew; Fineschi, Silvano; Finsterle, Wolfgang; Gizon, Laurent; Harrison, Richard; Hassler, Donald M.; Leibacher, John; Liewer, Paulett; Macdonald, Malcolm; Maksimovic, Milan; Murphy, Neil; Naletto, Giampiero; Nigro, Giuseppina; Owen, Christopher; Martínez-Pillet, Valentín; Rochus, Pierre; Romoli, Marco; Sekii, Takashi; Spadaro, Daniele; Veronig, Astrid; Schmutz, W.--This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/., A mission to view the solar poles from high helio-latitudes (above 60°) will build on the experience of Solar Orbiter as well as a long heritage of successful solar missions and instrumentation (e.g. SOHO Domingo et al. (Solar Phys. 162(1-2), 1–37 1995), STEREO Howard et al. (Space Sci. Rev. 136(1-4), 67–115 2008), Hinode Kosugi et al. (Solar Phys. 243(1), 3–17 2007), Pesnell et al. Solar Phys. 275(1–2), 3–15 2012), but will focus for the first time on the solar poles, enabling scientific investigations that cannot be done by any other mission. One of the major mysteries of the Sun is the solar cycle. The activity cycle of the Sun drives the structure and behaviour of the heliosphere and of course, the driver of space weather. In addition, solar activity and variability provides fluctuating input into the Earth climate models, and these same physical processes are applicable to stellar systems hosting exoplanets. One of the main obstructions to understanding the solar cycle, and hence all solar activity, is our current lack of understanding of the polar regions. In this White Paper, submitted to the European Space Agency in response to the Voyage 2050 call, we describe a mission concept that aims to address this fundamental issue. In parallel, we recognise that viewing the Sun from above the polar regions enables further scientific advantages, beyond those related to the solar cycle, such as unique and powerful studies of coronal mass ejection processes, from a global perspective, and studies of coronal structure and activity in polar regions. Not only will these provide important scientific advances for fundamental stellar physics research, they will feed into our understanding of impacts on the Earth and other planets’ space environment. © The Author(s) 2021., Open Access funding provided by ETH Zurich., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

International audience; Ozone, PM10 and PM2.5 concentrations over Paris, France and Stockholm, Sweden were modeled at 4 and 1 \unit{km} horizontal resolutions respectively for the present and 2050 periods employing decade-long simulations. We account for large-scale global climate change (RCP-4.5) and fine resolution bottom-up emission projections developed by local experts and quantify their impact on future pollutant concentrations. Moreover, we identify biases related to the implementation of regional scale emission projections over the study areas by comparing modeled pollutant concentrations between the fine and coarse scale simulations. We show that over urban areas with major regional contribution (e.g., the city of Stockholm) the bias due to coarse emission inventory may be significant and lead to policy misclassification. Our results stress the need to better understand the mechanism of bias propagation across the modeling scales in order to design more successful local-scale strategies. We find that the impact of climate change is spatially homogeneous in both regions, implying strong regional influence. The climate benefit for ozone (daily average and maximum) is up to -5 % for Paris and -2 % for Stockholm city. The joined climate benefit on PM2.5 and PM10 in Paris is between -10 and -5 % while for Stockholm we observe mixed trends up to 3 % depending on season and size class. In Stockholm, emission mitigation leads to concentration reductions up to 15 % for daily average and maximum ozone and 20 % for PM and through a sensitivity analysis we show that this response is entirely due to changes in emissions at the regional scale. On the contrary, over the city of Paris (VOC-limited photochemical regime), local mitigation of NOx emissions increases future ozone concentrations due to ozone titration inhibition. This competing trend between the respective roles of emission and climate change, results in an increase in 2050 daily average ozone by 2.5 % in Paris. Climate and not emission change appears to be the most influential factor for maximum ozone concentration over the city of Paris, which may be particularly interesting in a health impact perspective.

Advanced transportation biofuels have been the focus of intensive development since the early 2000s, and gasification in combination with synthesis technologies represents a flexible production pathway to deliver fuels for heavy-duty transport sectors that are difficult to electrify. This article is related to the pilot-scale development of a process concept aiming to smaller-scale production plants than are feasible with fluidized-bed gasifiers. Five test weeks with a total gasification time of 347 hours were realized at a pilot plant that consisted of the pressurized staged fixed-bed gasifier, raw gas cooling to 500–600 °C, filtration with robust metal filters, and catalytic reforming of tars and methane. The gasifier combined an updraft primary stage and a catalytically enhanced secondary stage where most of the updraft tars were decomposed. The tar content of the product gas, 2–12 g/m3, was of the same order of magnitude as determined previously for fluidized-bed gasifiers. Consequently, similar filtration and reforming methods could be successfully applied. After the reformer, the contents of C2-hydrocarbon gases and high-molecular-weight tars were negligible. Esa Kurkela,* Minna Kurkela, Ilkka Hiltunen Pilot-scale development of pressurized fixed-bed gasification for synthesis gas production from biomass residues Biomass Conversion and Biorefinery https://doi.org/10.1007/s13399-021-01554-2

This paper proposes a semantic framework for Business Model evaluation and its application to a real case study in the context of smart energy and sustainable mobility. It presents an ontology based representation of an original business model and examples of inferential rules for knowledge extraction and automatic population of the ontology. The real case study belongs to the GreenCharge European Project, that in these last years is proposing some original business models to promote sustainable e-mobility plans. An original OWL Ontology contains all relevant Business Model concepts referring to GreenCharge’s domain, including a semantic description of TestCards, survey results and inferential rules.

The drive to miniaturize power electronics motivates investigation into alternative passive component technologies such as piezoelectrics, which offer fundamentally higher power density and efficiency capabilities at small scales compared to magnetics. Piezoelectric transformers (PTs) have seen application in dc-dc converters, but these designs typically require additional magnetics for competitive efficiency. In this work, we systematically enumerate isolated and non-isolated dc-dc converter topologies and switching sequences capable of efficiently utilizing PTs as their only energy storage components. The proposed switching sequences maintain high-efficiency behaviors (e.g., zero voltage switching (ZVS), all-positive instantaneous power transfer, and minimal charge circulation) across wide voltage gain and load ranges. We present techniques for deriving these switching sequences’ ZVS regions, estimating PT efficiency, and solving for periodic steady state switching times; these offer insights for comparing and implementing design options. We then verify our analyses in a 180-500 V experimental prototype based on a commercially-available PT, which demonstrates significant efficiency gain through a proposed implementation.

Recently, IGCTs have shown a great potential for the soft-switching dc transformer applications based on LLC resonant converter. The zero-voltage switching that is present in this converter topology enables an operation of IGCTs without clamping circuit and with significantly higher switching frequencies, while maintaining the superiorly low conduction losses. The high voltage and current ratings of the IGCTs make them a preferred choice for an efficient bulk power transmission. This paper shows how gate units for IGCTs can be optimized for this soft-switching application. It presents a simplification of the driving topology and the design process for high switching frequencies. This results in low power consumption and a very small size of the gate unit. The prototype of the gate unit is built and experimentally validated in a 2.5 kV 0.75 kA resonant operation of the IGCT.

In this research, canola meal was densified using bio-additives including alkali lignin, glycerol, and l -proline. The fuel pellet's formulation was optimized. The best fuel pellet demonstrated relaxed density and mechanical durability of 1015 kg/m3 and 99.0%, respectively. Synchrotron-based computer tomography technique indicated that lack of water in pellet formulation resulted in a twofold increase in pellet porosity. Thermogravimetric analysis showed that ignition temperature (240 °C) and burn-out temperature (640 °C) for fuel pellet were smaller than those for coal. Impacts of process parameters were evaluated on the quality of the gas product obtained from pellet's steam gasification and hydrothermal gasification. The gasification experiments showed production of untreated syngas with a suitable range of H2/CO molar ratio (1.3–1.6) using steam gasification. Hydro-thermal gasification produced a larger molar ratio of H2/CO (1.8–51.2) for the gas product. Modeling of pellet's steam gasification showed an excellent agreement with experimental results of steam gasification.

Canola meal is a low-value agricultural residue obtained after oil extraction from canola, the utilization of which requires further attention. On the other hand, plastic waste disposal is also another leading issue that creates severe environmental challenges. Supercritical water gasification is considered an environmentally friendly technology to produce hydrogen from plastic residues and organic wastes. This study deals with hydrothermal co-gasification of canola meal and plastic wastes (i.e., low-density polyethylene) while exploring the influence of temperature (375–525°C), residence time (15–60 min) and plastic-to-biomass ratio (0:100, 20:80, 50:50, 80:20 and 100:0) on hydrogen yield. Maximum hydrogen yield (8.1 mmol/g) and total gas yield (17.9 mmol/g) were obtained at optimal temperature and residence time of 525°C and 60 min, respectively. A change in the gas yield with variable plastic-to-biomass ratio showed synergistic effects between both feedstocks. The trend of catalytic performance towards improving hydrogen yield was in the following order: WO3–TiO2 (18.5 mmol/g) > KOH (16.9 mmol/g) > TiO2 (9.5 mmol/g) > ZrO2 (7.8 mmol/g) > WO3–ZrO2 (7.4 mmol/g).

Funding Information: This research has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement (EnergyMatching project number 768766), and J. Gust. Richert foundation in Sweden (grant number: 2020-00586). Funding Information: This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement (EnergyMatching project number 768766 ), and J. Gust. Richert foundation in Sweden (grant number: 2020-00586 ). Publisher Copyright: © 2021 The Author(s) Peer-to-peer (P2P) energy sharing among neighboring households is a promising solution to mitigating the difficulties of renewable power (such as solar Photovoltaics (PV)) penetration on the power grid. Until now, there is still a lack of study on the impacts of future climate change on the P2P energy trading performances. The future climate change will cause variances in the renewable energy production and further lead to changes in the economic performances of households with various energy uses and affect the decision making in PV ownership and pricing strategies. Being unaware of these impacts could potentially hinder the P2P energy sharing application in practice. To bridge such knowledge gap, this paper conducts a systematic investigation of the climate change impacts on the energy sharing performance in solar PV power shared communities. The future weather data is generated using the Morphine method, and an agent-based modeling method is used for simulating the energy trading behaviors of households. Four comparative scenarios of different PV ownerships and pricing strategies are designed. The detailed energy trading performances (including the PV power self-sufficiency, cost saving, revenues, and compound annual growth rate) for the four comparative scenarios are analyzed under both the present and future climates and compared. The study results of a building community located in Sweden show that the future climate change is more beneficial to large energy use households while less beneficial to small households. High price of energy trading can improve the fairness of the economic performances in the community, especially when some of the households do not have any PV ownership. This study can help understand the future climate impacts on the energy sharing performances of building communities, which can in turn guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications.

Powertrain electrification has been proven as an effective solution to public concerns about fossil fuel usage and carbon emissions. As a midterm technology from conventional internal combustion engine vehicles to electric vehicles, hybrid electric vehicles have received wide research attention from industry and academics alike and are sharing an increasing percentage of vehicles in the market. As a crucial component in hybrid powertrains, the internal combustion engine has important impacts on vehicle performance. Recent years have witnessed tremendous effort towards hybrid electric vehicle-specific engine technologies. Low temperature combustion concept, alternative fuels, over-expansion Atkinson cycle, and waste heat recovery technique provide the most promising solutions to clean and efficient hybrid-specific engines. In this paper, recent progress in these four technologies on hybrid powertrain platforms is reviewed comprehensively. Working principles, influencing factors, benefit potentials, advantages, and disadvantages of each technology are discussed in detail. Although these technologies present improvement in fuel economy and emissions, there are several issues as well. Challenges and concerns associated with system complexity, restricted operating conditions, controls, cost, safety, etc., are specified, and corresponding recommendations are provided from technology level to powertrain level. Future research opportunities are suggested at the end to encourage more research activities in this area.

This article proposes a supervised learning approach for centralized localization of faults in microgrids with radial configuration that can operate in grid-connected or islanded mode. The key concept is to identify faults by learning and analyzing the features of voltage and current disturbances detected by a microgrid central protection unit. Two algorithms are developed that determine fault indices and transient features for simulation-based training, classification, and backup protection purposes. The proposed data-driven approach is effective under high penetration of distributed energy resources (DERs), and is robust under microgrid topology variations. Moreover, it requires few sensors (two for radial structure) and is easy to implement, yet provides high degree of reliability. The performance and accuracy of the developed approach are verified through extensive simulations of low-voltage microgrids that incorporate different types of DERs, including wind and solar photovoltaic systems.

Ejector systems are receiving considerable attention due to their simplicity, lower maintenance requirements, use of low grade heat, longer lifespan and low cost. In this paper an improved model to predict the performance of an ejector refrigeration system under both the critical and subcritical modes of operation was developed and validated. The model predicts ejector performance more precisely compared to studies following the same modelling approach in the literature. Using the developed model, performances with environmentally benign refrigerants, including R1233zd(E), HFO1336mzz(Z), R1234ze(Z), R600, RE245fa2, and RE245fa2 as alternatives to R141b and R245fa were investigated. For ejector area ratios between 4.45 to 12.98, evaporator temperatures between 0oC and 16oC and condenser temperatures between 20 and 40oC, the optimal performance of the ejector system was determined. Results show that for each refrigerant, higher area ratios give higher coefficients of performance, but require higher generator temperatures for better critical condensing temperatures. R600 showed the best performance followed by R1234Ze(Z) and R1233Zd(E) for the entire range of parameters considered. Results further show that there is an optimum generator temperature at each area ratio that maximizes performance. The optimal generator temperature increases as the area ratio and the condensing temperature increase. An alternative and more convenient approach to optimize ejector performance has been suggested in this work.

The use of nano phase change material in thermal energy storage applications appears promising, but the often-poor performance and the lack of understanding of the heat transfer mechanisms interconnectedness remains a challenge and hinders their widespread integration. The existing numerical work has unveiled numerous impediments in predicting the actual melting behaviour. They rarely combine the effects of conduction enhancement, convection degradation, and latent heat reduction, due to inaccurate characterization of the thermophysical properties and the limitations of their model assumptions. In the present study, an enhanced numerical approach was developed to investigate the melting performance of xGnP-octadecane filled in a vertical cylindrical enclosure at different weight concentrations. The model results for the pure phase change material were compared and validated against the experimental data. The progression of the melting front, temperature probes, energy storage capacity and heat transfer rate of the nano phase change material were thoroughly evaluated. The current numerical observations demonstrate that the addition of nanoparticles improves, up to a critical concentration of 0.5wt%, the melting rate. The results showed that by adding 0.5wt% of xGnP in the base phase change material (octadecane), the melting rate decreases by 9.7% and the heat storage rate increases by 12.6%. However, at higher loadings, the heat transfer rate is deteriorated due to worsening of other thermophysical properties provoking the prevalence of viscous forces over natural convection and latent capacity. The system overall efficacy was found to be dependent on the net effects of relative changes of all thermophysical properties with nanoparticle concentration and temperature in the solid, so called mushy, and liquid zones. Finally, when characterizing nano phase change material, the thermal conductivity cannot be considered alone as a criterion for nano phase change material selection. A high thermal conductivity is needed for maximum heat absorption in thermal transport applications. Nevertheless, low viscosity, high latent heat and specific heat capacities are also essential to ensure a better thermal energy storage efficiency in terms of capacity and heat extraction/release rate.

Space heating and cooling represents 63% of total building energy demand. In the present study, the concept of concrete foundation piles was used as an underground storage medium. This system requires no additional drilling costs or space, unlike conventional boreholes. A lab-scaled experiment facility was designed to experimentally investigate the thermal response of a concrete pile during the charging and discharging processes. The amount of energy stored and released during each process was evaluated. A flow rate parametric study was also conducted to explore the effect of the laminar and turbulent flow behaviour. In order to complement the experimental study, an extensive CFD model was developed and compared with the experimental data. There was good agreement between the numerical and experimental results for each process at different flow rates. The results revealed that increasing the flow rate increases not only the heat rejection and extraction but also the storage efficiency. Keywords: borehole, energy pile, thermal storage, thermal response, ground source heat pump

This research presents a 3D geographic information systems (GIS) modeling approach at a fine spatiotemporal resolution to assess solar potential for the development of smart net-zero energy communities. It is important to be able to accurately identify the key areas on the facades and rooftops of buildings that receive maximum solar radiation, in order to prevent losses in solar gain due to obstructions from surrounding buildings and topographic features. A model was created in ArcGIS, in order to efficiently compute and iterate the hourly solar modeling and mapping process over a simulated year. The methodology was tested on a case study area located in southern Ontario, where two different 3D models of the site plan were analyzed. The accuracy of the work depends on the resolution and sky size of the input model. Future work is needed in order to create an efficient iterative function to speed the extraction process of the pixelated solar radiation data.

We present a study of the effect of gold nanoparticles (Au NPs) on TiO2 on charge generation and trapping during illumination with photons of energy larger than the substrate band gap. We used a novel characterization technique, photoassisted Kelvin probe force microscopy, to study the process at the single Au NP level. We found that the photoinduced electron transfer from TiO2 to the Au NP increases logarithmically with light intensity due to the combined contribution of electron-hole pair generation in the space charge region in the TiO2-air interface and in the metal-semiconductor junction. Our measurements on single particles provide direct evidence for electron trapping that hinders electron-hole recombination, a key factor in the enhancement of photo(electro)catalytic activity., This work was supported by the Office of Basic Energy Sciences (BES) of the U.S. Department of Energy (DOE) under contract DE-AC02-05CH11231 through the Structure and Dynamics of Materials Interfaces Program (FWP KC31SM) and the Molecular Foundry. M.L. acknowledges funds from Comunidad de Madrid (P2018/EMT-4308), a Fulbright grant PRX16/00564, and the MCIU-AEI-FEDERUE (RTI2018-096937-B-C22 and MAT2014-59772-C2-1-P). J.C. acknowledges financial support from Ministerio de Ciencia e Innovación (MICINN) and the European Union through the project PID2019-104272RB-C52. Also, Y.H. acknowledges financial support from MCIU through MAT2014-59772-C2-2- P and L.M. from EC through ERC-2013-SYG-610256. V.A.P.O. and M.B. acknowledge the financial support from EC through ERC CoG HyMAP 648319, MINECO PID2019- 106315RB-I00 and ENE2017-89170-R, ″Comunidad de Madrid″ and European Structural Funds (FotoArt-CM project S2018/NMT-4367) and Fundación Ramón Areces (Art-Leaf project). M.B. also thanks the Juan de la Cierva Incorporación contract (IJC2019042430-I). X.Z. was supported by the NSF-BSF 359 grant number 1906014. The authors thank Prof. Eran Edri, María Ujué González Sagardoy, and Judit Meseguer- Oliver for fruitful discussions and Asylum customer support for help with modifications of the AFM.

In order to have an immediate impact on building energy-related emissions, existing buildings need to be addressed. To inform policy and technical decisions, detailed mathematical models are required which can explore numerous building retrofit solutions and their energy and emissions performance . This paper describes the adaptation of a hybrid statistical and engineering-based model for residential building stock in Canada to analyze community-scale energy retrofits . The modelling domain includes both envelope and mechanical retrofits, as well as district renewable energy systems. This model is then applied to a case study of converting a community of fifty 1980’s vintage single-detached homes to achieve net-zero energy. The case study demonstrated that deep envelope retrofits and fuel switching from natural gas to electric heat pump systems reduce community energy demand by 69%. Saturating available roof area with photovoltaics was able to achieve net-zero balance. By considering net-zero at the community-scale, individual buildings that did not achieve net-zero were offset by net-exporting neighbours. Annual community emissions of the retrofit reduced emissions by 95%. The analysis also highlights the significant impact on electrical infrastructure due to solar generation and energy demand mismatch.

Atom probe tomography (APT) is a single-ion sensitive time-of-flight mass spectrometry method with near-atomic spatial resolution. In principle, it can be used to detect any chemical element, but so far hydrogen in the form of protium (1H) had to be largely excluded. This is owing to the residual H emitted from the stainless-steel chambers and in-vacuum parts commonly used in atom probe instrumentation. This residual H is then picked up in the APT experiment. In this paper, we show that by replacing the stainless-steel chamber and in-vacuum parts with titanium parts, this residual H can largely be removed, thus enabling the direct imaging of H using APT. We show that besides the drastic reduction of H, also other contaminants such as O, OH, and H2O are reduced by employing this instrument. In the current set-up, the instrument is equipped with high-voltage pulsing limiting the application to conductive materials.

We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and an optimal power-train control strategy over this route. In order to show the effectiveness of our method in practice, we use a HERE Maps API to apply our algorithms based on traffic data in the city of Boston with more than 110,000 links. Moreover, we validate the performance of our eco-routing algorithm using speed profiles collected from a traffic simulator (SUMO) as input to a high-fidelity energy model to calculate energy consumption costs. Our results show significant energy savings (around 12%) for PHEVs with a near real-time execution time for the algorithm., arXiv admin note: text overlap with arXiv:1810.01443

A novel single-switch coupled-inductor switched-capacitor (CISC) high step-up converter is proposed which has a boost-type input structure allowing an improved input current ripple compared to other leading CISC converters. This is important for sustainable energy applications such as photovoltaic (PV) cells and fuel cells where high current ripple can degrade performance or lifetime. Though large input filters can be added between the energy source and the boost converter to smooth a pulsed converter input current, the proposed converter naturally has a more moderate current ripple, reducing the need for additional filtering. With regards to the coupled inductor, the leakage inductor energy is recycled without using an extra clamped circuit, and core utilization is high. The detailed theoretical operation is presented and an experimental prototype (200 W, 36 V to 48 V input, 400 V output) achieves a maximum efficiency of 97.1%.

The bipolar pad is one of the most promising topologies in inductive power transfer systems for electric vehicles. However, there is scant literature on the analytical model of the bipolar pad. In this paper, a 3-D analytical model of the inductive power transfer system including a bipolar transmitter and a square receiver is developed based on the superposition of two 2-D subdomain analytical models. Ferrite and the aluminum shields with finite dimension are taken into account on the transmitter and receiver sides. An analytical calculation of the mutual inductance is then carried out with respect to the main parameters of the inductive power transfer system, namely the dimension of the coils, the conductivity and the permeability of the shield. Two study cases are demonstrated to highlight how the proposed method can accelerate speed up the pad design process. Calculation results of the proposed model are compared with both a finite element analysis model and experimental measurements, demonstrating that the proposed model is 9 times faster than the finite element analysis method. When comparing with the experimental results, computational error of the proposed model is less than 6% in most of the study cases

Voltage source converter (VSC) has been extensively used in power systems for interfacing renewable energies and other modern loads. Because of the nonlinear nature, it is important to establish a proper harmonic model of VSC devices when con-ducting harmonic analysis in power systems. This is especially true for low-order harmonics which are routinely encountered in present power systems. To this end, an analytical harmonic model that represents the low-order harmonic characteristics of the VSC is developed in this paper. The new model takes both the control loop and power loop (i.e., dc-link capacitor) of the VSC into account through rigorous mathematical derivations. The final result has shown that the VSC can be represented by a coupled impedance matrix at harmonic frequencies, which can be easily used for harmonic analysis in large-scale power systems. It also shows that the dc-link capacitor has a more noticeable impact on the harmonic impedance of VSC with a smaller dc-link capacitance and low-order harmonics. The correctness of the new model has been verified using EMT simulations and lab experiments. A complete procedure to construct the proposed VSC model is also established based on the research findings.

There is great interest in so-called nano-electronic devices due to the furious rate of device miniaturization. Fabrica-tion of micro and nano scale resistors and capacitors have already been achieved steadily, but so far, there has been little development in the way of nano-scale coil inductors. This is because of the physical limitations in miniaturiza-tion of the design of a solenoid with wires coiled around a metallic core. So, while transistors get steadily smaller, basic inductors in electronics remained relatively bulky. Few methods exist for creating conductive polymer coils and graphene-based kinetic nano-inductors, but their large-scale fabrication process is complex and mostly beyond the current commercial technology available. So, a simpler, scalable, and robust fabrication technique is needed to overcome this bottleneck. In this work we demonstrate a new technique consisting of the laser lithography using a laser engraver of a (poly)vinyl alcohol (PVA)/graphene oxide film composite which results in a large inductive effect. We attribute this behavior to the formation of high curvature twisted screw dislocation type conductive pathways composed of polyacetylene chains linked by pi-pi interactions to reduced graphene oxide flakes resulting in inductive effect.

International audience; The mechanisms of H 2 dissociation on three stoichiometric anatase TiO 2 terminations, (001), (100) and (101), have been studied by means of density functional theory (PBE+U) calculations. A two-step process was considered: first, H 2 dissociation into H + and H − pair, and second the H − species migrates to a neighboring O site, transferring the electrons to the substrate. On (001), it shows the lowest activation barriers for hydrogen dissociation, 0.37 eV, whereas the highest value was found on (101), 0.98 eV. For hydrogen transfer from Ti to near O, the activation barriers are higher (from 1.10 to 2.37 eV), which indicates the dissociation step is kinetically more favorable than the H transfer process, although the latter is thermodynamically more favorable. Electronic structure, vibrational frequency analysis as well as temperature effects are studied to characterize the reactivity. The relationship between electronic structure, geometry and reactivity is analyzed by means of reactivity descriptors, and the results are compared with ceria and rutile TiO 2 facets.

Ce-promoted Ni/Mg/Al mixed oxides hydrotalcite-derived catalyst washcoated on metallic FeCrAlloy monolith was investigated in catalytic steam cracking of Vacuum Gas Oil (VGO) over a mild temperature range (300–400 °C). Hydrotalcite-derived powder solids were used as a slurry for the washcoating process were synthesized using co-precipitation and subsequent thermal decomposition. The as-fabricated catalyst exhibited over 40% VGO conversion with 46% light cut (Naphtha, Kerosene and Diesel) and 47.7% light VGO selectivity and Total Acidity Number of 0.9 mg KOH/g sample. This result seems promising for steam cracking of VGO over a novel structured catalyst. The washcoated catalyst was characterized using X-ray diffraction, surface area and X-ray Photoelectron Spectroscopy. Also, the liquid products composition/ quality and gas products composition were measured with various techniques such as simulation distillation, gas chromatography, viscosimeter and micro carbon residue.

Renewable resources are starting to constitute a growing portion of the total generation mix of the power system. A key difference between renewables and traditional generators is that many renewable resources are managed by individuals, especially in the distribution system. In this paper, we study the capacity investment and pricing problem, where multiple renewable producers compete in a decentralized market. It is known that most deterministic capacity games tend to result in very inefficient equilibria, even when there are a large number of similar players. In contrast, we show that due to the inherent randomness of renewable resources, the equilibria in our capacity game becomes efficient as the number of players grows and coincides with the centralized decision from the social planner's problem. This result provides a new perspective on how to look at the positive influence of randomness in a game framework as well as its contribution to resource planning, scheduling, and bidding. We validate our results by simulation studies using real world data., Appears in IEEE Transactions on Sustainable Computing

Reactor performance of bubbling fluidized bed (BFB) and turbulent fluidized bed (TFB) was carefully examined and systematically compared using catalytic ozone decomposition as a model reaction, based on a complete mapping of local flow structures and spatial distributions of ozone conversion and solids holdup. TFB clearly has a higher conversion and shows better reactor performance than BFB as a result of the vigorously turbulent flow and the relatively homogeneous gas–solids mixing in TEB. Besides, the intensive interaction between gas and solids in TFB leads to greater gas–solids contact efficiency of TFB over that of BFB. Due to gas bypassing and backmixing caused by bubbling behaviours and two-phase structure, BFB deviates significantly from a plug flow reactor and sometimes from a continuously stirred tank reactor. The flow structures essentially dictate the reactor performance in the low-velocity fluidized beds.

Ruthner powder is a by-product of the steel hot-rolling process. This study introduces a new application area for this waste material by investigating its activity for the oxygen evolution reaction. Ruthner powder with the α-Fe2O3 phase structure was deposited on the carbon paper substrates using the electrophoretic deposition (EPD) process to fabricate the electrodes. The effect of the concentration of cetrimonium bromide ([CTAB]) and the Ruthner powder ([RP]) in the EPD cell on the morphology and activity of the electrodes were investigated by SEM, LSV, and EIS techniques. The results revealed the formation of a homogenous layer on the carbon paper when [CTAB] and [RP] were respectively 0.4 g.l−1 and 0.2 g.l−1. The obtained electrode showed the best activity among all fabricated electrodes. In particular, its onset overpotential and overpotential at a current density of 10 mA.cm−2 were respectively 85% and 25% lower than those of bare carbon electrodes.

In this paper, a novel modular multilevel dc-dc converter with high power-density potential is proposed based on a cascaded string of voltage source submodules (VSM) merged with a current source submodule (CSM) that is configured to rapidly invert the polarity of the current in the VSM string. The proposed hybrid converter combines the i) modularity advantages of the modular multilevel converter (MMC) and ii) the high effective frequency advantages of the flying capacitor converter (FCC). Unlike other hybrid non-isolated MMC structures the proposed converter features a novel CSM stage enabling i) a near 50% reduction in string current, and ii) the input source and output load to be commonly grounded. In addition, the proposed operational approach enables self-balancing of the VSMs and a simple overall control structure. This article introduces the main operating principles of this novel topology termed the Current Shaping Modular Multilevel Forward Converter (CS-M2FC) along with a proposed control design. A peak efficiency of 97.1% is measured for a laboratory-scale prototype at 950-137V and 1.45 kW.

The predictive cruise control (PCC) is a promising method to optimize energy consumption of vehicles, especially the heavy-duty vehicles (HDV). Due to the limited sensing range and computational capabilities available on-board, the conventional PCC system can only obtain a sub-optimal speed trajectory based on a shorter prediction horizon. The recently emerging information and communication technologies such as vehicular communication, cloud computing, and Internet of Things provide huge potentials to improve the traditional PCC system. In this paper, we propose a general framework for the enhanced cloud-based PCC system which integrates a data-driven traffic predictive model and the instantaneous control algorithms. Specifically, we introduce a novel multi-view CNN deep learning algorithm to predict traffic situation based on the historical and real-time traffic data collected from fields, and the time-varying adaptive model predictive control (MPC) to calculate the instantaneous optimal speed profile with the aim of minimizing energy consumption. We verified our approach via simulations in which the impact of various traffic condition on the PCC-enabled HDV has been fully evaluated.

Concentrator PhotoVoltaics (CPV) may generate considerable heat as a byproduct in addition to power. Using that heat as concentrated solar power (CSP) to thermally desalinate salt water would allow for value addition in arid regions by supplementing produced electricity with fresh water. This paper discusses the primary trade-off between the net electricity amount and the net distilled water amount, both of which are desirable products in a hybrid concentrated photovoltaic and thermal system (CPV-T). While higher temperatures promote freshwater generation, they also cause a quick fall in cell efficiency, reducing the quantity of power generated and causing cell deterioration. The CPV-T receiver, which is partially covered with cells and then supplementary heated in a cell-free portion, is modeled and established. Furthermore, simple-stage and multistage desalination unit models are presented, linked to the receiver, and examined to cope with the reduced temperature limits of this receiver. The results demonstrate a CPV-T receiver's ability to generate both electrical power and freshwater, while also demonstrating that the cell temperature constraint can become quite important beyond 50% of the receiver surface coverage. These first order results establish the system's validity and potential and will aid the system designer in the initial system design.

This paper considers an unmanned aerial vehicles (UAV) communication network, where UAV operate as an aerial mobile relay between a source and a destination of the network. To capture the “timeliness” of the received information at the destination node, a new performance metric named age of information (AoI) is considered. In addition, a short packet communication scheme maintains low latency in the proposed UAV wireless communication system. The finite block-length theory investigates the performances of short packet communications scheme in the UAV-assisted wireless communications system. In this paper, the Average Age of Information (AAoI) is estimated by applying the Stochastic Hybrid Systems (SHS) model. The SHS model comprises discrete states represents events that reset the AoI process and continuously dynamics that represent linearly growing age processes. Finally, a closed-form expression for the AAoI of the proposed UAV wireless communication system is derived and it can be used to estimate the optimal altitude, block length and other parameters.

One of the main applications of energy storage systems (ESSs) is transmission and distribution systems cost deferral. Further, ESSs are efficient tools for localized reactive power support, peak shaving, and energy arbitrage. This article proposes an ESSs planning algorithm that includes all previous services. The proposed algorithm increases the distribution company profit and minimizes its future system upgrade cost. For a comprehensive planning algorithm, other options, such as including static VAR compensators (SVCs), feeders upgrade, or adding distributed generators, are considered along with ESSs. Different scenarios are utilized to model the load variation, the renewable resources’ intermittency, and the market price fluctuation. The problem constraints include an ESS dynamic model that reflects the capacity and lifetime limitations. Different battery technologies with different costs and dynamic characteristics are compared. The network power flow model is added to account for the voltage level and feeders’ capacity. Power limits constraints are included for the DGs and SVCs as well. The optimization problem is formulated as a mixed-integer quadratic programming problem. To validate the proposed technique, a case study is conducted on a real 41-bus radial feeder in Ontario, Canada using real data for renewable sources, loads, and market prices.

The synthesis of renewable chemical fuels from CO2 and H2O via photoelectrochemical (PEC) route reprensents a promising room-temperature approach for transforming greenhouse gas into value-added chemicals (e.g., syngas), but to date it has been hampered by the lack of efficient photocathode for CO2 reduction. Herein, we report efficient PEC CO2 reduction into syngas by photocathode engineering. The photocathode is consisting of a planar p-n Si junction for strong light harvesting, GaN nanowires for efficient electron extraction and transfer, and Au/TiO2 for rapid electrocatalytic syngas production. The photocathode yields a record-high solar energy conversion efficiency of 2.3%. Furthermore, desirable syngas compositions with CO/H2 ratios such as 1:2 and 1:1 can be produced by simply varying the size of Au nanoparticle. Theoretical calculations reveal that the active sites for CO and H2 generation are the facet and undercoordinated sites of Au particles, respectively.

Capturing the dynamic behavior of the power distribution grids, especially under high penetration of renewables, is of high interest for grid operators. The distribution power grids are not fully observable due to lack of sufficient metering infrastructure, especially downstream of medium voltage substations. Therefore, fusion of data recorded at significantly different reporting rates was proposed to increase the situational awareness of the system with non-negligible effect on the accuracy of the monitoring tool. Higher reporting rates are possible for next generation smart meters, but they raise higher concerns about data privacy, already an issue for smart meters rollout. This work proposes a framework for knowledge extraction from high reporting-rate smart metering data. The process takes place at smart meter level and with low computation and communication costs and preserving user privacy, with the scope to increase the accuracy of the monitoring tools for distribution power grids. The methodology makes use of statistical metrics able to capture system dynamics relevant for network diagnosis. The proposed approach is validated on a three-phase low voltage power flow model applied to a realistic testbed microgrid and real field measurements synchronized at one second.

Long horizon state of health (SOH) monitoring and remaining useful life (RUL) prediction are of industrial value in prognostic and health management (PHM) of lithium-ion batteries (LIBs) to ensure their reliable functionality by early detection. Machine Learning, as a data-driven health diagnostic technique, has been widely utilized in solitary and hybrid structures. However, an accurate SOH estimation and RUL prediction method with less computational burden are highly desirable for the online state prediction in an electric vehicle application. This paper evaluates nonlinear autoregressive with external input (NARX) recurrent neural network (RNN) and time delay neural network (TDNN) in their prediction precision using the NASA dataset. The superior method, NARXRNN, is employed for two different datasets to estimate the battery's SOH and predict its RUL on a broad horizon. The results reveal the outstanding performance by presenting the root mean square error within 3% and mean absolute error within 2% for unseen data. Therefore, this method is capable to accurately predict the SOH of LIBS from historical data at low computational complexity. It is a promising model for long horizon SOH and RUL prediction and practical for online applications.

State-of-health (SoH) is one of the critical battery states that must be estimated and closely monitored by the onboard battery management system in electric vehicles (EVs). In this study, the battery SoH, especially the capacity fade, is calculated based on the decoupled characteristic of the charging current under the constant-voltage (CV) scenario. Firstly, a dynamic-decoupled parameter identification method is proposed to extract the parameters of the simplified 2nd-order resistor-inductor (RL) network-based equivalent circuit model (ECM), developed by the authors. Secondly, the dynamic characteristics of the decoupled CV charging currents at different aging states are qualitatively investigated, and the corresponding time constant is selected as a feature-of-interest (FoI) to reflect the battery capacity degradation. Thirdly, the aging data based on two types of lithium-ion batteries are employed to evaluate the performance of the proposed method. Verification results demonstrate that the proposed parameter identification method yields a reduced computational cost with a satisfactory fitting performance, compared to the conventional methods. The proposed parameterization method and the selected FoI guarantee the root-mean-square errors of the estimated SoH less than 2%, and the comparative results further validate the superiority of the selected FoI in terms of the SoH estimation accuracy.

SiC MOSFET has superior switching performance over Si IGBT in terms of power loss and temperature characteristics. In order to significantly improve the efficiency and power density of medium voltage drive and high-power converters, this paper proposes a current source gate driver for series connected SiC MOSFETs, forming a universal block of series connected SiC devices with higher voltage rating. Proposed current source gate driver has better gate voltage synchronization performance because of its constant gate current and novel gate driver structure. By implementing synchronized gate voltages, the snubber circuit is designed only for power loop difference, gate displacement current difference, and the snubber can be minimized or even be eliminated. The proposed block has been verified by LTSPICE simulations and multi-pulse test experiments under 200kHz, 2kV, 0~60A condition using three 1.2kV/60A C2M0040120D SiC MOSFETs connected in series.

Methane hydrate has become one promising energy resource for humankind. In this study, recent worldwide onshore/offshore drilling and production activities are analysed. The most recent reports from sites such as Japan (2013 and 2017) and China (2017) show that the road towards comprehensive utilisation of methane hydrate is underway. Though the production methods (depressurisation, thermal stimulation and carbon dioxide (CO2) replacement) diverge in safety and efficiency, potential has been confirmed for future large-scale utilisation. The world hydrate policy is dependent on the socioeconomic status and environmental concerns in major countries. It is urged that international regulations on commercial explorations be settled for methane hydrate projects.

Generation Expansion Planning (GEP) can inform regulation, electricity market design, and regional system planning by identifying adaptive investment strategies. Relevant uncertainties include hourly variability in load and renewable generation and decadal-scale uncertainty in technology, markets, and regulation. A multi-stage and multi-scale stochastic GEP model that represents these uncertainties at sufficient resolution becomes intractable. We present an approach for representing this multi-scale uncertainty, and compare it to existing methods, applied to a two-stage stochastic GEP model with a cumulative carbon emission target. For long-term uncertainty, we compare partitioning methods, which reduce the number of decision variables but retain all scenarios, to representative scenario methods, which retain only a subset of the original scenarios. For short-term uncertainty, we compare methods that select representative weeks based on distance metrics in the parameter space to methods that use the covariance of outcomes across feasible decisions to select weeks. We find that scenario reduction methods struggle to find the appropriate investment levels for variable renewable generation and consequently produce more costly plans than scenario partitioning methods. While simple approximating methods perform well with larger models, covariance based approximations have the best performance overall.

International audience; Optimizing nuclear unit outages is of significant economic importance for the French electricity company EDF, as these outages induce a substitute production by other more expensive means to fulfill electricity demand. This problem is quite challenging given the specific operating constraints of nuclear units, the stochasticity of both the demand and non-nuclear units availability, and the scale of the instances. To tackle these difficulties we use a combined decomposition approach. The operating constraints of the nuclear units are built into a Dantzig-Wolfe pricing subproblem whose solutions define the columns of a demand covering formulation. The scenarios of demand and non-nuclear units availability are handled in a Benders decomposition. Our approach is shown to scale up to the real-life instances of the French nuclear fleet.

Cu/SiO2 catalysts prepared by a deposition-decomposition (DD) method using ammonium hydroxide are currently among the most promising catalysts for oxalates hydrogenation to ethylene glycol (EG). Here, a Cu/SiO2 catalyst prepared by the DD method was pre-reduced at a) 200–350 °C in 100% H2, and 2) 200 °C in a 50% H2/N2 mixture. Then, it was tested at 200 °C, and 25 barg, while EG yields were optimized, with H2-GHSV and H2/DMO ratios in the ranges 1000–4000 h−1 and 30–200 mol/mol. The calcined catalyst presents an XRD amorphous Cu phyllosilicate phase. After pre-reduction in pure H2 at 200–250 °C (Tred), the Cu metallic surface area increased from 6 to 12 m2/gcat and slightly decreased at 350 °C. Simultaneously, the silanol's band, measured by DRIFT experiments, increased with Tred. The highest ethylene glycol yield (91%) was achieved after pre-reduction at 200 °C in pure hydrogen, working with an H2-GHSV and H2/DMO of 1050 h−1 and 68 mol/mol, respectively. The catalyst was stable for more than 36 h after a 20 h induction period. Catalyst characterization results as a function of Tred confirm that mixed-valence copper nanoparticles favor the EG selective formation, while side reactions leading to ethanol and 1,2-butanediol are related to exposed acidic and basic sites due to decreased Cu/support interactions.

Owing to the shorter wavelength in the millimeter-wave (mmWave) spectrum, miniaturized antennas can receive power with a higher efficiency than UHF bands, promising sustainable mmWave-powered Internet of Things (IoT) devices. Nevertheless, the performance of a mmWave power receiver has not been compared, numerically or experimentally, to its sub-6 GHz counterpart. In this paper, the performance of mmWave-powered receivers is evaluated based on a novel wearable textile-based higher-order mode microstrip antenna, showing the benefits of wireless power transmission (WPT). Firstly, a broadband antenna is proposed maintaining a stable wearable measured bandwidth from 24.9 to 31.1 GHz, over three-fold improvement compared to a conventional patch. The proposed antenna has a measured 8.2 dBi co-polarized gain with the highest thickness-normalized efficiency of a wearable antenna. When evaluated for compact power receivers, the measured path gain shows that WPT at 26 GHz outperforms 2.4 GHz by 11 dB. A rectenna array based on the proposed antenna is then evaluated analytically showing the potential for up to 6.3x higher power reception compared to a UHF patch, based on the proposed antenna's gain and an empirical path-loss model. Both use cases demonstrate that mmWave-powered rectennas are suitable for area-constrained and large-area wearable IoT applications.

Nitrous oxide (N2O) is a greenhouse gas (GHG) mainly issued from agriculture and waste management activities. Since N2O has a global warming potential 298 times higher than CO2 and an annual emission equivalent to 5.1 % v/v of total GHG emissions, the control of its emissions becomes essential. One of the main challenges to control N2O emissions is to capture them under the main sources’ conditions, i.e. atmospheric pressure and ambient temperature. The available technologies to control N2O emissions operate presently at medium/high pressure, being high energy consuming. The development of new and specific adsorbents for capturing N2O is important. Molecular modeling is a helpful tool to develop engineered adsorbents, generating virtual molecular interactions as a prior adsorbate-adsorbent system before experimental studies. Zeolitic Imidazolate Framework-8 (ZIF-8) has been selected in this study as an adsorbent because of its easy and reproducible synthesis, thermal stability, flexible structure, hydrophobicity and high adsorption capacity of gases, including GHGs. In the present study, the interactions between N2O and ZIF-8 were studied by molecular modeling methods, PM6 and DFT. Optimized geometries of N2O and ZIF-8, adsorption energy and ligand point length parameters were analyzed as part of a physical adsorption process. Three adsorption sites were identified on the four-membered and six-membered windows of ZIF-8. The two possible N2O interaction configurations (–ONN and –NNO) were simulated and compared in order to determine the most probable behavior of N2O. The study showed that the –ONN configuration produces more stable interactions with ZIF-8 than –NNO configuration. The six-membered window of ZIF-8 seems to be the pore where the most stable interactions occur based on the adsorption energy and the approach distance. The present study was concentrated on the interactions of one N2O molecule and a fragment of the ZIF-8, and it will be the basis for molecular dynamics simulations of adsorption with a control volume, containing several N2O molecules and a representative surface of ZIF-8 under different pressures and temperatures.

Hybrid renewable energy systems (HRES) are seeing as a solution to overcome the fluctuation and randomness of certain renewable energy sources, such as solar and wind power. Coupling the fluctuating renewable energy sources with the controllable sources, such as biomass-fueled micro-cogeneration, constitute an HRES that significantly reduces CO2 emissions and primary energy consumption. The purpose of this work is to review research works on hybrid renewable energy systems based on micro-cogeneration and to present a case study of optimizing a solar-based micro-cogeneration system. First, renewable energy-fueled micro-cogeneration systems are presented according to the prime mover technology: Stirling engine, organic Rankine cycle and photovoltaic-thermal (PVT). The different prime movers are assessed according to their advantages, disadvantages and market availability. Next, several research works on hybrid renewable energy systems including solar and micro-cogeneration technologies are summarized and key findings are highlighted. Finally, the results of the case study are presented for reasoning the necessity of system hybridization. The results indicated that more experimental data on HRES and research effort on energy management strategies and stochastic optimization models are required. The results of the case study showed maximum thermal and electrical reliability of 68% and 70%, respectively. The optimized PVT/battery/thermal storage system was not able to cover all energy demand of the case study but supporting heat and electricity sources are required.

The increasing power density in modern high-performance multi-processor system-on-chip (MPSoC) is fueling a revolution in thermal management. On the one hand, thermal phenomena are becoming a critical concern, making accurate and efficient simulation a necessity. On the other hand, a variety of physically heterogeneous solutions are coming into play: liquid, evaporative, thermoelectric cooling, and more. A new generation of simulators, with unprecedented flexibility, is thus required. In this paper, we present 3D-ICE 3.0, the first thermal simulator to allow for accurate nonlinear descriptions of complex and physically heterogeneous heat dissipation systems, while preserving the efficiency of latest compact modeling frameworks at the silicon die level. 3D-ICE 3.0 allows designers to extend the thermal simulator with new heat sink models while simplifying the time-consuming step of model validation. Support for nonlinear dynamic models is included, for instance to accurately represent variable coolant flows. Our results present validated models of a commercial water heat sink, and an air heat sink plus fan that achieve an average error below 1 degree Celsius and simulate, respectively, up to 3x and 12x faster than the real physical phenomena.

Heterostructures made from van der Waals materials provide a template to investigate proximity effects at atomically sharp heterointerfaces. In particular, near-field charge and energy transfer in heterostructures made from semiconducting transition metal dichalcogenides (TMD) have attracted interest to design model 2D "donor-acceptor" systems and new optoelectronic components. Here, using of Raman scattering and photoluminescence spectroscopies, we report a comprehensive characterization of a molybedenum diselenide (MoSe$_2$) monolayer deposited onto hexagonal boron nitride (hBN) and capped by mono- and bilayer graphene. Along with the atomically flat hBN susbstrate, a single graphene epilayer is sufficient to passivate the MoSe$_2$ layer and provides a homogenous environment without the need for an extra capping layer. As a result, we do not observe photo-induced doping in our heterostructure and the MoSe$_2$ excitonic linewidth gets as narrow as 1.6~meV, hence approaching the homogeneous limit. The semi-metallic graphene layer neutralizes the 2D semiconductor and enables picosecond non-radiative energy transfer that quenches radiative recombination from long-lived states. Hence, emission from the neutral band edge exciton largely dominates the photoluminescence spectrum of the MoSe$_2$/graphene heterostructure. Since this exciton has a picosecond radiative lifetime at low temperature, comparable with the energy transfer time, its low-temperature photoluminescence is only quenched by a factor of $3.3 \pm 1$ and $4.4 \pm 1$ in the presence of mono- and bilayer graphene, respectively. Finally, while our bare MoSe$_2$ on hBN exhibits negligible valley polarization at low temperature and under near-resonant excitation, we show that interfacing MoSe$_2$ with graphene yields a single-line emitter with degrees of valley polarization and coherence up to $\sim 15\,\%$., version 3, 5 figures