• Energy Research
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Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

Environmental tax reform (ETR), a shift from labour to carbon taxes, has been mostly modelled using general equilibrium (GE) analysis. Since a low-carbon transition will require deep transformations, one will also have to address out-of-equilibrium dynamics and increased agent heterogeneity. Unlike GE models, agent-based models (ABMs) are well equipped to deal with this. We therefore replicate a recent GE model for ETR using an agent-based approach. This process, known as "agentization", allows assessing similarities as well as differences in policy impacts between the two modelling approaches, in turn providing a test of the robustness of the GE results. We find that the agent-based model is able to replicate many results of the general equilibrium analysis, while revealing strengths and weaknesses of both model types. We discuss concrete implementation steps and difficulties experienced in the GE-ABM translation process. We illustrate the potential of ABM by extending the model in several directions. We show that heterogeneous subsistence consumption can increase the space for combining a double dividend with an equity goal, and that overall macro-economic results can conceal important distributional impacts when green preferences and labour supply elasticities vary.

Organic solar cells utilize an energy-level offset to generate free charge carriers. Although a very small energy-level offset increases the open-circuit voltage, it remains unclear how exactly charge generation is affected. Here we investigate organic solar cell blends with highest occupied molecular orbital energy-level offsets (∆EHOMO) between the donor and acceptor that range from 0 to 300 meV. We demonstrate that exciton quenching at a negligible ∆EHOMO takes place on timescales that approach the exciton lifetime of the pristine materials, which drastically limits the external quantum efficiency. We quantitatively describe this finding via the Boltzmann stationary-state equilibrium between charge-transfer states and excitons and further reveal a long exciton lifetime to be decisive in maintaining an efficient charge generation at a negligible ∆EHOMO. Moreover, the Boltzmann equilibrium quantitatively describes the major reduction in non-radiative voltage losses at a very small ∆EHOMO. Ultimately, highly luminescent near-infrared emitters with very long exciton lifetimes are suggested to enable highly efficient organic solar cells. Donor–acceptor systems with low energy-level offset enable high power efficiency in organic solar cells yet it is unclear what drives charge generation. Classen et al. show that long exciton lifetimes enable efficient exciton splitting and thus generation of free charges while also suppressing voltage losses.

Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

The optical and photovoltaic properties of Si NCs / SiC multilayers (MLs) are investigated using a membrane-based solar cell structure. By removing the Si substrate in the active cell area, the MLs are studied without any bulk Si substrate contribution. The occurrence is confirmed by scanning electron microscopy and light-beam induced current mapping . Optical characterization combined with simulations allows us to determine the absorption within the ML absorber layer, isolated from the other cell stack layers. The results indicate that the absorption at wavelengths longer than 800 nm is only due to the SiC matrix. The measured short-circuit current is significantly lower than that theoretically obtained from absorption within the ML absorber, which is ascribed to losses that limit carrier extraction. The origin of these losses is discussed in terms of the material regions where recombination takes place. Our results indicate that carrier extraction is most efficient from the Si NCs themselves, whereas recombination is strongest in SiC and residual a-Si domains . Together with the observed onset of the external quantum efficiency (EQE) at 700-800 nm, this fact is an evidence of quantum confinement in Si NCs embedded in SiC on device level.

The accurate training of a wind power forecasting (WPF) model for a newly built wind farm is difficult because of limited historical data. This study established a multitask learning architecture wherein the WPF in different wind farms represents an independent task. Subsequently, a novel short-term WPF model based on a multitask learning architecture was proposed. In this model, a multitask Gaussian process is used to capture the intertask conjunction, which contributed to the training of each task. The proposed methodological framework employs dependencies from other tasks wherein older wind farms contain substantial historical data to enhance the performance of tasks in which there is a newly built wind farm. Several numerical experiments were conducted using datasets from seven independent wind farms in Australia. The results show that the proposed scheme not only obtains improved point forecasting results but also produces better probabilistic forecasting results, thus demonstrating the superiority of the proposed method.

Thermo-economically optimal design = optimal molecule + optimal process + optimal equipment.