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Earlier sources: Energy
Energy research and engineering concern how power is produced, stored, delivered, and consumed. Follow solar and nuclear power, fusion, geothermal systems, batteries, electricity grids, and changing power demand.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗650 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Air-core vortex formation and tail breakup in tidal-energy intakes: Effects of inlet geometry and flow mechanisms ↗
Air-core vortices (ACVs) in horizontal tidal-energy intakes can induce air entrainment, deteriorate inflow uniformity, and threaten downstream hydraulic components. Experiments and high-fidelity numerical simulations were conducted to investigate the effects of a straight pipe inlet (SPI) and a bell-mouth inlet (BMI) on ACV formation and tail breakup. The BMI suppresses ACV formation by mitigating inlet flow separation and weakening vortex stretching, reducing the maximum normalized vertical vorticity near the free surface by approximately 40%–45% compared with the SPI. By contrast, the separa…
- OpenAlex · Published · First archived
Preparation and performance study of novel polyurethane-based composite phase change materials for battery thermal management ↗
Solid–liquid phase change materials are promising for thermal management, but their leakage and low thermal conductivity limit practical applications. In this study, a novel PU@BNNSs/CF solid–solid composite phase change material was prepared by vacuum impregnation using polyurethane constructed with polyethylene glycol as the phase change matrix, boron nitride nanosheets as thermally conductive fillers, and copper foam as the supporting framework. The composite showed good shape stability without obvious leakage at 80 °C. It had a melting temperature of 54.13 °C and a melting enthalpy of 82.6…
- OpenAlex · Published · First archived
Energy efficiency imperatives from lifecycle energy demand trajectories in Global South mass housing ↗
The built environment of sub-Saharan Africa faces a critical deficit in lifecycle energy benchmarks, compounded by rapidly escalating residential demand driven by urbanization and climatic stress. Existing energy analysis practice seldom integrates operational and embodied energy accounting across climatically divergent contexts, limiting the evidence base for differentiated building performance policy. This study develops and validates a hybrid framework that couples smart-meter-calibrated EnergyPlus operational models with localized cradle-to-site embodied energy estimation for Ethiopia’s ur…
- OpenAlex · Published · First archived
Hybrid modeling and energy optimization of NGL demethanizers using deep reinforcement learning ↗
Abstract Cryogenic NGL demethanizers suffer from energy inefficiencies due to non-convex thermodynamic constraints. This study aims to implement a Deep Reinforcement Learning (DRL) framework to optimize energy consumption while respecting complex operational boundaries. A Soft Actor-Critic (SAC) agent was employed, trained on 2,000 rigorous Aspen HYSYS digital twin scenarios via a Deep Neural Network (DNN) surrogate. Unlike simplified proxy models, this supervisory strategy directly interacts with the high-fidelity simulation to navigate nonlinear process dynamics. The results demonstrate a 12…
- OpenAlex · Published · First archived
Development of a UV-Responsive Fusion Peptide Combining a Cell-Penetrating and a Mitochondria-Targeting Peptide to Suppress Intracellular Off-Target Effects ↗
Abstract Modification of plant mitochondria has attracted increasing attention as a strategy for developing highly productive crops, driving efforts to achieve efficient mitochondrial delivery of cargos. Mitochondria-targeting gene carriers with a strong cell-penetrating ability have been shown to deliver plasmid DNA into plant mitochondria, but this ability can reduce mitochondrial selectivity through nonspecific interaction with intracellular membranes. Herein, we developed a fusion peptide in which a mitochondria-targeting peptide was linked to a cell-penetrating peptide via an ultraviolet…
- OpenAlex · Published · First archived
Design and implementation of FLC and SVSC techniques for MPPT battery charging and dual-leg DC–AC conversion in hybrid electric power systems ↗
Abstract Hybrid renewable energy systems (HRES) commonly rely on multistage power conversion structures, which increase circuit complexity, switching losses, and overall system cost, while potentially decreasing conversion efficiency. To overcome these limitations, this study proposes a single-stage hybrid electric power system employing a fuzzy logic controller (FLC) for maximum power point tracking (MPPT)-based battery charging and a sliding variable structure controller (SVSC) for the control of a dual-leg DC–AC converter. The FLC enables efficient extraction of the maximum available power…
- OpenAlex · Published · First archived
Performance Optimization of Lead-Free Cs2AgBiI6 Solar Cells with the LBSO Electron Transport Layer: A SCAPS-1D Simulation Study ↗
Abstract Lead toxicity in conventional halide perovskites has long been a concern for practical photovoltaic deployment, and Cs2AgBiI6 double perovskites gained significant attention as promising lead-free alternatives due to their high carrier mobility, suitable optoelectronic characteristics, and relatively good chemical stability. In this work, density functional theory (DFT) calculations were performed to investigate the electronic properties of the Cs2AgBiI6 absorber, while SCAPS-1D simulations were independently employed to optimize the photovoltaic performance of the proposed device arc…
- OpenAlex · Published · First archived
Green-synthesized Co₃O₄ nanoparticles: Structural, vibrational, magnetic, and electrochemical insights for high-performance energy storage applications ↗
Co₃O₄ nanostructures were synthesized using an aqueous pomegranate (Punica granatum) peel extract as a plant-derived processing aid and subsequently evaluated through an integrated structural, vibrational, morphological, surface-chemical, magnetic, optical, and electrochemical characterization strategy. X-ray diffraction (XRD) confirmed the formation of cubic spinel Co₃O₄ (Fd-3m) with an average crystallite size of approximately 28 nm; Williamson–Hall analysis, where applicable, gave a comparable crystallite size of approximately 29 nm and a low microstrain of approximately 1.5 × 10⁻³ . Raman…
- OpenAlex · Published · First archived
Microgrid energy management optimization using PPO with curriculum learning trained in virtual simulation environment ↗
Abstract Microgrid energy management systems (EMS) require real-time, economically optimal, and safe dispatch strategies under high renewable uncertainty. While Deep Reinforcement Learning (DRL) offers promising online decision-making capabilities, standard DRL algorithms struggle with the “cold start” problem, slow convergence, and severe Sim-to-Real performance degradation when transferred from simulation to real-world operating conditions. To address these challenges, this paper proposes a novel Curriculum Learning-enhanced Proximal Policy Optimization (CL-PPO) framework for grid-connected…
- OpenAlex · Published · First archived
A deep learning-based surrogate model for Severe Accidents in nuclear reactors using ASTEC ↗
Integral codes like the Accident Source Term Evaluation Code (ASTEC) are powerful tools to study the physics of Severe Accidents (SAs) in nuclear reactors. Real time SA simulators can also be helpful in training operators of nuclear plants to react correctly to malfunctions. However, SA simulators can take up to several days per simulation, making their use infeasible for real time applications. In this work we show how to speed up a SA simulator with a fast, Deep Learning based (DL), surrogate model (SM). The SM is built as a combination of a dimensionality reduction stage, via an AutoEncoder…
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How to assess evidence about Energy
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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