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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 ↗742 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
Conjugate heat-transfer and integrated performance assessment of supercritical CO2 flow in self-affine rough geothermal fractures ↗
Supercritical CO 2 (sCO 2 ) is a promising working fluid for enhanced geothermal systems, but fracture-scale heat extraction depends on the coupled effects of surface roughness, flow conditions, and strongly variable thermophysical properties. A two-dimensional conjugate heat-transfer model was established for an independent smooth fracture and five self-affine rough fractures, accounting for the dependence of CO 2 thermophysical properties on temperature and pressure. After validation against published transient experiments, calculations were conducted for 96 combinations of fracture roughnes…
- OpenAlex · Published · First archived
Understanding Repulsion‐Governed Adsorption Mechanism for Efficient Surface Passivation in Blade‐Coated Perovskite Solar Cells ↗
ABSTRACT Surface passivation of perovskite thin‐films via adsorption of amine‐based derivatives plays an important role in minimizing nonradiative recombination. In this work, we developed a novel and efficient amine‐based surface passivation molecule, cystamine dihydrochloride (CH), which possesses a characteristic symmetric structure and exhibits an anomalous passivation mechanism. It is found that the electron‐rich sulfur atoms in central disulfide moiety of CH experience strong short‐range repulsion with surface iodides of perovskites. Consequently, contrary to the conventional attraction‐…
- OpenAlex · Published · First archived
A Novel Data-Driven Approach Integrating DGCN and TILDE-Q for Ultra-Short-Term Photovoltaic Power Forecasting ↗
Accurate ultra-short-term photovoltaic (PV) power forecasting is essential for the reliable operation and energy management of PV systems. However, rapid irradiance variations and complex meteorological conditions result in highly intermittent, nonlinear, and nonstationary PV power generation. Existing forecasting methods generally focus on temporal dependencies but provide limited representation of the dynamic relationships among meteorological variables and PV power. Moreover, conventional point-wise loss functions do not explicitly preserve the temporal shape of multi-step forecasts. To add…
- OpenAlex · Published · First archived
New Energy-Saving Absorption Configurations with Heat Exchange Between Partial Lean and Semi-Lean Solutions for CO2 Capture ↗
Post-combustion CO2 capture from coal-fired power plant flue gas remains constrained by the low material performance and high energy consumption of solvent regeneration. Advancement needs to be made on two fronts: the development of improved solvents and materials, and the design of more efficient capture process configurations. Among the configurations developed to lower the energy penalty, lean solution vaporization and compression (LVC) effectively reduces reboiler duty; however, it introduces a vapor compressor that raises capital cost and consumes electricity, which is unfavorable given t…
- OpenAlex · Published · First archived
FusionEP: Adaptive Cross-Modal Deep Fusion Network for Essential Protein Identification via Multi-Omics Integration and Contrastive Learning ↗
Identifying essential proteins lays a foundation for dissecting disease mechanisms and mining therapeutic targets. Existing algorithms mostly adopt unimodal inputs and struggle to capture multi-level biological interactions from genomics, subcellular localization and proteomics. We present FusionEP, which is an adaptive cross-modal deep fusion network built upon contrastive learning to predict essential proteins. FusionEP integrates gene expression profiles, subcellular localization features, and protein interaction map structures. For gene expression information, we design a six-layer Transfo…
- OpenAlex · Published · First archived
Multi-objective optimization design of a thermal management system for large-capacity energy storage batteries coupling liquid cooling, phase change material and bio-inspired fins ↗
With the increasing deployment of large-capacity energy-storage batteries, improving the thermal performance of their thermal management systems has become increasingly important. However, a single cooling method struggles to meet the stringent requirements of these systems. In this study, a 280 Ah large-capacity energy storage battery is selected as the research object to construct a hybrid thermal management system that couples liquid cooling, phase change material (PCM), and bio-inspired fins. In addition, a multi-objective optimization framework is developed to optimize the thermal perform…
- OpenAlex · Published · First archived
How Multivariate Design of Experiments and Feature Extraction Strategy Can Support the Understanding of Time Domain Nuclear Magnetic Resonance Signals from Complex Elastomeric Systems ↗
Abstract Time domain nuclear magnetic resonance (TD-NMR) is a nondestructive analytical technique increasingly used for the characterization of rubber products. Its growing adoption is due to the nature of the acquired signal, which consists of a time-dependent decay strongly correlated with the polymeric mobility of the analyzed materials. Consequently, any factor influencing polymeric mobility also affects the TD-NMR signal, making it essential to understand the impact of these factors for routine application of the technique. To this aim, a multivariate design of experiment (MDoE) approach…
- OpenAlex · Published · First archived
AI-based smart energy consumption prediction for sustainable buildings using IoT data ↗
Abstract Two complementary evidence layers are investigated for this study to look at next-hour building electricity forecasting. The first is a commercial building case study showing a 14 month monitoring experience of a 12,400 square metre office building in Bengaluru, India. The statistics revealed in the past include an RMSE of 3.27 kWh, a MAE of 2.41 kWh, a MAPE of 4.83%, a CoD of 0.971, and a median edge inference time of 38 ms. Unfortunately, the original telemetry, feature dictionary, checkpoints and residuals at the time stamp level were not available, and therefore these values are n…
- OpenAlex · Published · First archived
MSMFusion: A Method for Multiscale Dual-Path State Space Modeling for Multimodal Medical Image Fusion ↗
Multimodal medical image fusion aims to integrate information from different imaging techniques to generate a single fused image that is comprehensive and rich in detail. Structural and functional imaging provide high-resolution anatomical details and tissue metabolic information, respectively. Complementary fusion improves quantitative fusion quality and preserves structural and functional information in one view, which aids clinical interpretation. Currently, convolutional neural network-based methods struggle to efficiently capture global features, whereas Transformer-based models excel at…
- OpenAlex · Published · First archived
Integrated hydrogen production and liquefaction via alkaline electrolysis: Conceptual design and life cycle assessment under geothermal and hybrid renewable energy scenarios ↗
The viability of a hydrogen economy depends on efficient liquefaction for long-distance transport and storage. This study evaluates an integrated system combining alkaline water electrolysis, continuous ortho -to-para catalytic conversion, and reverse-Brayton/Organic Rankine Cycle (ORC) cooling. Aspen HYSYS V14 simulations yield 15.07 kg/h of liquid hydrogen (97.98% para -hydrogen) at −236.9 °C and 2100 kPa. Two power-supply options are assessed: a 1008.2-kW geothermal dual-flash/ORC system in Meshkinshahr, Iran, and a HOMER Pro-optimized hybrid microgrid (8 MW PV, 1.98 MW wind, 500 kW biogas,…
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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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