Unconventional Resources最新文献

{"title":"Pore structure and gas content evaluation of coal-rock gas using well log data","authors":"Fei Zhao ,&nbsp;Jin Lai ,&nbsp;Lu Xiao ,&nbsp;Zongli Xia ,&nbsp;Zhongrui Wang ,&nbsp;Ling Li ,&nbsp;Bin Wang ,&nbsp;Guiwen Wang","doi":"10.1016/j.uncres.2025.100247","DOIUrl":"10.1016/j.uncres.2025.100247","url":null,"abstract":"<div><div>The pore structure of coal significantly affects the adsorbability, desorption, and seepage behavior of coal-rock gas. This study firstly represents a comprehensive assessment of pore structure and fractal dimension characteristics for the low-medium rank coal of the Jurassic-Triassic, Kuqa Depression, Tarim Basin, China, with a focus on their implications for methane adsorption capacity. In addition, integration the laboratory and well log data (CMR_NG) are used to evaluate gas bearing property of coal seams. Coal samples of low-medium rank were analyzed using low-pressure CO₂ adsorption (LP-CO₂GA), low-temperature N₂ adsorption (LT-N₂GA), mercury intrusion porosimetry (MIP), nuclear magnetic resonance (NMR), and scanning electron microscopy (SEM). The adsorption-desorption isotherms of coal samples are predominantly Type H3 and H4, indicating parallel plate pores and ink-bottle or narrow slit pores, which promote coal-rock gas enrichment. Micropores, responsible for most specific surface area (SSA), dominate the pore structure, alongside macropores with two T₂ peaks. Fractal dimensions (D₁, D₂ from LT-N₂GA; D₃, D₄ from NMR) reflect pore characteristics, where higher D₁ and D₂ correlate positively with SSA and total pore volume (TPV) of micropores and mesopores. Langmuir volume (V_L) correlates with D₃, indicating greater adsorption capacity, while lower D₄ suggests better connectivity and permeability. Furthermore, industrial components and gas bearing property are evaluated by using conventional well log and CMR_NG log. The favorable coal reservoir exhibits high fixed carbon content, a broad T₁ spectrum, and bimodal T₂ distributions from CMR_NG, indicating both adsorbed and free gas with high coal-rock gas content. These insights could enhance understanding of low-medium rank coal reservoir pore structure and fractal dimension characteristics, as well as their influence on methane adsorption, gas bearing property and seepage capacity.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100247"},"PeriodicalIF":4.6,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An overview of hydrogen in the subsurface","authors":"Barry Jay Katz","doi":"10.1016/j.uncres.2025.100245","DOIUrl":"10.1016/j.uncres.2025.100245","url":null,"abstract":"<div><div>Hydrogen is the most abundant element in the Universe. As a fuel and energy carrier it has had several false starts. Today it is thought to be on track to become a part of the future energy mix, with a multi-fold increase in usage estimated over the next 25 years. As this future develops earth science will play a role in both storage and production/manufacturing. Large-scale utilization of hydrogen will require subsurface storage. Currently, subsurface storage has largely focused on massive salt or salt diapirs. This is geographically limiting. To broaden storage opportunities bedded evaporites and porous media will need to play a role. Each subsurface storage type has multiple issues to be examined including the effects of the frequency and magnitude of drawdown, impact of microbial processes, reservoir and seal (caprock) diagenesis, and potential hydrogen losses. Storage space for hydrogen in porous media could potentially compete with CO₂ storage. On the production side there is growing interest in natural (white) hydrogen, the availability of water, especially freshwater, for electrolysis (green hydrogen), and the potential for anthropogenic (orange and gold) hydrogen in the subsurface. With respect to natural hydrogen, mechanisms and rates of generation are being investigated as is the common association with helium. Understanding the natural hydrogen system, including the trap, overlaps with issues of storage that focus on the reservoir and seal. The commercial subsurface stimulation of hydrogen generation is also being examined with respect to mechanisms and rates, with an aim of making it competitive with surface manufacturing. Large-scale production of natural hydrogen is yet to be established.One may ultimately view the current state of the subsurface hydrogen story being comparable to that of the initial stages of unconventional gas production more than two decades ago, with much still to be learned.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100245"},"PeriodicalIF":4.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical simulation of CO2 sequestration potential in deep saline aquifers and salt caverns in the middle Yangtze River region: Insights from the Qingjiang Basin","authors":"Shuanglong Zhang ,&nbsp;Fuqiang Xiao ,&nbsp;Yongjun Zou ,&nbsp;Sijian Zheng ,&nbsp;Yuchen Tian","doi":"10.1016/j.uncres.2025.100244","DOIUrl":"10.1016/j.uncres.2025.100244","url":null,"abstract":"<div><div>Deep saline aquifers are widely recognized as one of the most promising and scalable options for geological CO₂ storage within CCUS strategies due to their large capacity and widespread distribution. Numerical modeling plays a critical role in predicting CO₂ migration, evaluating injection safety, and optimizing site design, offering essential insights for the practical deployment of CO₂ sequestration. This study presents a comprehensive two-dimensional numerical investigation of CO₂ injection and migration in deep saline aquifers of the Qingjiang Basin, situated in the middle reaches of the Yangtze River. Using COMSOL Multiphysics, we developed a fully coupled flow–geomechanical model that integrates multiphase Darcy flow, mass conservation, capillary-buoyancy effects, and linear poroelastic deformation. The model domain-an axisymmetric slice extending 5.5 km laterally and 100 m vertically at a depth of 3 km was discretized with nonstructured triangular meshes refined to sub-meter scale near the injector to resolve steep pressure and saturation gradients. Transient simulations reveal a rapid pressure rise up to ∼30 MPa within 0.1 year, followed by gradual equilibration as CO₂ displaces brine. The resulting plume is characterized by a high-saturation core adjacent to the wellbore and steep radial decay, controlled by the interplay of buoyancy and capillary resistance. Sensitivity analyses demonstrate that reservoir permeability (1 × 10⁻¹⁵–1 × 10⁻¹² m²) and capillary entry pressure critically influence both plume spread and pressure footprint, underscoring the need for accurate petrophysical characterization. Our findings confirm the efficacy of the Qingjiang Basin's thick seal rocks and stable tectonic setting for CO₂ containment and provide guidance on mesh design, solver configuration, and coupling strategies for future three-dimensional, heterogeneous, reactive-transport simulations.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100244"},"PeriodicalIF":4.6,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid renewable energy systems for seawater-based green hydrogen in Egyptian coastal zones: A case study","authors":"Mohamed Osman Atallah ,&nbsp;Abdallah M. Elsayed ,&nbsp;Mohammed H. Alqahtani ,&nbsp;Abdullah M. Shaheen","doi":"10.1016/j.uncres.2025.100239","DOIUrl":"10.1016/j.uncres.2025.100239","url":null,"abstract":"<div><div>As the world accelerates its transition toward net-zero emissions, green hydrogen production via seawater electrolysis presents a promising and innovative pathway for clean energy generation and ensuring long-term energy sustainability. This study investigates the feasibility of green hydrogen production through seawater electrolysis powered by renewable energy sources in four Egyptian coastal cities: New Alamein, El Tor, New Port Said (Salam), and Suez. A hybrid system comprising photovoltaic panels, wind turbines, batteries, a proton exchange membrane electrolyzer, hydrogen storage tanks, and diesel generators is proposed and evaluated under four distinct scenarios. Both stand-alone and grid-connected configurations are evaluated using HOMER Pro software to optimize system design based on techno-economic and environmental criteria. Multiple scenarios, incorporating varying numbers of wind turbines (15, 20, and 50), are assessed for each location. The results are compared depending on energy generation, hydrogen production, storage capacity, excess electricity, and key financial indicators, including net present cost, levelized cost of energy, and levelized cost of hydrogen. The findings indicate that Scenario Four, which achieves the lowest hydrogen production cost of 0.177 $/kg, demonstrates the most cost-effective performance. This result remains consistent across all studied locations and operating conditions, thereby highlighting the robustness and adaptability of the proposed hybrid system. This research demonstrates the technical viability of integrating renewable energy with seawater electrolysis for sustainable hydrogen production, contributing to Egypt's transition toward a low-carbon energy system and supporting the objectives of its national hydrogen strategy.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100239"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review on traveling wave-based fault assessment and enhanced protection of distribution networks in smart grid scenario","authors":"Chinmayee Biswal ,&nbsp;Binod Kumar Sahu ,&nbsp;Pravat Kumar Rout ,&nbsp;Manohar Mishra","doi":"10.1016/j.uncres.2025.100242","DOIUrl":"10.1016/j.uncres.2025.100242","url":null,"abstract":"<div><div>Transitioning from traditional power systems to advanced smart grid and microgrid systems is crucial for meeting increasing energy demands and ensuring a reliable and secure power supply. Integrating renewable energy sources, electric vehicle charging, power electronics, and nonlinear loads complicates the system dynamics and introduces operational uncertainties. Furthermore, this poses challenges to system protection, fault detection and location, control, and power quality. Factors such as dynamic system behaviour, reduced inertia, bidirectional power flow, and a low short-circuit ratio exacerbate these challenges. This paper reviews advanced protection schemes and fault detection, estimation, and location techniques, with a focus on traveling wave (TW) technology. It provides a comprehensive overview of TW-based methods in distribution network protection, highlighting significant progress in fault detection, assessment, and location. In addition, it identifies existing research gaps and future development directions, including operational challenges that arise during and after implementation. The insights from this review are invaluable for researchers working to enhance power system protection. It aims to facilitate the development of innovative protection schemes to address the evolving challenges of the power grid. This work is instrumental in advancing state-of-the-art power system protection and is pivotal for the grid's future stability and efficiency.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100242"},"PeriodicalIF":4.6,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A proxy-assisted multi-layer cooperative optimization framework for economic shale gas field development","authors":"Huijun Wang ,&nbsp;Zhiguo Shu ,&nbsp;Taohua He ,&nbsp;Jiyong Liu ,&nbsp;Juan Teng ,&nbsp;Gaofeng Zou ,&nbsp;Liu He ,&nbsp;Shuangfang Lu ,&nbsp;Jiayi He ,&nbsp;Yuanzhen Zhou ,&nbsp;Yuchen Yao","doi":"10.1016/j.uncres.2025.100238","DOIUrl":"10.1016/j.uncres.2025.100238","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Shale gas development optimization faces significant challenges due to computational constraints when handling complex parameter interactions across different scales. Conventional optimization methods are limited by their inability to efficiently process high-dimensional parameter spaces, excessive computational demands that prevent field-scale application, and failure to simultaneously consider both technical performance and economic outcomes. The fundamental objective of this research is to maximize field-scale Net Present Value (NPV) through systematic optimization of engineering parameters under given geological constraints, transforming the complex field development decision-making process into a quantitative mathematical problem of maximizing the NPV objective function while determining the optimal corresponding engineering parameters. This paper introduces a novel proxy-assisted multi-layer cooperative optimization (PAMLCO) framework that systematically addresses these limitations through hierarchical problem decomposition and multi-scale parameter integration. The PAMLCO framework transforms the complex field optimization problem into three hierarchically connected subproblems: (1) an outer layer focuses on field-scale optimization, determining global parameters including fracture half-length (FHL), fracture conductivity (FC), cluster spacing (CS) and target A coordinate; (2) a middle layer optimizes well column parameters such as horizontal section length (HSL), well number and target B coordinate; and (3) an inner layer optimizes single well parameters such as the length from wellhead to target A and the drilling platforms connected to each well. Unlike conventional divide-and-conquer methods that often lead to locally optimal solutions, PAMLCO implements a bidirectional information exchange mechanism between adjacent optimization layers—higher-level optimization results provide constraint boundaries for lower-level optimization, while lower-level optimal solutions guide the evolution direction of higher-level parameters. The key innovation of the PAMLCO framework lies in its ability to efficiently handle the coupling effects between microscopic fracture parameters and macroscopic field development strategies while considering reservoir heterogeneity and surface constraints. At its core, a high-precision Gaussian Process Regression (GPR) proxy model (R&lt;sup&gt;2&lt;/sup&gt; = 0.9999, RMSE = 0.0132) coupled with a genetic algorithm (GA) accelerates the optimization process over 2400 times compared to traditional numerical simulation methods while maintaining solution accuracy within 2 % of exhaustive approaches. This computational efficiency breakthrough makes comprehensive field-scale optimization practically feasible, enabling the integration of complex technical and economic factors in real-world decision-making processes. Applied to the Sichuan Basin, the PAMLCO framework achieved accumulated gas production of 68.58 × 10&lt;sup&gt;8&lt;/sup&gt; ","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100238"},"PeriodicalIF":4.6,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomass-based green ammonia: Pathways, technologies, and sustainability for a carbon-neutral future","authors":"Khemlata Soni ,&nbsp;Pranay Rajendra Lanjekar ,&nbsp;Narayan Lal Panwar","doi":"10.1016/j.uncres.2025.100241","DOIUrl":"10.1016/j.uncres.2025.100241","url":null,"abstract":"<div><div>Ammonia plays a pivotal role in the global economy, serving as a hydrogen carrier, carbon-free fuel, and a key component in nitrogen fertilizers that enhance agricultural productivity. However, the conventional Haber-Bosch (H-B) process, which relies on methane (natural gas) as a source of hydrogen, contributes approximately 2 % of global CO₂ emissions, underscoring the need for sustainable alternatives. This review explores biomass as a renewable feedstock for green ammonia production, focusing on thermochemical and biochemical conversion processes through two pathways: (1) Indirect, using renewable based hydrogen from steam methane reforming of syngas, bio-oil, biogas and glycerol obtained from biomass gasification, pyrolysis, anaerobic digestion and transesterification processes, respectively, and (2) Direct, converting nitrogen-rich biomass into ammonia through catalytic or laser-driven pyrolysis, or recovering ammonia from biohydrogen or biogas effluents via stripping. While the biochemical process has higher technology readiness, thermochemical methods, especially biomass steam gasification, are more widely used due to higher green hydrogen yields. Novel integrations, such as process simulations, cascaded designs, chemical looping, and external energy sources like solar, biomass, wind, or hybrid systems, enhance ammonia production. Green ammonia reduces CO₂ emissions by approximately 65–66 % and is less costly than conventional processes, depending on system configuration and biomass feedstock. This review examines technological advancements, economic feasibility, and environmental impacts, concluding that biomass-based green ammonia is essential for sustainable energy systems. While earlier reviews have provided broad overviews of green ammonia production, they often overlook the specific potential of biomass-based routes. This review addresses that gap by systematically analyzing biomass-driven pathways, along with their technological, economic, and environmental dimensions, to underscore the distinctive contribution of biomass to sustainable ammonia production.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100241"},"PeriodicalIF":4.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental validation and enhanced thermal prediction of a shallow solar pond using artificial neural network–based model predictive control for real-time optimization under multiple heat extraction modes","authors":"Abdelkrim Terfai ,&nbsp;Younes Chiba ,&nbsp;Mounir Zirari ,&nbsp;Mohamed Najib Bouaziz","doi":"10.1016/j.uncres.2025.100240","DOIUrl":"10.1016/j.uncres.2025.100240","url":null,"abstract":"<div><div>This study presents the experimental validation and enhanced thermal modeling of a Shallow Solar Pond (SSP) operating under three distinct heat extraction modes: direct, open cycle, and closed cycle. A custom-designed SSP, insulated and equipped with double-glazing and a PVC heat exchanger and black-painted bottom, was monitored under clear-sky conditions. 14 Artificial Neural Network (ANN) configurations were trained, with the optimal Bayesian Regularization-based model (two hidden layers, 15 neurons) achieving exceptional predictive accuracy (R² = 0.99919, RMSE = 32.7580 %, MRE = 0.62 %) for temperatures across all system components and operational modes. The ANN model effectively captured complex nonlinear dynamics, including transient heating and cooling phases. The integration of this ANN with a Model Predictive Control (MPC) framework enabled real-time optimization of the fluid flow rate in the closed-cycle mode, which was identified as the most efficient configuration. The MPC-ANN strategy reduced the outlet temperature tracking error by over 50 % (MAE = 1.42 °C vs. 2.97 °C without MPC), demonstrating superior thermal stability and adaptive control under fluctuating solar irradiance. This work confirms the closed-cycle SSP's superiority for stable energy delivery and establishes a robust ANN-MPC framework for real-time operational optimization of solar thermal systems.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100240"},"PeriodicalIF":4.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A scalable forecasting framework for PV systems using hyper-tuned regressors and environmental data","authors":"Mohamed A. Atiea ,&nbsp;Ali M. El-Rifaie ,&nbsp;Ghareeb Moustafa ,&nbsp;Abdullah M. Shaheen","doi":"10.1016/j.uncres.2025.100236","DOIUrl":"10.1016/j.uncres.2025.100236","url":null,"abstract":"<div><div>Forecasting photovoltaic (PV) power output is essential for reliable grid integration, operational planning, and supporting the global transition toward renewable energy. This paper proposes an integrated machine learning framework that improves prediction accuracy through systematically designed preprocessing, model selection, and advanced hyperparameter optimization. Using a high-resolution dataset from the Sharda University PV system, 13 regression models, including ensemble methods and neural networks, are tested and compared with the aim of maximizing generalizability and predictive performance. Performance gains are achieved through structured hyperparameter optimization using Randomized Search Cross-Validation (RSCV) and Grid Search Cross-Validation (GSCV), where the Random Forest Regressor achieved an R² of 0.9561 before tuning and 0.9893 after tuning, representing the highest improvement. Gradient Boosting Regressor and K-Nearest Neighbors also benefited from hyperparameter optimization. A comparative study with benchmark approaches shows that the optimized models in this work are superior in both predictive accuracy and computational efficiency. The proposed framework is scalable, as it can be adapted to different PV datasets while requiring fewer computational resources than deep learning methods, thereby bridging the gap between traditional machine learning approaches and practical energy management systems.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100236"},"PeriodicalIF":4.6,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boosting Thermoelectric Power Generation with Black Body Coatings and Oil Thermal Storage tank","authors":"Jalal Faraj ,&nbsp;Georges El Achkar ,&nbsp;Mohammad Hammoud ,&nbsp;Rani Taher ,&nbsp;Samer Ali ,&nbsp;Maya Julian ,&nbsp;Chafic Salame ,&nbsp;Mahmoud Khaled","doi":"10.1016/j.uncres.2025.100237","DOIUrl":"10.1016/j.uncres.2025.100237","url":null,"abstract":"<div><div>Thermoelectric generators (TEGs) are a sustainable way to transform waste heat into electricity, with applications including waste heat recovery, renewable energy, and industrial exhaust gas systems. Despite their promise, TEGs' modest power output limits their widespread implementation. This paper describes an engineering solution for improving TEG performance by using solar energy as the major heat source and including an oil tank as a thermal energy storage device. The change entails transforming the hot surface of commercial and standard TEG modules into a blackbody surface to increase heat absorption. Unlike traditional settings, this study investigates the combined impact of black-coated surfaces and an oil tank on the hot side to optimize heat input. This technique provides a cost-effective and ecologically responsible option for increasing TEG efficiency. To proceed, a regular commercial TEG module, a TEG module with black body film, and a TEG module with both black body film combined with an oil tank are studied under the same conditions. The output power density and temperature differential of each arrangement were measured and compared. Replacing the white surface on the hot side of the TEG module with a blackbody surface boosted power density by 1500 mW/m², reaching 2250 mW/m². Adding an oil tank to the black surface increased the output to 3500 mW/m². These enhancements emphasize the potential of TEGs to greatly boost power output, notably in solar-powered systems and industrial waste heat recovery applications aiming at sustainable energy production.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"8 ","pages":"Article 100237"},"PeriodicalIF":4.6,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}