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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13

Clinical effects of 3D printing-assisted posterolateral incision in the treatment of ankle fractures involving the posterior malleolus

Objective To explore the clinical outcomes of a 3D printing-assisted posterolateral approach for the treatment of ankle fractures involving the posterior malleolus. Methods A total of 51 patients with ankle fractures involving the posterior malleolus admitted to our hospital from January 2018 to December 2019 were selected. The patients were divided into 3D printing group (28 cases) and control group (23 cases). 3D printing was performed for ankle fractures, followed by printing of a solid model and simulation of the operation on the 3D model. The operation was then performed according to the preoperative plan, including open reduction and internal fixation via the posterolateral approach with the patient in the prone position. Routine x-ray and CT examinations of the ankle joint were performed, and ankle function was evaluated using the American Foot and Ankle Surgery Association (AOFAS) ankle-hindfoot score. Results All patients underwent x-ray and CT examinations. All fractures healed clinically, without loss of reduction or failure of internal fixation. Good clinical effects were achieved in both groups of patients. The operation time, intraoperative blood loss and intraoperative fluoroscopy frequency in the 3D printing group were significantly less than those in the control group ( p < 0.05). There was no significant difference between the two groups in the anatomical reduction rate of fractures or the incidence of surgical complications ( p > 0.05). Conclusion The 3D printing-assisted posterolateral approach is effective in the treatment of ankle fractures involving the posterior malleolus. The approach can be well planned before the operation, is simple to perform, yields good fracture reduction and fixation, and has good prospects for clinical application.

Zheng, Hongming↗

Entropy-Assisted Quality Pattern Identification in Finance

Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a formidable challenge. In this paper, we propose an entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behavior over time. We ground our approach in the premise that historical patterns, when accurately clustered and pruned, can yield substantial predictive power for short-term price movements. To achieve this, we incorporate an entropy-based measure as a proxy for information gain: patterns that lead to high one-sided movements in historical data yet retain low local entropy are more “informative” in signaling future market direction. Compared to conventional clustering techniques such as K-means and Gaussian Mixture Models (GMMs), which often yield biased or unbalanced groupings, our approach emphasizes balance over a forced visual boundary, ensuring that quality patterns are not lost due to over-segmentation. By emphasizing both predictive purity (low local entropy) and historical profitability, our method achieves a balanced representation of Buy and Sell patterns, making it better suited for short-term algorithmic trading strategies. This paper offers an in-depth illustration of our entropy-assisted framework through two case studies on Gold vs. USD and GBPUSD. While these examples demonstrate the method’s potential for extracting high-quality patterns, they do not constitute an exhaustive survey of all possible asset classes.

Physics↗

Self-Cleaning Highly Porous TiO 2 Coating Designed by Swelling-Assisted Sequential Infiltration Synthesis (SIS) of a Block Copolymer Template

Photocatalytic self-cleaning coatings with a high surface area are important for a wide range of applications, including optical coatings, solar panels, mirrors, etc. Here, we designed a highly porous TiO 2 coating with photoinduced self-cleaning characteristics and very high hydrophilicity. This was achieved using the swelling-assisted sequential infiltration synthesis (SIS) of a block copolymer (BCP) template, which was followed by polymer removal via oxidative thermal annealing. The quartz crystal microbalance (QCM) was employed to optimize the infiltration process by estimating the mass of material infiltrated into the polymer template as a function of the number of SIS cycles. This adopted swelling-assisted SIS approach resulted in a smooth uniform TiO 2 film with an interconnected network of pores. The synthesized film exhibited good crystallinity in the anatase phase. The resulting nanoporous TiO 2 coatings were tested for their functional characteristics. Exposure to UV irradiation for 1 h induced an improvement in the hydrophilicity of coatings with wetting angle reducing to unmeasurable values upon contact with water droplets. Furthermore, their self-cleaning characteristics were tested by measuring the photocatalytic degradation of methylene blue (MB). The synthesized porous TiO 2 nanostructures displayed promising photocatalytic activity, demonstrating the degradation of approximately 92% of MB after 180 min under ultraviolet (UV) light irradiation. Thus, the level of performance was comparable to the photoactivity of commercial anatase TiO 2 nanoparticles of the same quantity. Our results highlight a new robust approach for designing hydrophilic self-cleaning coatings with controlled porosity and composition.

36 MATERIALS SCIENCE↗

Dynamic Electric Field Assisted CO 2 Methanation

Energy-efficient advanced chemical reactions are essential for accelerating the growth of hydrocarbon economy. Sabatier reaction stands out for its potential to effectively transform carbon dioxide into valuable hydrocarbons and is an asset for long-duration Mars missions. This study explores a novel catalytic approach that harnesses electric field-assisted catalysis to substantially enhance the efficiency of the Sabatier reaction. Application of a dynamically perturbed electric field at 1000 Hz resulted in remarkable enhancements, increasing methane formation rates by over 100% at 350 °C and by 74% at 400 °C. Post-reaction catalyst characterization further revealed reduced blockage of active catalytic surface area under the applied electric field, emphasizing improved catalytic longevity and sustained activity. These results underscore the potential of tailored electric field waveforms to dynamically modulate elementary reaction kinetics and surface processes, positioning electric field-assisted catalysis as a transformative strategy for energy-efficient, cost-effective chemical manufacturing and energy conversion technologies.

42 - ENGINEERING↗

Operator Insights and Usability Evaluation of Machine Learning Assistance for Power Grid Contingency Analysis

Introducing machine learning (ML) assistance into any established process comes with adoption barriers, including entrenched procedures, technological and human readiness levels, human-machine trust, and work culture resistance to change. These barriers are even greater in critical operations such as operating a national or regional power grid, in which both regulatory frameworks and the importance of maintaining reliability levels causes additional resistance to the adoption of new computational support. Developers of future systems and job aides must consider not only technical aspects, but also whether new systems are usable by power system operators. This work presents the methodology and results of a study to evaluate the usability and readiness of a prototype recommender system for power grid contingency analysis. We explore operator cognitive load and evaluate operator performance when solving a collection of scenarios both with and without recommender assistance. We also examine operator trust in the system. We report insights gained on the readiness of the system using a collection of evaluation techniques.

Human-Machine Teaming, Power Systems, usability ev↗

Lahaina Energy Partnership Community Workshop: Technical Assistance Task Updates and Discussion [Slides]

The Lahaina Energy Partnership (LEP) is an initiative funded by the U.S. Department of Energy (DOE) to support energy planning and rebuilding efforts in Hawaii's historic town of Lahaina on Maui as the community recovers from a devastating fire on August 8, 2023, with technical assistance provided by NLR. This presentation provides an update on NLR's technical assistance efforts for May 2026.

14 SOLAR ENERGY↗

Effect of Catalyst Pretreatment on Methane Conversion under Microwave-assisted and Conventional Thermal Methods

The presentation was delivered from work performed in NETL's Upcycling of Associated Natural Gas FWP Task 4 Benzene, Toluene, Xylene Synthesis via Microwave-assisted catalyst. The objective of this project is to develop a modular, microwave-assisted reactor to upcycle flare gas into valuable chemicals. The presentation discusses important work researchers have performed to compare the pre-treatment of a benchmark Mo/ZSM-5 catalyst under microwaves to traditional thermal heating. Pre-treatment is required to enable to catalyst to produce benzene. This study provided insights into how the exposure impacts the structure and activity of the catalyst and will be used to help design better catalysts.

Abdelsayed, Victor↗

A Machine Learning-Assisted Framework to Control Thermally Anisotropic Building Envelopes in Residential Buildings

To curb the energy consumption of buildings and their related CO2 emissions, Oak Ridge National Laboratory (ORNL) has developed the thermally anisotropic building envelope (TABE) —a multi-layer design comprising insulation materials and metal foils connected to thermal loops. In this study, a machine learning-assisted framework was developed to control the TABE in residential buildings to reduce the computation load for future optimal rule-based control and application. First, a 2D finite element model was established in COMSOL to calculate the hourly heat flux through exterior walls installed with the TABE. Then, TABE wall heat fluxes were simulated for various given indoor and outdoor boundary conditions, as well as thermal loops fluid temperatures and flow rates. Since the finite element simulations are computationally expensive, an artificial neural network (ANN) was then trained to use as a proxy of the finite element (COMSOL) modeling. Finally, the trained ANN model was coupled with the EnergyPlus model to predict the energy consumption of a US Department of Energy prototype single-family house installed with the TABE. An optimal simple rule-based control was determined from predefined rules for a case study. The results demonstrate that the developed machine learning–assisted framework can reduce 99.9% of the computation time while efficiently managing residential building energy for installed TABE walls.

Shen, Zhenglai↗

Devices and methods for performing shear-assisted extrusion, extrusion feedstocks, extrusion processes, and methods for preparing metal sheets

Devices and methods for performing shear-assisted extrusion processes for forming extrusions of a desired composition from a feedstock material are provided. The processes can use a device having a scroll face having an inner diameter portion bounded by an outer diameter portion, and a member extending from the inner diameter portion beyond a surface of the outer diameter portion.Extrusion feedstocks and extrusion processes are provided for forming extrusions of a desired composition from a feedstock. The processes can include providing a feedstock having at least two different materials and engaging the materials with one another within a feedstock container.Methods for preparing metal sheets are provided that can include preparing a metal tube via shear assisted processing and extrusion; opening the metal tube to form a sheet having a first thickness; and rolling the sheet to a second thickness that is less than the first thickness.

Whalen, Scott A.↗

Shear assisted extrusion process

A shear assisted extrusion process for producing cladded materials wherein a cladding material and a material to be cladded are placed in sequence with the cladded material positioned to contact a rotating scroll face first and the material to be cladded second. The two materials are fed through a shear assisted extrusion device at a preselected feed rate and impacted by a rotating scroll face to generate a cladded extrusion product. This process allows for increased through wall strength and decreases the brittleness in formed structures as compared to the prior art.

Joshi, Vineet V.↗

System and method for simulation-assisted additive manufacturing involving estimating anisotropic deformation

A simulation-assisted additive manufacturing system and method for generating an anisotropic compensation to account for non-uniform deformation due to additive manufacturing and service loading. The predicted deformation may not be fully defined. The present disclosure provides a system and method for estimating the missing deformation data through regression analysis. The present disclosure also provides an integrated framework where the various simulated-assisted design modules are configured for two-way communication and sharing access to changes to the model.

Kim, Seokpum↗

Microwave-Assisted Syngas Cleanup: Catalytic Reforming of Gasifier Tar Using a Low-Cost Iron Catalyst

The microwave-assisted gasification of plastic wastes to produce hydrogen-rich syngas is an attractive energy-saving plastic upcycling route, and the addition of biomass could improve the quality of the syngas produced; however, it could also increase the tar yield, which is an undesired, secondary product in this process. The presence of tars could result in downstream lines blockage, reactor down time and costly maintenance. Therefore, reducing or removing tar is desired. Due to its chemical complexity, toluene, which is one of the main tar constituents, could be used as a model tar compound. In this work, the microwave-assisted catalytic dry reforming of toluene was studied using Fe/Al2O3 as a catalyst, under CO2 at different reaction temperatures. The toluene reforming reaction was conducted using microwave and conventional thermal reactors. The results showed that under microwave irradiation, higher CO2 and toluene conversions, as well as better hydrogen yield can be observed compared to conventional toluene reforming at the same reaction temperature. The catalyst stability test was also investigated. Three reaction pathways were observed during microwave reaction.

Bai, Xinwei↗

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives.

access↗

Empowering Geothermal Research: The Geothermal Data Repository's New AI Research Assistant

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has integrated a Large Language Model (LLM) with the metadata and supporting documents associated with GDR datasets to create an Artificially Intelligent (AI) research assistant. By leveraging work done to make GDR metadata machine-readable and an open-source LLM integration model called the Energy Language Model, developed by the National Renewable Energy Laboratory, AskGDR serves as a virtual research assistant to GDR users. It provides answers to a variety of user-provided questions using natural language processing and generative machine learning. Users can get answers to questions about specific datasets, including inquiries about the equipment, assumptions and methodologies used in the origination of the data; or more abstract questions, such as the applicability of data to specific research fields. AskGDR improves the discoverability of geothermal data by helping guide users to datasets beyond simple keyword searches. It enables users to find data based on properties of the data, discover information contained within supporting documents, and explore data from projects related to their research objectives. This paper will outline the development, integration, output, and efficacy of the AskGDR LLM, including adherence to scientific rigor through improvements designed to increase the accuracy of generated answers, avoid speculation, and provide proper references for all resources used.

access↗

Shear-assisted extrusion assemblies and methods

Shear-assisted extrusion assemblies are provided. The assemblies can include a billet containing assembly containing a billet comprising a billet outer material and a billet inner material in at least one cross-section; a tool operably engaged with the billet; an extrudate receiving channel configured to receive extrudate from the tool, wherein the extrudate comprises extruded outer material and extruded inner material in at least one cross-section, the extruded outer material being the same material as the billet outer material, and the extruded inner material being the same as the billet inner material. Methods for producing multi-material shear-assisted extrudate are also provided.

Komarasamy, Mageshwari↗

Low-Temperature Plasma Assisted Kinetics Study of Ethanol

Abstract: Non- equilibrium plasma assisted kinetics of ethanol at 0.5 atm over a temperature range of 523-1203 K were studied at stoichiometric conditions by using a plasma flow reactor (PFR). The effects of plasma chemistry on fuel and its influence on neutral chemistry is decoupled with both experimental and modelling efforts. Enhanced reactivity was observed experimentally in both plasma-assisted oxidation and pyrolysis cases with fuel consumption beginning at temperatures as low as 523 K. Absolute fuel consumption was observed at temperatures nearly 200 K earlier than pure thermal reactions highlighting the effectiveness of non-equilibrium plasma to promote reactivity. Modelling results illustrated the effect of electron impact reactions towards accelerating fuel consumption and promoting low temperature chemistry by generating excited state N2 and reactive O and OH radicals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE provides targeted technical assistance for manufacturers pursuing energy and resource efficiency

The U.S. Department of Energy (DOE) is committed to providing the industrial sector with resources and funding to support the development of innovative new technologies and processes. Previously, DOE’s Advanced Manufacturing Office was the front door of the department for many manufacturers. This office focused on two main missions: driving innovation in manufacturing technologies, and reducing energy and emissions related to manufacturing. These missions complemented each other in many ways, but as attention in these areas grew, so too did the need for specialization. In October 2022, the Advanced Manufacturing Office was reorganized into two new offices: the Advanced Materials and Manufacturing Technologies Office (AMMTO) and the Industrial Efficiency and Decarbonization Office (IEDO). For emissions-heavy industries, such as ceramics and glass, the latter office provides research and development funding, technical assistance, and demonstration support to help manufacturers along their journey to reduce emissions and increase resource efficiency. This article overviews the portfolio of resources applicable to ceramic and glass manufacturers through IEDO, including programs that were portioned into this office during the split and new offerings that were added since then. These programs and resources include energy management support, technology-specific guidance, and in-plant technical assistance.

Source record↗

Synthesis of High-Quality Mg-MOF-74 Thin Films via Vapor-Assisted Crystallization

The unique features of metal-organic frameworks (MOFs), such as their large surface areas and diversity of structures, makes them suitable to a broad range of applications. One of the most critical enabling technologies for implementing MOF films is the preparation of dense and continuous films that would maximize the performance of the configurations. While formation of crystalline Mg-MOF-74 thin films presents significant challenges, demonstrating large-scale coatings of the MOF, which exhibits the highest CO2 uptake among MOFs at 1 bar and 25 °C, would be particularly beneficial for CO2- related sensing applications. In this work, we demonstrate for the first time high-quality Mg-MOF-74 films synthesized via a vapor-assisted crystallization (VAC) process. The VAC process described herein produces dense and highly crystalline layers of Mg-MOF-74 with a low coefficient of variation (COV) of film thickness below 7%. We first optimized a precursor solution for the VAC process, and then investigated the effects of synthesis temperature, time and droplet volume on the growth, crystallinity and thickness of Mg-MOF-74 films. The porosity of the film was assessed by measuring the CO2 uptake at room temperature and 1 bar. The obtained Mg-MOF-74 films possess a well-defined microporosity, as deduced from CO2 adsorption studies via quartz crystal microbalance (QCM) and comparison with bulk Mg MOF-74 reference data. Furthermore, CO2 cyclic adsorption-desorption experiments on the Mg-MOF-74

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗