SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Tuning the accelerator during operational hours is a tedious yet essential aspect of managing any experimental facility. This process significantly reduces the beam time available for experimenters, as diagnosing issues and making corrections can take hours. Automating or facilitating the normal beam line tuning process would be highly beneficial.
Covalent organic frameworks (COFs) are a type of porous, extended structure material which has demonstrated utility in numerous applications, including sensing and separations. Judicious choice of the linker and node not only fine tune the size of the framework, but also the functionality. We seek to tailor COF materials for applications in gas capture and electrochemical sensing. Herein, we demonstrate the material properties of COFs can be fine-tuned via post-synthetic metal cation doping of the parent structures. We have synthesized several COF structures with varying linkers which allow for the incorporation of metal cations. Structures incorporating Zn 2+ , Mn 2+ , and Cu 2+ have demonstrated utility in improving the CO 2 uptake properties of the COFs, while Ag + doped structures show potential as electrochemical sensors for chloride anions.
Various matching methods for tuning Drift Tube Linacs are overviewed. Special emphasis is on the methods utilizing signature phase scans with single and pairs of Beam Position Monitors (BPM) placed inside or outside of the tuned-up cavity, and that using a combination of phase scans with energy scans.
Campaign II and III of the Floating Offshore-wind Controls Advanced Laboratory Experimental Program (FOCAL) aimed to generate a dataset enabling the validation of the performance and loads of a scaled hull, with and without structural hull control. The floating platform was subjected to a variety of wave environments and controlled using tuned-mass dampers (TMDs) tuned to two of the systems natural frequencies (Platform Pitch and Tower-bending). The floating platform is fully instrumented to record a variety of parameters in real time such as platform dynamics, accelerations, and loads at different points in the structure. The test data considered was generated at the University of Maine's Harold Alfond Wind and Wave (W2) testing facility. This testing was focused only on validation of wave loading, and wind conditions were not considered. As such the platform does not support a working turbine, and instead supports a structure designed to have the same mass properties as the 1:70 IEA 15MW Reference turbine. The Load Cases (LC) considered in this testing campaign are as follows: LC 1.X - Platform Static Offset (TMD off); LC 2.X - Platform Free-decays (TMD off); LC 3.X - Wave Cases (Regular Wave, Irregular Wave, Pink Noise Wave) with and without TMDs active. Detailed properties on the model system are found in the following reference: Lenfest E., Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental Program - Campaigns 2 and 3: 1:70 Model-scale Testing of the IEA-Wind 15MW Reference Turbine and the VolturnUS-S Hull. UMaine ASCC Report Number 23-56-1183.
Low-Rank Adaptation (LoRA) has become a widely used method for parameter-efficient fine-tuning of large-scale, pre-trained neural networks. However, LoRA and its extensions face several challenges, including the need for rank adaptivity, robustness, and computational efficiency during the fine-tuning process. We introduce GeoLoRA, a novel approach that addresses these limitations by leveraging dynamical low-rank approximation theory. GeoLoRA requires only a single backpropagation pass over the small-rank adapters, significantly reducing computational cost as compared to similar dynamical low-rank training methods and making it faster than popular baselines such as AdaLoRA. This allows GeoLoRA to efficiently adapt the allocated parameter budget across the model, achieving smaller low-rank adapters compared to heuristic methods like AdaLoRA and LoRA, while maintaining critical convergence, descent, and error-bound theoretical guarantees. The resulting method is not only more efficient but also more robust to varying hyperparameter settings. We demonstrate the effectiveness of GeoLoRA on several state-of-the-art benchmarks, showing that it outperforms existing methods in both accuracy and computational efficiency.
The Axion Dark Matter Experiment (ADMX) searches for axions by converting them into detectable photons using resonant microwave cavities at cryogenic temperatures. A precise tuning system is needed to adjust cavity frequency without adding thermal load or electromagnetic interference. This project developed and tested a 1000 to 1 gear reduction system made from PEEK, a low thermal conductivity plastic with good dimensional stability and self lubrication at low temperatures. A compound gear train design of five 3 to 1 stages and one 4 to 1 stage achieves high reduction within a 40 mm diameter compact housing. Prototypes were 3D printed and later CNC machined in PEEK using Fusion 360 and Bantam Tools to confirm manufacturability. Prototype testing showed smooth gear engagement and no slipping. The final gearbox improves cavity tuning precision for axion searches while protecting cryogenic conditions.
The metal–support interface is central to governing catalytic transformations. While strong metal–support interaction (SMSI) is an established strategy to tailor the morphology and electronic properties of supported metal catalysts, the role of interfacial charge redistribution in SMSI formation remains poorly understood and rarely leveraged. Here, in this study, we report a dual-stimuli approach that combines pH modulation with ultrasonication to mediate SMSI construction in aqueous solution through dynamic Fermi level tuning. By leveraging in situ pH-driven charge redistribution at the metal–support interface, we achieve controllable SMSI encapsulation of metal nanoparticles, as verified by electrochemical analysis, work function measurements, and x-ray-based techniques. The resulting catalysts exhibit tunable SMSI features and deliver enhanced activity and selectivity in hydrogenation reactions. This work establishes a facile strategy to modulate catalyst structure and electronic properties by exploiting Fermi level variation as a driving force, thereby advancing rational SMSI design and catalytic performance across diverse environments.
Perovskite solar cells (PSCs) have demonstrated a comparable efficiency to Si-based cells. However, the buried interface with weak adhesion remains a critical issue since the ion migration enhanced by the built-in electric field at this interface might lead to instability. We report here that adjusting the energy-level alignment at the weak adhesion homojunction interface can mitigate ion migration and thereby enhance the stability and photovoltaic performance of PSCs. Functional molecules with self-assembled monolayer characteristics were introduced to the surface of the SnO2 layer using silane derivatives, which tuned the work function of the homojunction depending on the functional groups in the molecules and thereby significantly reduced the built-in electric field. The PSC exhibited a power conversion efficiency (PCE) of 25.3%. The maximum power point (MPP) tracking under continuous illumination confirmed that the device retained more than 97% of its initial PCE, even after 1,000 h.
Efficiently removing/converting methane via methane combustion imposes challenges on catalyst design: how to design local structures of a catalytic site so that it has both high intrinsic activity and atomic efficiency? By manipulating the atomic distance of isolated Pd atoms, herein we show that the intrinsic activity of Pd catalysts can be significantly improved for methane combustion via a stable Pd 2 structure on a ceria nanorod support. Guided by theory and confirmed by experiment, we find that the turnover frequency (TOF) of the Pd 2 structure with the Pd–Pd distance of 2.99 Å is higher than that of the Pd 2 structure with the Pd–Pd distance of 2.75 Å; at least 26 times that of ceria supported Pd single atoms and 4 times that of ceria supported PdO nanoparticles. The high intrinsic activity of the 2.99 Å Pd–Pd structure is attributed to the conductive local redox environment from the two O atoms bridging the two Pd 2+ ions, which facilitates both methane adsorption and activation as well as the production of water and carbon dioxide during the methane oxidation process. In conclusion, this work highlights the sensitivity of catalytic behavior on the local structure of active sites and the fine-tuning of the metal–metal distance enabled by a support local environment for guiding the design of efficient catalysts for reactions that highly rely on Pt-group metals.
Ethers as electrolyte cosolvents in sodium-ion batteries (SIBs) provide favorable Na + solvation and interfacial properties, but their low oxidative stability limits their use in high-voltage SIBs. Herein, we address this limitation via molecular tuning of ether cosolvents for high-voltage (4.2 V) hard carbon || NaNi 0.33 Fe 0.33 Mn 0.33 O 2 full cells. Tetrahydropyran (THP) is functionalized with a nitrile group to form tetrahydropyran-4-carbonitrile (THPCN). To delineate the effect of nitrile functionalization and benchmark ether against a conventional carbonate, THP, THPCN, and diethyl carbonate (DEC) are evaluated as cosolvents with ethylene carbonate. Nitrile functionalization lowers the HOMO energy of the ether, extends the electrolyte stability window, and alters Na⁺ solvation. Spectroscopic techniques and molecular dynamics simulations reveal that THPCN exhibits predominantly aggregate-dominated solvation (95.1 %) with weakened Na + -solvent interactions, producing the most anion-rich environment relative to DEC and THP cosolvents. THPCN-modified solvation promotes the formation of highly conductive, fluorine-enriched interphases that suppress parasitic reactions. Pouch full cells with THPCN sustained ~ 600 cycles at 4.2 V, outperforming THP and DEC. Operando gas analysis reveals that THPCN reduces CO 2 generation by 45% and H 2 generation by 30% relative to THP. Furthermore, the findings demonstrate nitrile functionalization as a molecular design strategy to stabilize ethers and enable high-voltage SIBs.
The Portable Isotopic Neutron Spectroscopy (PINS) system, employs neutron-induced gamma-ray spectroscopy and provides a nondestructive method for high explosives detection. In standard operation it uses Californium-252 as a neutron source. Operating PINS with a deuterium-tritium (DT) neutron generator has some advantages over Cf-252, including lifetime and ability to produce high-energy inelastic scattering gamma rays. However, current systems using DT neutron generators suffer from a high environmental background and reduced ability to induce neutron capture, reducing spectral quality and limiting nitrogen sensitivity. Here, this study presents the development of an energy-tuning assembly (ETA) designed to optimize the DT neutron energy spectrum to increase nitrogen reaction rates in a target, thereby improving high explosive detection capabilities. A metaheuristic optimization framework, MultiGNOWEE, coupled with MCNP, was employed to generate two ETA configurations: a single-objective ETA, which maximizes nitrogen capture reactions, and a multi-objective ETA, which balances neutron capture and inelastic scattering. Simulations demonstrated the optimized configurations achieved up to a 10-fold improvement in nitrogen capture rates compared to the bare configuration. Experimental validation was conducted using a DT neutron generator and a high-purity germanium (HPGe) detector. Two prototype ETAs were constructed and assessed on a melamine simulant. Measurements demonstrated improved nitrogen detection for both prototype ETA configurations when compared to the standard system.
While a building’s energy usage is driven largely by its design and use, building operator behavior has a strong influence on its energy consumption. This project developed and piloted a specific, data-driven coaching methodology to help operators understand how they can adjust operations and/or affect no/low-cost repairs or upgrades to their specific building HVAC systems to reduce energy consumption. Named BuildingCoach, the operational optimization method used is based on the Building Re-tuning approach developed by the Pacific Northwest National Laboratory. A building operations analytics market has matured over the past decade, though its potential to affect energy-saving changes has not been fully realized. Training operators to understand the methods for operational optimization with the explicit approach of using building-system performance data is hypothesized to create a more effective, longer lasting result in building energy efficiency, and this strategy is the fundamental premise of this project. With the support of an Industry Advisory Board, the project succeeded in developing materials and recruiting for and delivering three pilot cohorts. Deliverables included twenty-two self-paced training modules (accessed via a Learning Management System) and a web-based platform that includes access to real-time building system data and a repository for building system documentation. The project set out to have 100 participants from 50 buildings in three pilot cohorts. In the end, there were 28 participants from 17 buildings, i.e., a significant shortfall. The first two pilot cohorts had only two buildings in each, and this was partially due to difficulties in deploying the Building Operator Coaching Solution (“the BOCS”), which is technology that extracts the data from the controls network and presents it as prescribed for coaching. In the third cohort, the project team deployed the BOCS successfully to 13 buildings, the methodology was piloted as intended, and numerous opportunities for optimization were identified. The BuildingCoach business plan charts a path to an economically sustainable effort. However, even with a licensing model captured in the final version of the business plan, the scalability is still limited to keeping less than 1,000 buildings affected by 2033. Even so, there are unexplored paths to greater scalability that are being considered. CUNY BPL is working to perpetuate and grow the use of BuildingCoach. As of this writing, about twenty buildings have either been connected or will be connected with operators coached / to be coached in the NYC municipal portfolio, twelve buildings across four campuses in NY State will use BuildingCoach, a NY upstate county wishes for six or seven buildings to participate with the support of funding from NYSERDA, and others have also expressed interest. In the decades to come, there will be an increasing percentage of large and mid-sized buildings that incorporate automated system optimization (ASO), and the building operators’ role will shift to spend more time on maintenance and monitoring. Meanwhile, programs such as BuildingCoach will play a critical role in optimizing operations. And, regardless of the emergence of ASO, operators will still need to understand how their systems operate so that they can monitor them properly. Within that context, BuildingCoach is an important step towards operators’ understanding of efficient building system operations.
Analysis on the effectiveness of instruction tuned embedding models for the reduction of Artificial Intelligence hallucinations compared to the standard embedding models.
The microstructure of mesophase pitch carbon fibers (CFs) are tuned by varying ramp rates from 1 to 50 °C min –1 up to 1000 °C to study the effect of ramp rate on CFs’ microstructure, thermal and mechanical properties with the goal of offsetting the cost by decreasing cycle time. The ramp rates represent carbonization times ranging from 16.4 to 1.17 h, not including cool down. Differential scanning calorimetry, thermogravimetric analysis, and derivative thermogravimetry are used to investigate the impact ramp rate has on the thermal properties of mesophase pitch. It is found that lower ramp rates are endothermic in nature with a lower temperature onset and maximum weight loss. Higher ramp rates possess an exothermic nature with higher temperatures resulting in maximal weight loss over a smaller range of temperatures. Mechanical testing shows varying CF strengths and moduli dependent on ramp rate and an optimized process is developed to produce the strongest CF. Furthermore, microstructural characterization revealed that faster ramp rates lead to smaller interplanar spacings and larger crystallites but possessed greater disorder.
In monolayer transition metal dichalcogenides bubbles-nanoscale deformations typically exhibiting a dome-like shape-Excitons are confined by the strain effect, which exhibits extraordinary emission properties, such as single photon generation, enhanced light emission, and spectrally tunable excitonic states. While the strain profiles of these bubbles are extensively studied, this work provides an approach 1) to directly visualize the associated exciton properties in bubbles formed in WSe2 monolayer, revealing an intrinsic emission wavelength shift of ≈40 nm, and 2) actively modify local strain, enabling further exciton emission tuning over a range of 50 nm. These are achieved by emission mapping and nanoindentation using a dielectric near-field probe, which enables the detection of local emission spectra and emission lifetimes within individual bubbles. Statistical analysis of 67 bubbles uncovers an emission wavelength distribution centered around 780 nm. Furthermore, saturation behavior in the power-dependent studies and the associated lifetime change reveal the localized nature of the strain-induced states. These findings provide direct insights into the strain-localized emission dynamics in bubbles and establish a robust framework for non-destructive, reversible, and predictable nanoscale emission control, presenting a potential avenue for developing next-generation tunable quantum optical sources.
Achieving durable lithium (Li) metal anodes in liquid electrolytes remains challenging, primarily due to the instability of the formed solid-electrolyte interphases (SEIs). Modulating the Li-ion solvation structures is pivotal in forming a stable SEI for stabilizing Li metal anodes. Here a strategy is developed to fine-tune the Li-ion solvation structures through enhanced dipole–dipole interactions between the Li-ion-coordinated solvent and the non-Li-ion-coordinating diluent, for creating a stable SEI in the developed binary salt electrolyte. The enhanced dipole–dipole interactions weaken the coordination between Li-ions and the solvents while strengthening the interaction between Li-ions and dual anions, thereby facilitating the Li-ion transport and a robust anion-derived SEI with a distinct bilayer structure. Consequently, the developed electrolyte exhibited exceptional electrochemical performance in high energy-density Li||LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cells, with long calendar life, stable cyclability at 1 C, and reliable operation between 25 and −20 °C, and it also demonstrat remarkable cycling stability for a Li||NMC811 pouch cell with projected energy density of 402 Wh kg −1 , maintaining 80% capacity retention over 606 cycles under practical conditions.
Abstract Li‐excess disordered rocksalts (DRXs) hold promise as next‐generation cathodes for Li‐ion batteries due to their high capacity and energy density, along with the potential to eliminate the need for Co and Ni. However, due to their low Li + diffusivity, DRXs need to be pulverized into nanoparticles to achieve high performance. Herein, a new strategy for overcoming this limitation is demonstrated, involving the design of as‐synthesized partially disordered oxides with a structure that lies between ordered layered and fully disordered, exhibiting a varying degree of local (dis)order. This unique structure activates new Li + diffusion channels, improving percolation and transport properties. This strategy allows a large content of Li + to be accessed in material with large, micron‐sized particles through highly reversible Cr 3+/6+ and O redox, yielding a first discharge capacity of 286 mAh g −1 (881 Wh kg −1 ). The Li + percolation network is further improved by substituting Ti with a mixture of multiple metals, which appears to locally decrease the migration barrier through lattice distortion. Proper tuning of the chemical composition, especially the content of metals with empty d orbitals, is established as a crucial factor for controlling the degree of disorder and mitigating voltage fade and hysteresis growth upon cycling.
Abstract Asymmetric carbon molecular sieve (CMS) hollow fiber membranes with tunable micro‐ and macro‐structural morphologies for energy efficient propylene‐propane separation are reported here. A sub‐glass transition temperature (sub‐Tg) thermal oxidative crosslinking strategy enables simultaneous optimization of the intrinsic molecular sieving properties while also reducing the thickness of the CMS “skin” derived from the 6FDA : BPDA/DAM polyimide precursors. Such synergistic tuning of CMS microstructure and macroscopic morphology of CMS hollow fibers enables significantly increased propylene permeance (reaching 186.5 GPU) while maintaining an appealing propylene/propane selectivity of 13.3 for 50/50 propylene/propane mixed gas feeds. Our findings reveal a more refined and versatile tool than available with previous O 2 ‐doping pretreatments. The advanced approach here should be broadly useful to other polyimide precursors and diverse gas pairs.