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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Energy Efficiency and Renewable Energy Resources for State and Local Leaders

The Weatherization and Intergovernmental Programs Office (WIP) is part of DOE’s Office of Energy Efficiency and Renewable Energy (EERE) and supports DOE’s mission to create greater energy affordability, security, and resilience. WIP’s mission is to enable strategic investments in energy efficiency and renewable energy technologies using innovative practices across the United States in partnership with a wide range of stakeholders, including state and local organizations and community-based nonprofits. WIP supports DOE’s strategic objective to lower energy bills while expanding cost-effective energy choices for all Americans through the Weatherization Assistance Program (WAP) and State Energy Program (SEP). This resource guide highlights resources and publications from the State and Local Solution Center website and across EERE programs.

cost-effective energy, energy efficiency, tools an↗
DOE OSTI2025

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Using Eye-Tracking to Quantify Reverse Engineering Expertise

Software reverse engineering (RE) requires analysts to closely read and make decisions about code. Little is known about what makes an analyst successful, making it difficult to train new analysts or design tools to augment existing ones. The goal of this project was to quantify the eye movement behaviors supporting RE and code comprehension more generally. We applied eye-tracking methods from the language comprehension literature to understand where analysts direct their attention over time when completing tasks (e.g., function identification, bug detection). Across three studies, we manipulated aspects of code hypothesized to impact comprehension (e.g., variable name meaningfulness, code complexity) and presentation methods (e.g., line-by-line, free viewing, gaze-contingent moving window) to understand effects on accuracy and gaze patterns. Results showed clear benefits of meaningful variable names, and effects of expertise on global and line-specific viewing patterns. Findings could inspire empirically-supported tool or analytic adaptations that help to reduce analyst workload.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

PdPt-TiO 2 nanowires: correlating composition, electronic effects and O-vacancies with activities towards water splitting and oxygen reduction

Here we report the optimization of both the support and the active phase of PdPt NPs supported on TiO 2 nanowires to obtain highly active electro/photocatalysts for the oxygen reduction and water splitting reactions. This system displayed strong metal-support interactions, high concentration of oxygen vacancies, and PdPt NP were ~2 nm in size. By optimizing the loading of PdPt, both the photo- and electrocatalytic activities were improved compared to commercial materials. Interestingly, a volcano plot was obtained from the activity and the PdPt composition, and the Pd 0.22 Pt 0.78 -TiO 2 /C sample afforded the optimal performance. For instance, the amount of hydrogen produced from water splitting was 11.6 mmol/g catalyst . For the ORR, the activity was similar to a commercial Pt catalyst, but a lower E onset (0.87 V RHE vs w 0.95 V RHE ) was detected. The variations in the activities with the composition correlated well with the variations in the electronic effects and the concentration of oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Calculation of Moisture-Dependent, Anisotropic Parameters Supporting the Hanford Site's Composite Analysis, Cumulative Impact Evaluation, and Performance Assessments

Variable, moisture (tension) dependent anisotropy (MDA) in unsaturated soils is an effective, large-scale (macroscopic) flow property that results from media heterogeneities at a smaller scale. The purpose of this environmental calculation file (ECF) is to document the variable MDA calculations using a script routine. The accuracy of the script calculations are cross-checked against results using other software. Appendices for this ECF are Appendix A, which documents supporting script use; Appendix B, which provides supporting spreadsheet calculations; and Appendix C, which provides supporting utility calculations. The work is in support of vadose zone flow and transport models used in performance assessment (PA), composite analysis (CA), and cumulative impact evaluation (CIE) at the Hanford Site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Structural and functional analysis of two SHMT8 variants associated with soybean cyst nematode resistance

Two amino acid variants in soybean serine hydroxymethyltransferase 8 (SHMT8) are associated with resistance to the soybean cyst nematode (SCN), a devastating agricultural pathogen with worldwide economic impacts on soybean production. SHMT8 is a cytoplasmic enzyme that catalyzes the pyridoxal 5‐phosphate‐dependent conversion of serine and tetrahydrofolate (THF) to glycine and 5,10‐methylenetetrahydrofolate. A previous study of the P130R/N358Y double variant of SHMT8, identified in the SCN‐resistant soybean cultivar (cv.) Forrest, showed profound impairment of folate binding affinity and reduced THF‐dependent enzyme activity, relative to the highly active SHMT8 in cv. Essex, which is susceptible to SCN. Given the importance of SCN‐resistance in soybean agriculture, we report here the biochemical and structural characterization of the P130R and N358Y single variants to elucidate their individual effects on soybean SHMT8. We find that both single variants have reduced THF‐dependent catalytic activity relative to Essex SHMT8 (10‐ to 50‐fold decrease ink cat /K m ) but are significantly more active than the P130R/N368Y double variant. The kinetic data also show that the single variants lack THF‐substrate inhibition as found in Essex SHMT8, an observation with implications for regulation of the folate cycle. Five crystal structures of the P130R and N358Y variants in complex with various ligands (resolutions from 1.49 to 2.30 Å) reveal distinct structural impacts of the mutations and provide new insights into allosterism. Our results support the notion that the P130R/N358Y double variant in Forrest SHMT8 produces unique and unexpected effects on the enzyme, which cannot be easily predicted from the behavior of the individual variants.

Biochemistry & Molecular Biology↗
DOE OSTI2020

ddcMD.os

ddcMD is a general purpose molecular dynamics (MD) code that supports MPI parallelism. MD codes are used for simulation of particles systems and capture all the many-body effects of the underlying particle potential that defines the physical system. Though MD can be used to model systems from the subatomic to astrological length scales ddcMD is mainly focused on the atomic scale length scale, In this release of ddcMD the support will be mainly for systems using the coarse-grain Martini potential, a particle potential for biological systems.

Glosli, JamesN↗
DOE OSTI2023

Woodland wildfire enables fungal colonization of encroaching Douglas‐fir

Abstract Self‐reinforcing differences in fire frequency help closed‐canopy forests, which resist fire, and open woodlands, which naturally burn often, to co‐occur stably at landscape scales. Forest tree seedlings, which could otherwise encroach and overgrow woodlands, are killed by regular fire, yet fire has other effects that may also influence these feedbacks. In particular, many forest trees require symbiotic ectomycorrhizal fungi in order to establish. By restructuring soil fungal communities, fire might affect the availability of symbionts or the potential for symbiont sharing between encroaching trees and woodland vegetation. To investigate this possibility, we performed a soil bioassay experiment using inoculum from burned and unburned oak woodlands and Douglas‐fir forests. We examined how fire, ecosystem type, and neighboring heterospecific seedlings affect fungal root community assembly of Douglas‐firs and oaks. We asked whether heterospecific seedlings facilitated fungal colonization of seedling roots in non‐native soil, and if so, whether fire influenced this interaction. External fungal colonization of oak roots was more influenced by fire and ecosystem type than by the presence of a Douglas‐fir, and oaks increased the likelihood that Douglas‐fir roots would be colonized by fungi in oak woodland soil. Yet, fire increased colonization of Douglas‐fir in oak soil, diminishing the otherwise crucial role played by oak facilitation. Fire also strengthened the positive effect of Douglas‐firs on oak root‐associated fungal diversity in Douglas‐fir forest soil. Prior work shows that fire supports woodland ecosystems by stemming recruitment of encroaching seedlings. Here, we find evidence that it may contrastingly reduce fungal limitation of invasive seedling growth and establishment, otherwise relieved only by facilitation. Future work can investigate how these opposing effects might contribute to the net impact of changes in fire regime on landcover stability. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Valley-Coherent Quantum Anomalous Hall State in AB-Stacked MoTe 2 / W S e 2 Bilayers

Moiré materials provide fertile ground for the correlated and topological quantum phenomena. Among them, the quantum anomalous Hall (QAH) effect, in which the Hall resistance is quantized even under zero magnetic field, is a direct manifestation of the intrinsic topological properties of a material and an appealing attribute for low-power electronics applications. The QAH effect has been observed in both graphene and transition metal dichalcogenide (TMD) moiré materials. It is thought to arise from the interaction-driven valley polarization of the narrow moiré bands. Here, we show that the newly discovered QAH state in AB-stacked MoTe 2 / W S e 2 moiré bilayers is not valley polarized but valley coherent. The layer- and helicity-resolved optical spectroscopy measurement reveals that the QAH ground state possesses spontaneous spin (valley) polarization aligned (antialigned) in two TMD layers. In addition, saturation of the out-of-plane spin polarization in both layers occurs only under high magnetic fields, supporting a canted spin texture. Our results call for a new mechanism for the QAH effect and highlight the potential of TMD moiré materials with strong electronic correlations and spin-orbit interactions for exotic topological states. Published by the American Physical Society 2024

2-dimensional systems↗
DOE OSTI2020

Voluntary Renewable Energy Procurement Programs in Regulated Utility Markets

Multinational corporations are increasingly purchasing renewable energy (RE) to fulfill international commitments, reduce supply chain emissions, limit environmental impact, and secure stable and affordable electricity. The potential scale of global corporate RE purchasing has been estimated to be nearly 100 GW and growing; however, many markets still lack supportive enabling environments for corporations to access RE through on-site project development or private sector transactions. Even where allowed by law, on-site generation may be insufficient due to space and technical constraints, introducing additional challenges. Utility green pricing and utility green tariff programs backed by renewable energy certificates (RECs), referred to as utility green procurement programs (GPPs) in this report, offer powerful market-based solutions to utilities, regulators, and policymakers to provide corporate and other consumers with RE product options while generating revenue to support RE development. As RE markets expand around the globe, GPPs have proven to be effective mechanisms in market regimes, ranging from fully integrated state-owned utilities to broadly liberalized power markets. GPPs utilize RECs, which are a type of energy attribute certificate and closely resemble guarantees of origin, to track and ultimately monetize RE attributes that corporations and other buyers must procure to demonstrate progress against their RE commitments and make public claims of RE use. Time-tested and transparent REC accounting mechanisms provide market confidence, while at the same time offering flexibility to utilities, regulators, and customers for a range of applications. RECs are used in all types of electricity market structures, as indicated in Figure 1, but REC-based program designs and supporting components differ depending on the type of market. Liberalized markets allow for customers to contract directly with generators for electricity and RECs, while traditionally regulated markets with vertically integrated utility structures may have greater restrictions on generation asset ownership and electricity sales. RE markets can be further defined as being either mandatory or voluntary. Mandatory markets require suppliers to deliver specified amounts of RE to grid customers, such as under a renewable portfolio standard (RPS), while voluntary markets involve no legal mandates, but demand is driven by self-imposed customer goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Surface Enhanced Raman Scattering Selectivity in Proteins Arises from Electron Capture and Resonant Enhancement of Radical Species

Plasmon-enhanced Raman scattering is a powerful approach to detecting and characterizing proteins in live and dynamic biological systems. However, the selective detection/enhancement of specific residues as well as spectral diffusion and fluctuations have complicated the interpretation of enhanced Raman spectra and images of biological matter. In this paper, we therefore demonstrate that the amino acid tryptophan (Trp) can capture an electron from an excited plasmon, which generates a radical anion that is resonantly enhanced: a visible excited electronic state slides into resonance upon charging. This surface enhanced resonance Raman scattering (SERRS) mechanism explains the persistence of Trp signatures in the SERS and TERS spectra of proteins. Evidence for this picture includes the observation of visible resonances in the UV-Vis extinction spectrum, changes in the ground state vibrational spectrum, and plasmon-resonance dependent behavior. DFT calculations support the experimental observations. The behavior observed from the free Trp molecule is shown to explain the SERS spectrum of the Trp-cage protein. In effect, resonant Raman scattering from radicals formed through plasmonic excitation represents an under-investigated mechanism that may be exploited for chemical sensing applications. This work was supported by the National Institutes of Health Award R01-GM109988. The authors thank Hannah Shafaat for helpful discussions and providing an azurin sample for comparison. The authors also thank Joel Harris for providing constructive comments on our manuscript.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Partition between supercooled liquid droplets and ice crystals in mixed-phase clouds based on airborne in situ observations

Abstract. The onset of ice nucleation in mixed-phase clouds determines the lifetime and microphysical properties of ice clouds. In this work, we develop a novel method that differentiates between various phases of mixed-phase clouds, such as clouds dominated by pure liquid or pure ice segments, compared with those having ice crystals surrounded by supercooled liquid water droplets or vice versa. Using this method, we examine the relationship between the macrophysical and microphysical properties of Southern Ocean mixed-phase clouds at −40 to 0 °C (e.g. stratiform and cumuliform clouds) based on the in situ aircraft-based observations during the US National Science Foundation Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) flight campaign. The results show that the exchange between supercooled liquid water and ice crystals from a macrophysical perspective, represented by the increasing spatial ratio of regions containing ice crystals relative to the total in-cloud region (defined as ice spatial ratio), is positively correlated with the phase exchange from a microphysical perspective, represented by the increasing ice water content (IWC), decreasing liquid water content (LWC), increasing ice mass fraction, and increasing ice particle number fraction (IPNF). The mass exchange between liquid and ice becomes more significant during phase 3 when pure ice cloud regions (ICRs) start to appear. Occurrence frequencies of cloud thermodynamic phases show a significant phase change from liquid to ice at a similar temperature (i.e. −17.5 °C) among three types of definitions of mixed-phase clouds based on ice spatial ratio, ice mass fraction, or IPNF. Aerosol indirect effects are quantified for different phases using number concentrations of aerosols greater than 100 or 500 nm (N>100 and N>500, respectively). N>500 shows stronger positive correlations with ice spatial ratios compared with N>100. This result indicates that larger aerosols potentially contain ice-nucleating particles (INPs), which facilitate the formation of ice crystals in mixed-phase clouds. The impact of N>500 is also more significant in phase 2 when ice crystals just start to appear in the mixed phase compared with phase 3 when pure ICRs have formed, possibly due to the competing aerosol indirect effects on primary and secondary ice production in phase 3. The thermodynamic and dynamic conditions are quantified for each phase. The results show stronger in-cloud turbulence and higher updraughts in phases 2 and 3 when liquid and ice coexist compared with pure liquid or ice (phases 1 and 4, respectively). The highest updraughts and turbulence are seen in phase 3 when supercooled liquid droplets are surrounded by ice crystals. These results indicate both updraughts and turbulence support the maintenance of supercooled liquid water amongst ice crystals. Overall, these results illustrate the varying effects of aerosols, thermodynamics, and dynamics through various stages of mixed-phase cloud evolution based on this new method that categorizes cloud phases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BTRIC Technical Support for Appalachia: FY 2023 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This study investigates the effects of various concentrations of carbon dioxide (CO 2 ) on the photosynthesis and biomass accumulation of crops growing in an Agricultural Pod (AgPod). The initial test crop was kale. It has been found that increasing the CO 2 concentration in the AgPod promotes higher photosynthetic rates in kale plants up to 1300 ppm (highest CO 2 concentration). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until unusually high levels of photosynthetically active radiation (PAR, > 1200 µmolm-2s-1) and CO 2 concentration (> 1100 ppm) are reached. Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched greenhouse crop production. This task is one part of an overall plan to incorporate an AgPod to utilize carbon captured from the atmosphere to achieve net negative carbon emissions in a small neighborhood or community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Measurement of the thermal effects in the dispersion relation of the dust acoustic wave in the presence of a magnetic field

This award supported an experimental study of the properties of the dust acoustic wave, low-frequency, l ongitudinal wave mode that propagates through the dust component of a dusty plasma system and is self-excited by the free energy from the ion streaming p ast the dust, in the presence of a high magnetic fiel d. In particular, this project measured the thermal state of dusty plasma system by measuring the dispersi on relation of the dust acoustic wave while varying (1) the strength and direction of the magnetic field relative to the propagation direction of the wave and (2) the neutral gas pressure. By exploiting the unique ability of the MDPX facility to generate a dusty plasma in a high magnetic field environment, it is possible to create a preferential ion flow along the magnetic field lines as the ions become magnetized. In this way, the magnetic field strength can be used to control t he strength of the ion flow through the dust cloud an d provide insight into the contribution that one of the physical mechanisms, a two-stream ion-dust instability, thought to be responsible for high temperatures that have been previously observed might have. This work was completed over two, one-week long runs o n the Magnetized Dusty Plasma eXperiment (MDPX) in the Magnetized Plasma Research Laboratory at Auburn University and supported by work at Wittenberg University (development of an electrode system that would allow for the wave mode to propagate in th e direction of gravity as the orientation of the magnetic field is changed by rotating the magnets on the M DPX device, analysis of data acquired during the experimental campaigns, testing alternative strategies to form a dust cloud based on what was learned the first experimental campaign, etc.).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

BTRIC Technical Support for Appalachia: FY 2024 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This report investigates the effects of various concentrations of CO 2 on the photosynthesis and biomass accumulation of crops growing in an AgPod, using kale as the test crop. In the first year of the study, increasing the CO 2 concentration in the AgPod was found to promote higher photosynthetic rates in kale plants up to 1,300 ppm (the highest CO 2 concentration measured). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until reaching unusually high levels of photosynthetically active radiation (PAR, > 1,200 µmol m -1 s -1 ) and CO 2 concentration (> 1,100 ppm). Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched controlled environment agriculture (ECEA). During the second year of the study, a second crop was planted to confirm the actual effects on growth with increased CO 2 concentrations. Our results suggest that growing kale plants in the AgPod system at higher CO 2 levels resulted in a successful and highly productive crop, up to three times the amount grown at 415 CO 2 . Further, the kale plants grown under higher CO 2 conditions (1000 ppm) are not CO 2 saturated and can potentially further improve yield at even higher CO 2 environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Process-dependent anisotropic thermal conductivity of laser powder bed fusion AlSi10Mg: impact of microstructure and aluminum-silicon interfaces

Purpose AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity. Design/methodology/approach The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity. Findings The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm 3 and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm 3 . The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains. Practical implications The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications. Originality/value To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

Engineering↗
DOE OSTI2025

Do Mandates Deliver Cost Reductions for Energy Storage?

In 2013, California implemented a mandate directing the state’s investor-owned utilities to procure 1325 MW of energy storage, to help integrate nondispatchable renewable sources of energy and assist the state in meeting its environmental goals. This paper evaluates this policy’s impact of both battery deployment, and cost, finding that as of 2019, the state was effective in spurring nearly 500 MWh of battery storage deployment over what would have been installed in absence of the policy. This additive deployment would have the effect of reducing global battery cell costs by roughly $1.00/ kWh, based on learning by doing. To support these findings, we utilize both a difference in differences estimation, and a synthetic control analysis, both of which allow us to compare battery deployment in California, to deployment in other states. To pair deployment to cost reduction, we use a learning curve analysis, which links battery shipments to cell and storage block costs. For policymakers, these results provide evidence to the effectiveness of mandates in promoting storage deployment and help explain how these policies can induce downstream effects.

Boff, Daniel S.↗