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DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multimodal 3D quantification of particle stimulated nucleation in industrially manufactured aluminium AA5182 sheet

Particle stimulated nucleation is a dominant recrystallisation mechanism observed in many industrially relevant aluminium alloys during thermomechanical processing. Here, in this work, we quantify particle stimulated nucleation in 3D in an aluminium AA5182 alloy sheet cold-rolled to 75% thickness reduction. Second phase particles and nuclei are mapped in the same sample volume by conventional laboratory absorption X-ray tomography and synchrotron X-ray Laue micro-diffraction. The large second phase particles are classified as Fe- and Mg-rich phases. It is found that 84% of the nuclei are particle stimulated and 40% of the particles stimulate nucleation. The critical particle diameter is found to be 4 μm. Deviatoric elastic strains are derived from micro-diffraction data and it is found that elastic strains are present in the recrystallised nuclei. The effects of the different particle types, particle clustering, particle size and aspect ratio as well as strain inheritance are discussed. This work provides a full 3D quantification of particle stimulated nucleation behaviour in AA5182 alloy sheet deformed to high strain.

Deviatoric strain↗

DOE OSTI2020

Microstructural modification of additively manufactured metals by electropulsing

Additive manufacturing (AM) promises rapid development cycles and fabrication of ready-to-use, geometrically-complex parts. The metallic parts produced by AM often contain highly non-equilibrium microstructures, e.g. chemical microsegregation and residual dislocation networks. While such microstructures can enhance some material properties, they are often undesirable. Many AM parts are thus heat-treated after fabrication, a process that significantly slows production. This study investigated if electropulsing, the process of sending high-current-density electrical pulses through a metallic part, could be used to modify the microstructures of AM 316 L stainless steel (SS) and AlSi10Mg parts fabricated by selective laser melting (SLM) more rapidly than thermal annealing. Electropulsing has shown promise as a rapid postprocessing method for materials fabricated using conventional methods, e.g. casting and rolling, but has never been applied to AM materials. For both the materials used in this study, as-fabricated SLM parts contained significant chemical heterogeneity, either chemical microsegregation (316 L SS) or a cellular interdendritic phase (AlSi10Mg). In both cases, annealing times on the order of hours at high homologous temperatures are necessary for homogenization. Using electropulsing, chemical microsegregation was eliminated in 316 L SS samples after 10, 16 ms electrical pulses. In AlSi10Mg parts, electropulsing produced spheroidized Si-rich particles after as few as 15, 16 ms electrical pulses with a corresponding increase in ductility. Finally, this study demonstrated that electropulsing can be used to modify the microstructures of AM metals.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Consumable development to tailor residual stress in parts fabricated using directed energy deposition processes

Distortion and residual stresses are major challenges that limit the ability to fabricate large scale structures using Additive Manufacturing (AM). Researchers worldwide are evaluating techniques to induce compressive residual stress in the parts via intermittent rolling. While reasonable success has been documented, the idea of lowering the martensite start temperature to induce compressive stresses has not been evaluated in the context of AM, despite demonstrated success by the welding community. This study validates the hypothesis that, by a proper selection of materials and process parameters, one may effectively reduce distortion and induce a compressive residual stress in AM parts. Using neutron diffraction to measure residual stresses in parts, we demonstrate that, in addition to selection of the correct materials, the inter pass temperature plays a major role in controlling the residual stress evolution. The observations relating to the residual stresses are rationalized based on a microstructural evolution in these samples. Based on this preliminary study, a strategy to fabricate large structures with minimal distortion and residual stress is outlined.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Canonical scalar field inflation with a Woods–Saxon potential

This paper focuses on the realization of an inflationary model from a canonical scalar field theory with a Woods–Saxon potential, in the slow-roll approximation. Our analysis indicates that the observable quantities derived theoretically from our model, namely the spectral index of the primordial scalar curvature perturbations and the tensor-to-scalar ratio, are compatible with the latest Planck collaboration data. We also discuss the qualitative features of the potential, and we show that the value of the scalar field for which the graceful exit occurs, coincides with the inflection point of the scalar potential. We also attempt to study the post-inflation reheating phase of the model, in order to further examine the viability of the Woods–Saxon scalar field model, and as we demonstrate the results indicate viability of the model for this era too, however the instantaneous reheating is not allowed for the model at hand.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Sizing ramping reserve using probabilistic solar forecasts: A data-driven method

Ramping products have been introduced or proposed in several U.S. power markets to mitigate the impact of load and renewable uncertainties on market efficiency and reliability. Current methods often rely on historical data to estimate the requirements of ramping products and fail to take into account the effects of the latest weather conditions and their uncertainties, which could lead to overly conservative or insufficient requirements. This study proposes a k-nearest-neighbor-based method to give weather-informed estimates of ramping needs based on short-term probabilistic solar irradiance forecasts. Forecasts from multiple sites are employed in conjunction with principal component analysis to derive numerical classifiers to characterize system-level weather conditions. In addition, we develop a data-driven method to optimize the model parameters in a rolling-forward manner. By using real-world data from the California Independent System Operator, we design two metrics to evaluate method performance: 1) frequency of shortage and 2) oversupply of ramping product. Our proposed method presents advantages in comparison with the baseline and a set of benchmark methods: without compromising system reliability, it reduces system ramping requirements by up to 25%, therefore improving both system reliability and economics.

14 SOLAR ENERGY↗

DOE OSTI2022

Carbon emission responsive building control: A case study with an all-electric residential community in a cold climate

In the United States, buildings account for 35% of total energy-related carbon dioxide emissions, making them important contributors to decarbonization. Carbon intensities in the power grid are time-varying and can fluctuate significantly within hours, so shifting building loads in response to the carbon intensities can reduce a building’s operational carbon emissions. This paper presents a rule-based carbon responsive control framework that controls the setpoints of thermostatically controlled loads responding to the grid’s carbon emission signals in real time. Based on this framework, four controllers are proposed with different combinations of carbon accounting methods and control rules. To evaluate their performance, we performed simulation studies using models of a 27-home, all-electric, net zero energy residential community located in Basalt, Colorado, United States. The carbon intensity data of four future years from the Cambium data set are adopted to account for the evolving resource mix in the power grid. Various performance metrics, including energy consumption, carbon emission, energy cost, and thermal discomfort, were used to evaluate the performance of the controllers. Sensitivity analysis was also conducted to determine how the control thresholds and intervals affect the controllers’ performance. Simulation results indicate that the carbon responsive controllers can reduce the homes’ annual carbon emissions by 6.0% to 20.5%. However, the energy consumption increased by 0.9% to 6.7%, except in one scenario where it decreased by 2.2%. Compared to the baseline, the change in energy cost was between –2.9% and 3.4%, and thermal discomfort was also maintained within an acceptable range. The little impact on energy cost and thermal discomfort indicates there are no potential roadblocks for customer acceptance when rolling out the controllers in utility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

The value of concentrating solar power in ancillary services markets

Ancillary services, such as spinning reserves, can provide grid reliability and contribute to profitability of an energy resource. We exercise an existing dispatch optimization model to estimate the profitability of a concentrating solar power plant by incorporating the sale of spinning reserves in the ancillary service market using the National Renewable Energy Laboratory's System Advisor Model to simulate operations within a 72-h rolling horizon framework. Assuming a price-taker approach with day-ahead energy and spinning reserve prices from both the California Independent System Operator and the Electricity Reliability Council of Texas, we find that selling spinning reserves in addition to electric energy increases plant profitability by up to 7% with perfect knowledge of day-ahead pricing and solar resource availability. Here, this finding suggests that spinning reserve markets provide significant value streams to concentrating solar power plants that can leverage thermal energy storage to offer reliable production in the short-to-medium term.

14 SOLAR ENERGY↗

DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗

DOE OSTI2025

Carbon nanotube coated metal mesh: Bridging nanoscale and macroscale

A novel hybrid structure has been developed by growing carbon nanotubes (CNTs) on a metal mesh that functions as a literally unlimitedly extendable backbone. This hybrid material structure provides a new approach of extending CNTs’ advantageous properties such as ultrahigh thermal and electrical conductivities, high sensitivity to gases, and distinctive wettability for different liquids with chemical inertness to macroscale—otherwise available only in nano- and microscales. In this feasibility work, CNTs were grown on a Type 316 stainless steel (SS) mesh by self-catalytical chemical vapor deposition (CVD) without the need of an externally added catalyst or catalyst support. For the radially aligned and entangled CNT forest on the SS mesh, the average CNT diameter is around 50 nm, while the length varies from 20 to 25 µm. High-resolution transmission electron microscopy analysis revealed the multiwall structure of the CNTs with >30 rolled-up graphitic sheets. Raman spectra of the CNTs showed a dominant G band, indicating a well-ordered graphitic nanostructure. Being highly hydrophobic with a water contact angle of ∼145° and oleophilic, the CNT-coated SS mesh could be used in fluid separation and organic contaminant removal from water. Moreover, CNTs are recognized for their exceptional thermal conductivity and the CNT-coated mesh offers a supportive structure with directly connected CNTs for efficient heat transfer. Proof of concept has been achieved for the CNT-coated mesh’s potentials as a liquid filter and an thermal interface material (TIM). Specifically, the CNT-coated mesh demonstrated the capability of capturing water from a water-organic mixture with a 100 % efficiency while allowing organic liquids to pass through the filter. Furthermore, when used as a TIM, the CNT-coated mesh reduced the interfacial thermal impedance by >30 %.

Carbon nanotubes (CNTS)↗

DOE OSTI2022

New bipolar host materials for high power efficiency green thermally activated delayed fluorescence $\mathrm{OLEDs}$

We report four bipolar molecules, namely m-CzPym, p-CzPym, m-CzTrz, and p-CzTrz, with carbazole (Cz) donor and a benzonitrile-substituted pyrimidine (Pym) or triazine (Trz) acceptor core were synthesized and characterized. The electron deficiency of heteroaryl cores together with the substitution pattern of benzonitrile were employed to tune the energy levels as well as the thermally activated delayed fluorescence (TADF) characteristics. The four molecules exhibited TADF behavior with inferior photoluminescent quantum yields (PLQYs) that limit their applications as emitters. These bipolar molecules were employed as TADF host materials for the benchmark TADF emitter 4CzIPN to achieve high-performing green TADF organic light-emitting diodes (OLEDs). Among the molecules, m-CzPym-hosted TADF-OLEDs achieved a maximum external quantum efficiency (EQE max ) of 31.5%, maximum power efficiency (PE max ) of 95.6 lm/W, and maximum current efficiency (CE max ) of 100.2 cd/A. Notably, p-CzPym-hosted TADF-OLEDs also achieved a PE max of 116.5 lm/W, turn-on voltage of 2.5 V, and impressive low efficiency roll-off performance (>89% of EQE max at 5000 cd/m 2 ), representing one of the highest efficiencies ever reported in 4CzIPN-doped devices. The high device efficiency can be ascribed to the balanced ambipolar carrier-transporting character of the host materials and high PLQY as well as the outstanding light outcoupling efficiency of the emitting layer.

42 ENGINEERING↗

DOE OSTI2026

Adsorption-based direct air capture using hierarchical porous composites prepared via confined-space crystallization

Capturing CO₂ at trace concentration remains a critical challenge in sustainable carbon management via adsorption, as conventional adsorbents suffer from low CO₂ selectivity, poor moisture tolerance, and energy-intensive regeneration requirements. Here, we report a hierarchical Ba²⁺-exchanged silicoaluminophosphate (Ba²⁺-CSAPO-34) composite synthesized via confined-space crystallization within an activated carbon matrix. Comprehensive characterization revealed a confined nucleation mechanism and the successful incorporation of Ba²⁺ active sites within the SAPO-34 framework, achieved via a two-step liquid ion-exchange protocol. The core-shell architecture combines the selective CO₂ binding of Ba²⁺-functionalized SAPO-34 with the hydrophobic protection of the carbon shell. Fixed-bed adsorption tests demonstrated strong CO₂ binding (at 500-2500 ppm), no roll-up, and effective suppression of water affinity, while maintaining high selectivity even at 90% relative humidity. A phenomenological adsorption model, validated against dynamic breakthrough data, accurately predicted dynamic adsorption behavior under real-world operating conditions, enabling rational process design for direct air capture (DAC) and closed-loop life support systems. Furthermore, these results establish Ba²⁺-CSAPO-34 as a scalable, moisture-resistant adsorbent that addresses key limitations in trace CO₂ capture, advancing practical implementation of carbon removal technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Large-scale metal strip for power storage and energy conversion applications by machining-based deformation processing

Machining-based deformation processing is used to produce metal foil and flat wire (strip) with suitable properties and quality for electrical power and renewable energy applications. In contrast to conventional multistage rolling, the strip is produced in a single-step and with much less process energy. Examples are presented from metal systems of varied workability, and strip product scale in terms of size and production rate. By utilizing the large-strain deformation intrinsic to cutting, bulk strip with ultrafine-grained microstructure, and crystallographic shear-texture favourable for formability, are achieved. In conclusion, implications for production of commercial strip for electric motor applications and battery electrodes are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

A sensitivity analysis of twinning crystal plasticity finite element model using single crystal and poly crystal Zircaloy

The popularity of crystal plasticity finite element method (CPFEM) models is increasing due to their ability to predict the mechanical response of crystalline materials such as metals and metal alloys more accurately than traditional continuum mechanics models. This is since the crystal plasticity models consider the effect of atomic structure, microstructural morphology, and properties of individual grains. These CPFEM models use a large number of material parameters in order to capture the mesoscale physics which comes with the downside of the tedious calibration process. In this paper, a CPFEM code was developed to include the twinning induced grain reorientation and subsequent crystallographic slip for HPC material. The developed code is incorporated in a large-scale, parallelized nonlinear solver WARP3D. Further, a sensitivity analysis with respect to 22 material parameters was then conducted using single crystal and polycrystal representative volume element (RVE) of Zircaloy material. Loading was applied along five different crystallographic orientations for single crystal RVE and along three directions namely, rolling (RD), transverse (TD), and normal (ND) direction for polycrystal RVE. Results obtained from the sensitivity analysis were used for the calibration of material parameters for Zircaloy. Finally, developed code along with calibrated material parameters was used to investigate the effect of the hydride phase formation in Zircaloy which is a typical case observed for nuclear applications. It was found that the volume fraction of the hydride phase has a significant impact on the mechanical properties of Zircaloy.

36 MATERIALS SCIENCE↗

DOE OSTI2026

ClassNMSW- a real-time classification approach for non-recycled municipal solid waste using hyperspectral imaging

Real-time classification of non-recycled municipal solid waste (NMSW) is essential for efficient valorization. This study introduces ClassNMSW, a comprehensive framework for classifying 22 NMSW subclasses under industrial constraints by using hyperspectral imaging (HSI). A primary innovation of this work is the development of a variance-controlled spectral extraction algorithm. Unlike traditional methods that rely on simple averaging, this approach systematically investigates the extent of pixel extraction to minimize the loss of critical chemical information while maximizing data reduction thus ensuring high spectral fidelity with low computational cost. The approach developed in this work integrates automated, computer-vision-based background removal, eliminating the need for the manual thresholding common in current literature. To resolve ambiguities among chemically similar subclasses, a tiered classification and multi-camera fusion strategy (NIR17 and NIR22) is implemented. Results demonstrate that ClassNMSW achieves an object-wise weighted accuracy of 98.70% for single-sensor configurations and 100% under sensor fusion. A novel rolling-window strategy satisfies desired end-to-end latency of <2 s, satisfying the strict deterministic requirements of high-speed industrial sorting environments. The ClassNMSW framework provides a scalable foundation for advancing circularity and resource recovery in large-scale waste valorization operations.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Microstructural basis for improved corrosion resistance of laser surface processed AZ31 Mg alloy

Despite their excellent strength to weight ratio, wider use of Mg alloys for light weighting applications is limited by their poor corrosion resistance, especially in chloride ion-containing environments. The present study shows improved corrosion resistance imparted by laser surface processing (LSP) of a commercial AZ31 (Mg-3Al-1Zn) alloy. Nanosecond laser processing at three different power settings was carried out on the surface of a 1 mm thick rolled AZ31 sheet. Corrosion testing based on ASTM B117 method and several other electrochemical tests indicates substantial enhancement of corrosion resistance in LSP-treated AZ31. The underlying reason behind improved corrosion resistance of LSP-AZ31 surface has been identified using a variety of characterization tools (SEM, TEM, XPS). Formation of a ~0.5 µm thick mixed metal (Mg, Al) oxide surface film together with refinement in the size and number density of Al-Mn intermetallic particles appear to be playing a major role towards improved corrosion resistance after LSP treatment of AZ31 alloy.

Jana, Saumyadeep↗

DOE OSTI2022

A bi-layer barrier design for 122-type iron-based superconducting wires and tapes

Iron-based superconducting wires and tapes hold great promise for high-field magnet applications. A promising design for 122-type wires and tapes based on the powder-in-tube method is using silver and copper double-layer sheaths. For this design a heat treatment temperature below ~ 779 °C is required to prevent Ag-Cu liquid formation. However, this may be below the optimal heat treatment temperature for the critical current density, and still cannot prevent Ag-Cu interdiffusion occurring in the solid state. In this work we propose adding a niobium or tantalum or vanadium (or their alloys) barrier layer between the Ag and Cu to solve the Ag-Cu interdiffusion issue, given that the group-VB metals (vanadium, niobium, tantalum) are relatively inert to both Ag and Cu. To investigate the effectiveness of this design, BaFe 1.84 Co 0.16 As 2 wires and tapes with Ag/Cu and Ag/Ta/Cu sheaths, as well as Ba 0.6 K 0.4 Fe 2 As 2 wires and tapes with Ag/Cu and Ag/Nb/Cu sheaths, were fabricated. It was found that both the Ta and Nb layers kept integral after wire drawing, but after a large flat-rolling reduction the Ta layer broke while the Nb layer kept integral. In the tapes with Ag/Cu sheaths (without the Ta or Nb layer) Cu diffused through the Ag layer and into the powder cores during 740 °C heat treatment, while in the tapes with Ag/Nb/Cu sheaths the Nb layer effectively blocked Ag-Cu interdiffusion even at 900 °C. Further, this work demonstrates that Ta is a suitable barrier material for 122-type wires, while Nb is suitable for both wires and tapes. In this design using Ag/Nb (or Ta)/Cu sheaths, we can regard the outer Cu as the conductor matrix while the Ag and Nb (or Ta) serve as two layers of barriers that suppress reactions between the components. Thus, we call this design a “bi-layer barrier” design for 122-type wires and tapes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗