SEARCH · Engineering Papers

Results for “interconnection application”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Toward ultrafast, ultra-stable imaging arrays: Superlattice doping to enhance the performance of backside-illuminated 3D-hybridized silicon photodetectors

In this paper, the authors report the latest results on their development of superlattice-doped, thinned, backside-illuminated (BSI), 3D-integrated photodiode detectors—a step toward their ultimate goal of demonstrating ultrafast, ultrastable CMOS imaging arrays. As with most silicon-based photodetectors, backside-illumination and backside surface passivation are keys to achieve the highest performance capability. The two-dimensional (2D) doping technique developed at the Jet Propulsion Laboratory (JPL) has proved to result in a highly efficient, highly stable detector response when combined with a variety of detectors. Here, JPL's 2D-doping has been combined with Sandia's BSI photodetectors hybridized with custom fanout wafer via copper Direct Bond Interconnect (DBI®), a technology that is rapidly becoming industry standard for BSI CMOS imaging arrays. The prototype detectors were packaged and evaluated with respect to their response to low energy electrons. The authors find that the responsivity of 2D-doped BSI detectors is higher than devices prepared using other surface passivation techniques (i.e., ion implantation). The success of the work described herein verifies that the 2D-doping processes previously developed for Sandia's frontside-illuminated photodetectors are generally applicable to BSI detectors and demonstrates for the first time that JPL's 2D-doping process is compatible with the Cu-DBI® technology.

Jewell, April D.↗

DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗

DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A Bi-Layer Dense/Porous Solid Electrolyte Interphase for Enhanced Lithium-Metal Stability

Due to its high theoretical capacity and low electrochemical potential, lithium metal is a highly investigated anode for next-generation high-energy batteries. However, the unstable chemical and topographical heterogeneous surface of lithium gives rise to safety and efficiency concerns that prevent it from being utilized in practical applications. Exposure to electrolyte leads to non-uniform, mixed organic-inorganic solid-electrolyte interphase (SEI) formation, starting a cascading to non-uniform flux distribution, consumption of active materials, and dendrite growth. The SEI is the key feature that will lead to harnessing the capabilities possible with lithium metal. In this work, the formation of a closed-host bi-layer solid electrolyte interphase (SEI) improves the stability of lithium anode. This is successfully realized by forming an interconnected porous LiF-rich artificial SEI in contact with Li metal, and a dense, stable in-situ formed upper layer SEI. The porous layer increases the number of Li/LiF interfaces, which reduces local volume fluctuations and improves Li+ diffusion along these interfaces. Additionally, the tortuous porous structure guides uniform Li+ flux distribution and mechanically suppresses dendrite propagation. The dense upper layer of the SEI accomplishes a closed-host design through reaction with LiNO3 additive and prevents continuous consumption of active materials seen without the additive included in the electrolyte. The duality of a dense top layer with porous bottom layer led to extended cycle life and improved rate performance, evidenced with symmetric cell testing, as well as full cell testing paired with sulfur and LiFePO4 (LFP) cathodes. This work is a good example of a rational design of the SEI, based on comprehensive consideration of various critical factors to improve Li-metal anode stability, and highlights a new pathway to improve cycling and rate performances of Li metal batteries.

25 ENERGY STORAGE↗

DOE OSTI2021

The Dynamic of Complex Two-Phase Mixtures During Coarsening: From Dendritic to Bicontinuous Mixtures

Dendrites are tree-like crystals that frequently form during the solidification of castings. In systems with nearly isotropic interfacial energy, these dendrites possess secondary and sometimes even tertiary arms, and lead to morphologically complex two-phase mixtures. Dealloying, in which one component is selectively leached, leads to nanoporous structures that have proven useful for many technological applications. These bicontinuous two-phase mixtures are topologically and morphologically complex with spatially varying mean and Gaussian curvatures. The evolution of these structures during coarsening is of considerable technological importance since the morphology of the dendrites and nanoporous structure sets the properties of the resulting material. During coarsening, the total surface area per volume of the mixture decreases, thus resulting in an increase in the size-scale of the two-phase mixture. The evolution of interfacial morphology of these interconnected two-phase mixtures is being studied using large-scale computer simulations. The simulations are used to develop a theory of coarsening in these systems that will elucidate the impact of the complicated morphology found in dendritic and nanoporous systems on the coarsening process. The experiments employ four-dimensional X-ray microtomography, which enables the morphology of the two-phase mixture to be followed in three dimensions and time (an additional dimension). The experiments also serve as a test of simulations and theory of the coarsening process, as well as to provide initial conditions for the simulations. Through these experiments and theory, we aim to develop a comprehensive description of coarsening in these complex and technologically important two-phase mixtures.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Smart sensor for online situational awareness in power grids

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.

Dehghanian, Payman↗

DOE OSTI2024

Graph-Based Representations and Applications to Process Simulation

Rapid and robust convergence of a process flowsheet is critical to enable large-scale simulations that address core scientific questions related to process design, optimization, and sustainability. However, due to the highly coupled and nonlinear nature of chemical processes, efficiently solving a flowsheet remains a challenge. In this work, we show that graph representations of the underlying physical phenomena in unit operations may help identify potential avenues to systematically reformulate the network of equations and enable more robust topology-based convergence of flowsheets. To this end, we developed graph abstractions of the governing equations of vapor-liquid and liquid-liquid equilibrium separation equipment. These graph abstractions consist of a mesh of interconnected variable nodes and equation nodes that are systematically generated through PhenomeNode, a new open-source library in Python developed in this study. We show that partitioning the graph into separate mass, energy, and equilibrium subgraphs can help decouple nonlinearities and guide decomposition algorithms. By employing the graph abstraction on an industrial separation process for separating glacial acetic acid from water, we implemented a new block decomposition scheme in BioSTEAM and demonstrated that this can accelerate convergence over a traditional sequential modular approach.

Distillation↗

DOE OSTI2023

Circulating Current Reduction of Back-to-Back MMC with Advanced Grid-Support Functionalities for Medium-Voltage Applications

A Lyapunov energy function based circulating current reduction scheme for a back to back modular multilevel converter based system for a microgrid application has been proposed in this digest. In order to ensure no circulating or zero sequence currents within the modules, the dynamics from one leg of the converter to the other are evaluated. A Lyapunov energy function is then developed and utilizing the circulating current dynamics of the converter the overall control law is implemented. In this digest a decentralized hierarchical control architecture has been implemented for the main current control; where the outer loop or the central controller implements the higher level grid interconnection functions as per IEEE 1547-2018 standards and the inner loop based on synchronous reference frame implements the current control architecture. The inner loops' outputs are the commanded converter voltages either on either side which are augmented by the Lyapunov energy function based circulating current suppression architecture. To evaluate the efficacy of the overall system, the overall system is modeled around a 300kVA back to back SiC multilevel modular converter used as a direct-connected medium voltage (MV) grid intertie based on MATLAB/Simulink domain. Several important case studies are presented in this paper to prove the effectiveness of the proposed architecture. case study results are presented.

circulating current↗

DOE OSTI2021

Unraveling the Unconventional Order of a High-Mobility Indacenodithiophene-Benzothiadiazole Copolymer

We report a new class of donor–acceptor (D-A) copolymers found to produce high charge carrier mobilities competitive with amorphous silicon (>1 cm 2 V –1 s –1 ) exhibit the puzzling microstructure of substantial local order, however lacking long-range order and crystallinity previously deemed necessary for achieving high mobility. Here, we demonstrate the application of low-dose transmission electron microscopy to image and quantify the nanoscale and mesoscale organization of an archetypal D-A copolymer across areas comparable to electronic devices (≈9 μm 2 ). The local structure is spatially resolved by mapping the backbone (001) spacing reflection, revealing nanocrystallites of aligned polymer chains throughout nearly the entire film. Analysis of the nanoscale structure of its ordered domains suggests significant short- and medium-range order and preferential grain boundary orientations. Moreover, we provide insights into the rich, interconnected mesoscale organization of this new family of D-A copolymers by analysis of the local orientational spatial autocorrelations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The IDAES process modeling framework and model library—Flexibility for process simulation and optimization

Abstract Energy systems and manufacturing processes of the 21st century are becoming increasingly dynamic and interconnected, which require new capabilities to effectively model and optimize their design and operations. Such next generation computational tools must leverage state‐of‐the‐art techniques in optimization and be able to rapidly incorporate new advances. To address these requirements, we have developed the Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform, which builds on the strengths of both process simulators (model libraries) and algebraic modeling languages (advanced solvers). This paper specifically presents the IDAES Core Modeling Framework (IDAES‐CMF), along with a case study demonstrating the application of the framework to solve process optimization problems. Capabilities provided by this framework include a flexible, modifiable, open‐source platform for optimization of process flowsheets utilizing state‐of‐the‐art solvers and solution techniques, fully open and extensible libraries of dynamic unit operations models and thermophysical property models, and integrated support for superstructure‐based conceptual design and optimization under uncertainty.

42 ENGINEERING↗

DOE OSTI2020

Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow

This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit knowledge of the system model. The problem is modeled as a dynamic optimization problem with time-varying performance objectives and engineering constraints. The design of the algorithms leverages the online zero-order primal-dual projected-gradient method. In particular, the primal step that involves the gradient of the objective function (and hence requires a networked systems model) is replaced by its zero-order approximation with two function evaluations using a deterministic perturbation signal. The evaluations are performed using the measurements of the system output, hence giving rise to a feedback interconnection, with the optimization algorithm serving as a feedback controller. The paper provides some insights on the stability and tracking properties of this interconnection. Finally, the paper applies this methodology to a real-time optimal power flow problem in power systems, and shows its efficacy on the IEEE 37-node distribution test feeder for reference power tracking and voltage regulation.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow: Preprint

This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit knowledge of the system model. The problem is modeled as a dynamic optimization problem with time-varying performance objectives and engineering constraints. The design of the algorithms leverages the online zero-order primal-dual projected-gradient method. In particular, the primal step that involves the gradient of the objective function (and hence requires networked systems model) is replaced by its zero-order approximation with two function evaluations using a deterministic perturbation signal. The evaluations are performed using the measurements of the system output, hence giving rise to a feedback interconnection, with the optimization algorithm serving as a feedback controller. The paper provides some insights on the stability and tracking properties of this interconnection. Finally, the paper applies this methodology to a real-time optimal power flow problem in power systems, and shows its efficacy on the IEEE 37-node distribution test feeder for reference power tracking and voltage regulation.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Antenna With Embedded Die in Glass Interposer for 6G Wireless Applications

This article presents the antenna-integrated glass interposer for D-band 6G wireless applications using dieembedding technology. Here, we implement the die-embedded package on glass substrates and characterize the electrical performance in the D-band. The electrical characterization employs embedded test dies with the 50-Ω ground–signal–ground (GSG) ports and coplanar waveguides. We achieve low-loss die-to-package transitions by using staggered dielectric vias, which are compared with the transitions of wire-bonding and flip-chip assembly. This article provides detailed information on the design, modeling, fabrication, and characterization of the die-to-package interconnects. This article also demonstrates the integration of microstrip patch antenna array and embedded dies in the D-band. The results show superior electrical performance provided by the die-embedded glass interposer. The die-to-package interconnect exhibits good matching (less than —10-dB S11) and low loss (0.2-dB loss) in the D-band. The integrated 1 × 8 patch antenna array shows 11.6-dB broadside gain and good matching with the embedded die. In addition, by using a temporary carrier, the antenna-integrated glass interposer also has great potential for further heterogeneous integration and thermal management.

42 ENGINEERING↗

DOE OSTI2021

Packaging of an 8-kV Silicon Carbide Diode Module with Double-Side Cooling and Sintered-Silver Joints

Packaging innovations are needed for medium-voltage wide bandgap power semiconductor modules to enable their adaptation in grid applications. A unique challenge for packaging medium-voltage power modules is managing the trade-off between insulation demand and heat dissipation. The focus of this work was on developing a packaging innovation that improves the module heat dissipation and offers more flexibility to its insulation design. Two strategies were explored for the packaging of an 8-kV SiC diode rectifier module:(1) double-side cooling and (2) sintered-silver bonding. Double-side cooling was realized by using short metal posts rather than long and thin wire bonds for device interconnection, forming a low-profile package with devices sandwiched between two insulated metal substrates. Sintered-silver bonding enabled the devices to function reliably at over 250 °C. Simulations of the packaged module showed a low interconnect inductance of 2.67 nH and a 50% less heat transfer coefficient required to cool the chips. Prototypes of the module were fabricated, and preliminary electrical testing results validated the package design.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2025

Tensile Modeling PVC Gels for Electrohydraulic Actuators

Polyvinyl chloride (PVC)-dibutyl adipate (DBA) gels are a fascinating dielectric elastomer actuator showing promise in soft robotics. When actuated with high voltages, the gel deforms towards the anode. A recent application of PVC gels in electrohydraulic actuators motivates elastic and hyperelastic constitutive relationships for tensile loading modes. PVC gels with plasticizer-to-polymer weight ratios of 2:1, 4:1, 6:1, and 8:1 w/w were evaluated. PVC gels exhibit a linear elastic region up to 25% strain. The elastic modulus decreased with increasing plasticizer content from 288.8 kPa, 56.1 kPa, 24.7 kPa, to 11 kPa. Poisson’s ratio also decreased with increasing plasticizer content from 0.42, 0.43, 0.39, to 0.35. We suggest that the decrease in polymer concentration facilitates a weakly interconnected polymer network susceptible to chain slippage that hinders the network response, thus lowering Poisson’s ratio. Our work suggests that PVC gels can be treated as isotropic and incompressible for large strains and hyperelastic modeling; however, highly plasticized gels tend to act less incompressible at small strains. The power scaling law between the elastic modulus and plasticizer weight ratio showed high agreement, making the elastic modulus deterministic for any plasticizer content. The Neo–Hookean, Mooney–Rivlin, Yeoh, Gent, Ogden, and extended tube hyperelastic constitutive models are investigated. The Yeoh model shows the highest feasibility when evaluated up to 3.5 stretch, showing a maximum normalized root-mean-square-error of 6.85%. Together, these findings establish a constitutive basis for PVC-DBA gels, incorporating small strain elasticity, large strain non-linear behavior, and network analysis while providing suggestive insight into the network structure required for accurately modeling the EPIC.

Polymer Science↗

DOE OSTI2025

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Cybersecurity Incident Response Guide for Wind

As wind energy systems become increasingly digitized and interconnected, they face a growing array of cyber threats that can disrupt operations, compromise safety, and trigger cascading impacts across the energy ecosystem. The Wind Incident Response Guide provides a structured, wind-specific framework for preparing for, detecting, responding to, and recovering from cyber incidents. Drawing on lessons from field demonstrations, cyber-physical testbeds, and stakeholder engagement across the wind sector, this guide integrates technical, operational, and regulatory considerations to support asset owners, operators, and responders. It outlines key roles and responsibilities, maps incident response phases to wind-specific scenarios, and highlights applicable laws, regulations, standards, and best practices. By tailoring general cybersecurity principles to the unique architectures and operational constraints of wind systems—including remote access, legacy components, and environmental interfaces—this guide aims to enhance resilience, reduce response time, and support coordinated action across public and private stakeholders. It is intended as a practical resource for utilities, developers, regulators, and emergency managers working to secure the future of wind energy.

17 - WIND ENERGY↗

DOE OSTI2024

Structural characterization of high-protein system through ultra-small and small-angle X-ray scattering

High-protein systems exhibit a hierarchical structure consisting of interconnected multiscale length assemblies. Recent investigations are directed toward identifying these structural units under various processing and environmental conditions to establish structure–function correlations. Ultra-small and small-angle X-ray scattering (USAXS/SAXS) has become a crucial tool for characterizing the structures of proteins and their clusters/aggregates, ranging from nanometers to micrometers, with minimal disruption to their original state. Here, this review first describes the facilities and principles of X-ray scattering, followed by discussions on the analysis of scattering data, including the interpretation of fitting models. It then delves into the main applications of USAXS/SAXS in plant and dairy protein-rich systems. Future strategies to enhance the utilization of scattering techniques for elucidating the structure of high-protein systems are also included.

60 APPLIED LIFE SCIENCES↗