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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 19 records

Distributed Wind Certification Best Practices Guideline: January 16, 2023 - January 15, 2026

This Distributed Wind (DW) Certification Best Practices Guideline describes the typical approach for certification of distributed wind turbines above and below 150 kilowatts (kW) in size based on the conformity assessment requirements in the United States. The purpose of the guideline is to clarify and consistently describe the path to certification for various systems and components by helping the user navigate the complex path to certification compliance. This is done via clarification of both the required turbine type certification elements, as well as third-party electrical safety listing of turbine system components and subassemblies. In the United States specifically, there is no wind turbine certification scheme that governs or maintains a consistent set of conformity assessment requirements, and this can lead to wide ranging interpretations of the standards and required elements for certifications. This guideline attempts to simplify the path by organizing the information and guiding the user to the applicable set of requirements. Any wind turbine manufacturer or designer of wind turbines used in distributed generation applications in the United States would find value in the conformity assessment guidance in this guideline. Users are expected to be involved in the technical development of the product and supporting documentation, as the details provided are geared towards electrical and mechanical engineering of the system and components.

17 WIND ENERGY↗

Conducting Industrial Hygiene Exposure Assessments at Scale Using Non-Parametric Upper Tolerance Limits at the Hanford Site - 20439

Chemical vapors are generated in the radioactive waste storage tanks at the Hanford Site due to ongoing chemical and radiological activity. Hanford's Tank Operations Contractor conducts exposure assessments for individual tank farms to identify, evaluate, and recommend controls or other worker protection measures for chemical, physical, and biological hazards present within each tank farm. These exposure assessments conform to the American Industrial Hygiene Association assessment strategy and recommended statistical procedures. The exposure assessment process involved manually processing tens of thousands of records that were collected over several years and entered into a central database. Working with Pacific Northwest National Laboratory, this process has been largely automated, providing a scalable analysis process that reduced processing time by over 90%, while providing defensible results and improved data quality. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Home Energy Professionals Certifications ISO/IEC 17024: 2021 Policies and Procedures Manual

The U.S. Department of Energy (DOE) enlisted its National Renewable Energy Laboratory (NREL) to coordinate the development of a framework for new certifications in the weatherization and home performance industry. The Home Energy Professional certifications support DOE's Weatherization Assistance Program (WAP) and the broader residential home performance industry through the credentialing process of defined job task analysis for energy auditors and quality control inspectors. The HEP certifications are not intended to supplant or infringe upon any existing industry-recognized credentials, however, the WAP and the home performance industry have utilized the advanced HEP certifications to promote quality work and standardized job task analysis since 2010. On an ongoing basis, NREL brings industry practitioners and subject matter experts together to develop, review, and revise the certification schemes in accordance with the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 17024 standard, "Conformity assessment - General requirements for bodies operating certification of persons" (ISO/IEC 17024). This handbook covers the policies and procedures for the process of developing, maintaining, and validating the certification schemes. Each policy and procedure includes the relevant ISO/IEC 17024 section at the beginning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NRAP Recommended Practices for Containment Assurance and Leakage Risk Quantification

This report presents recommendations for quantitatively assessing and managing leakage risk and effective containment assurance at geologic carbon storage (GCS) sites, amidst uncertainty in site characteristics and performance. These recommended practices are a product of the U.S. Department of Energy’s (DOE) Office of Fossil Energy and Carbon Management’s National Risk Assessment Partnership (NRAP)—a multi-year collaborative research effort of Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, National Energy Technology Laboratory, and Pacific Northwest National Laboratory. These recommended practices are organized as a set of conceptual workflows that correspond with the stages of the GCS project lifecycle. They consider aspects of site characterization, quantification of potential leakage, assessing the spatial extent of potential environmental impacts, optimizing monitoring design for detection of potential leakage, evaluation of concordance between monitored and forecasted reservoir response, assessing conformance with expected/accepted performance, and determination of the timeline over which risk of impactful leakage can be expected to abate. These conceptual workflows are intended to aid stakeholders in making risk management decisions at GCS sites and to support development of sound, risk-based justifications for characterizing the subsurface, defining area of potential leakage impact, designing site monitoring plans, selecting leakage risk management/mitigation alternatives, and estimating site closure timelines.

54 ENVIRONMENTAL SCIENCES↗

Distributed Wind Certification Best Practices Guideline: January 16, 2023-January 15, 2026

This Distributed Wind (DW) Certification Best Practices Guideline describes the typical approach for certification of distributed wind turbines above and below 150 kilowatts (kW) in size based on the conformity assessment requirements in the United States. The purpose of the guideline is to clarify and consistently describe the complex path to certification for various systems and components. This is done via clarification of both the required turbine type certification elements, as well as third-party electrical safety listing of turbine system components and subassemblies.

17 WIND ENERGY↗

Assessing the Impacts of Conformational Fluxionality on Copper(II/I) Electron Transfer Self-Exchange

Typical Cu(II/I) complexes exhibit hallmark structural changes during their electron transfer (ET) reactions that result from the (pseudo) Jahn-Teller distortions and changes in polarizability inherent to their d 10 / d 9 configurations. Given that such structural changes incur large reorganization energy penalties, slow the rates of ET are characteristic of these compounds. Notwithstanding, we recently reported a set of Cu(II/I) complexes that undergo significant and well-defined structural changes during their redox reactions yet exhibit rapid (> 10 5 M ‒1 s ‒1 ) ET self-exchange rate constants ( k 11 ). To explain these results we proposed a pre-equilibrium model in which inherent conformational fluxionality in one of the two oxidation states provides access to pathways involving lower reorganization energies during the ET event. Herein we report our results testing this hypothesis through the preparation and study of a homologous series of compounds exhibiting varying extents of con-formational fluxionality in the Cu(I) state. We characterize these compounds electrochemically, structurally, and by varia-ble temperature NMR spectroscopy to provide experimental evidence for increase fluxionality across the series. We then correlate the trend with increasing k 11 through NMR linewidth broadening experiments, further taking care to define the impacts of solvent impurities therein. Finally, the nature of the conformational rearrangements, and their relation to increased k 11 are explored computationally to reveal differential Boltzmann populations of conformers across the series. The cumulative results of these studies support a previously underappreciated strategy for overcoming barriers to slow ET kinetics: via the incorporation of conformational fluxionality.

Singh, Aditi↗

Conformational dynamics linked to domain closure and substrate binding explain the ERAP1 allosteric regulation mechanism

The endoplasmic-reticulum aminopeptidase ERAP1 processes antigenic peptides for loading on MHC-I proteins and recognition by CD8 T cells as they survey the body for infection and malignancy. Crystal structures have revealed ERAP1 in either open or closed conformations, but whether these occur in solution and are involved in catalysis is not clear. Here, we assess ERAP1 conformational states in solution in the presence of substrates, allosteric activators, and inhibitors by small-angle X-ray scattering. We also characterize changes in protein conformation by X-ray crystallography, and we localize alternate C-terminal binding sites by chemical crosslinking. Structural and enzymatic data suggest that the structural reconfigurations of ERAP1 active site are physically linked to domain closure and are promoted by binding of long peptide substrates. These results clarify steps required for ERAP1 catalysis, demonstrate the importance of conformational dynamics within the catalytic cycle, and provide a mechanism for the observed allosteric regulation and Lys/Arg528 polymorphism disease association.

59 BASIC BIOLOGICAL SCIENCES↗

Lysosomal enzyme binding to the cation-independent mannose 6-phosphate receptor is regulated allosterically by insulin-like growth factor 2

The cation-independent mannose 6-phosphate receptor (CI-MPR) is clinically significant in the treatment of patients with lysosomal storage diseases because it functions in the biogenesis of lysosomes by transporting mannose 6-phosphate (M6P)-containing lysosomal enzymes to endosomal compartments. CI-MPR is multifunctional and modulates embryonic growth and fetal size by downregulating circulating levels of the peptide hormone insulin-like growth factor 2 (IGF2). The extracellular region of CI-MPR comprises 15 homologous domains with binding sites for M6P-containing ligands located in domains 3, 5, 9, and 15, whereas IGF2 interacts with residues in domain 11. How a particular ligand affects the receptor’s conformation or its ability to bind other ligands remains poorly understood. To address these questions, we purified a soluble form of the receptor from newborn calf serum, carried out glycoproteomics to define the N-glycans at its 19 potential glycosylation sites, probed its ability to bind lysosomal enzymes in the presence and absence of IGF2 using surface plasmon resonance, and assessed its conformation in the presence and absence of IGF2 by negative-staining electron microscopy and hydroxyl radical protein footprinting studies. Together, our findings support the hypothesis that IGF2 acts as an allosteric inhibitor of lysosomal enzyme binding by inducing global conformational changes of CI-MPR.

59 BASIC BIOLOGICAL SCIENCES↗

X‐ray scattering reveals disordered linkers and dynamic interfaces in complexes and mechanisms for DNA double‐strand break repair impacting cell and cancer biology

Abstract Evolutionary selection ensures specificity and efficiency in dynamic metastable macromolecular machines that repair DNA damage without releasing toxic and mutagenic intermediates. Here we examine non‐homologous end joining (NHEJ) as the primary conserved DNA double‐strand break (DSB) repair process in human cells. NHEJ has exemplary key roles in networks determining the development, outcome of cancer treatments by DSB‐inducing agents, generation of antibody and T‐cell receptor diversity, and innate immune response for RNA viruses. We determine mechanistic insights into NHEJ structural biochemistry focusing upon advanced small angle X‐ray scattering (SAXS) results combined with X‐ray crystallography (MX) and cryo‐electron microscopy (cryo‐EM). SAXS coupled to atomic structures enables integrated structural biology for objective quantitative assessment of conformational ensembles and assemblies in solution, intra‐molecular distances, structural similarity, functional disorder, conformational switching, and flexibility. Importantly, NHEJ complexes in solution undergo larger allosteric transitions than seen in their cryo‐EM or MX structures. In the long‐range synaptic complex, X‐ray repair cross‐complementing 4 (XRCC4) plus XRCC4‐like‐factor (XLF) form a flexible bridge and linchpin for DNA ends bound to KU heterodimer (Ku70/80) and DNA‐PKcs (DNA‐dependent protein kinase catalytic subunit). Upon binding two DNA ends, auto‐phosphorylation opens DNA‐PKcs dimer licensing NHEJ via concerted conformational transformations of XLF‐XRCC4, XLF–Ku80, and LigIV BRCT –Ku70 interfaces. Integrated structures reveal multifunctional roles for disordered linkers and modular dynamic interfaces promoting DSB end processing and alignment into the short‐range complex for ligation by LigIV. Integrated findings define dynamic assemblies fundamental to designing separation‐of‐function mutants and allosteric inhibitors targeting conformational transitions in multifunctional complexes.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative Assessment of Data-driven Process Models in Health Information Technology

Process mining for conformance analysis consists of comparing a reference process model against a data-driven process model generated via log files from information technology systems. However, in the absence of a complete reference process model, we found no suggested approaches in the literature to address the need for evaluating process conformance among different healthcare facilities to assess standardization of care. Our goal is to find similarities and dissimilarities in data-driven process models among US Veterans Health Administration (VHA) facilities that can be indicative of patient safety issues. Our hypothesis was that the analysis would not produce statistically significant differences in outcome. We present a unique implementation of conformance analysis in process mining that consists of combining process mining, process mapping and statistical metrics. We illustrate our approach by applying it to the analysis of two clinical radiology order process models generated from healthcare data provided by two similar facilities in the VHA. The comparative assessment showed that about 70% of the orders completed successfully and 30% were not completed due to policy and duplications. Our analysis found a good statistical correlation between both facilities, as the Spearman’s correlation coefficient between facilities for the frequency of cases per total hours was 0.87879, for the frequency of cases by state transition was 0.79702 and for the throughput time per state transition was 0.63582. Additional statistical analyses using the Mann-Whitney U test and the root mean square error both produced values that were not significant. The foregoing approach validated our hypothesis by demonstrating a good statistical correlation of data describing the flow of clinical radiology orders absent a credible reference model. Finding good agreement between both facilities was important in confirming that the clinical orders flow in a similar manner, suggesting standardization of care.

97 MATHEMATICS AND COMPUTING↗

Fragment binding to the Nsp3 macrodomain of SARS-CoV-2 identified through crystallographic screening and computational docking

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate–ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of 2533 diverse fragments resulted in 214 unique macrodomain-binders. An additional 60 molecules were selected from docking more than 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several fragment hits were confirmed by solution binding using three biophysical techniques (differential scanning fluorimetry, homogeneous time-resolved fluorescence, and isothermal titration calorimetry). The 234 fragment structures explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating chromosome conformation and DNA repair in a computational framework to assess cell radiosensitivity

Objective. The arrangement of chromosomes in the cell nucleus has implications for cell radiosensitivity. The development of new tools to utilize Hi-C chromosome conformation data in nanoscale radiation track structure simulations allows for in silico investigation of this phenomenon. We have developed a framework employing Hi-C-based cell nucleus models in Monte Carlo radiation simulations, in conjunction with mechanistic models of DNA repair, to predict not only the initial radiation-induced DNA damage, but also the repair outcomes resulting from this damage, allowing us to investigate the role chromosome conformation plays in the biological outcome of radiation exposure. Approach. In this study, we used this framework to generate cell nucleus models based on Hi-C data from fibroblast and lymphoblastoid cells and explore the effects of cell type-specific chromosome structure on radiation response. The models were used to simulate external beam irradiation including DNA damage and subsequent DNA repair. The kinetics of the simulated DNA repair were compared with previous results. Main results. We found that the fibroblast models resulted in a higher rate of inter-chromosome misrepair than the lymphoblastoid model, despite having similar amounts of initial DNA damage and total misrepairs for each irradiation scenario. Significance. This framework represents a step forward in radiobiological modeling and simulation allowing for more realistic investigation of radiosensitivity in different types of cells.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗

Data-Driven Buy Clean: Decarbonization and Beyond

This report was compiled to provide recommendations on the availability of public background data from the U.S. Federal life cycle assessment (LCA) Data Commons to be conformant with the Association for Life Cycle Assessment (ACLCA) 2022 Product Category Rule (PCR) Open Standard to build technical tools that can assist industry in creating more comparable Type II Environmental Product Declarations (EPDs) for Federal Buy Clean and sustainability initiatives. The Federal LCA Commons is not only a public data source but also a consistently structured, self-referencing mega-repository for data developed by federal agency experts (in agency repositories) and by academia, nonprofit organizations, and industry (via the US Life Cycle Inventory Database). The Federal LCA Commons Technical Working Group is continuously improving the standardization of data documentation, formatting, and nomenclature to ensure lossless data loading and accurate data representation. This report and appendixes include the following: 1) An introduction to data-driven Buy Clean and decarbonization initiatives at the federal level; 2) The current status and associated challenges with LCA data and EPD standards and comparability; 3) Opportunities for the Federal LCA Commons to support conformance with the ACLCA 2022 PCR Open Standard and provide resources to implement the Federal Sustainability Plan, Buy Clean Program, and Inflation Reduction Act (IRA) sustainability goals and objectives. To date, the Federal LCA Commons is the result of coordinated work by National Renewable Energy Laboratory (NREL), the U.S. Department of Agriculture (USDA), the Environmental Protection Agency (EPA), the National Energy Technology Laboratory (NETL), the Argonne National Laboratory (ANL), the U.S. Army Corps of Engineers (USACE), the Federal Highway Administration (FHWA), the U.S. Forest Service (USFS), the Federal Aviation Administration (FAA), the Department of Defense (DoD) and the National Institute of Standards and Technologies (NIST). The Federal LCA Commons will continue to combine databases from the collaborating agencies while remaining a public resource. There are several initiatives among the collaborating agencies to expand the Federal LCA Commons and dedicated federal funding and resources could accelerate and strengthen these initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Towards a Comparative Assessment of Data-Driven Process Models in Health Information Technology

Process mining for conformance analysis focuses on comparing a reference process model against a data-driven process model that is generated via log files from information technology systems. While this approach is helpful when there is an existing process model in an organization, it leaves the question of what to do in the absence of a complete reference process model unanswered. In this paper, we present a comparative assessment approach that combines process mining, process mapping for dimensionality reduction, and statistical analysis. Our goal is to find similarities and dissimilarities in data-driven process models among U.S. Veterans Health Administration (VHA) facilities to assess process conformance among different healthcare facilities, which can help assess the standardization of care. We illustrate our approach by applying it to two clinical radiology order process models generated by two similar facilities. Our results demonstrate statistical similarities in the standardization of care among those two facilities.

Klasky, Hilda↗

An investigation on machine learning predictive accuracy improvement and uncertainty reduction using VAE-based data augmentation

The confluence of ultrafast computers with large memory, rapid progress in Machine Learning (ML) algorithms, and the availability of large datasets place multiple engineering fields at the threshold of dramatic progress. However, a unique challenge in nuclear engineering is data scarcity because experimentation on nuclear systems is usually more expensive and time-consuming than most other disciplines. One potential way to resolve the data scarcity issue is deep generative learning, which uses certain ML models to learn the underlying distribution of existing data and generate synthetic samples that resemble the real data. In this way, one can significantly expand the dataset to train more accurate predictive ML models. In this study, our objective is to evaluate the effectiveness of data augmentation using variational autoencoder (VAE)-based deep generative models. We investigated whether the data augmentation leads to improved accuracy in the predictions of a deep neural network (DNN) model trained using the augmented data. Additionally, the DNN prediction uncertainties are quantified using Bayesian Neural Networks (BNN) and conformal prediction (CP) to assess the impact on predictive uncertainty reduction. To test the proposed methodology, we used TRACE simulations of steady-state void fraction data based on the NUPEC Boiling Water Reactor Full-size Fine-mesh Bundle Test (BFBT) benchmark. Here, we found that augmenting the training dataset using VAEs has improved the DNN model’s predictive accuracy, improved the prediction confidence intervals, and reduced the prediction uncertainties.

Bayesian neural network↗

Dynamic Implications of Noncovalent Interactions in Amphiphilic Single-Chain Polymer Nanoparticles

Single-chain polymer nanoparticles (SCNPs) combine the chemical diversity of synthetic polymers with the intricate structure of biopolymers, generating versatile biomimetic materials. The mobility of polymer chain segments at length scales similar to secondary structural elements in proteins is critical to SCNP structure and thus function. However, the influence of noncovalent interactions used to form SCNPs (e.g., hydrogen-bonding and biomimetic secondary-like structure) on these conformational dynamics is challenging to quantitatively assess. To isolate the effects of noncovalent interactions on SCNP structure and conformational dynamics, we synthesized a series of amphiphilic copolymers containing dimethylacrylamide and monomers capable of forming these different interactions: (1) di(phenylalanine) acrylamide that forms intramolecular β-sheet-like cross-links, (2) phenylalanine acrylamide that forms hydrogen-bonds but lacks a defined local structure, and (3) benzyl acrylamide that has the lowest propensity for hydrogen-bonding. Each SCNP formed folded structures comparable to those of intrinsically disordered proteins, as observed by size exclusion chromatography and small angle neutron scattering. The dynamics of these polymers, as characterized by a combination of dynamic light scattering and neutron spin echo spectroscopy, was well described using the Zimm with internal friction (ZIF) model, highlighting the role of each noncovalent interaction to additively restrict the internal relaxations of SCNPs. These results demonstrate the utility of local scale interactions to control SCNP polymer dynamics, guiding the design of functional biomimetic materials with refined binding sites and tunable kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗