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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Shape-persistent phthalocyanine cages

Phthalocyanine (Pc), an electro-redox active moiety, has many attractive properties stemming from its large aromatic system and ability to act as a catalyst in electrochemical reactions, such as the CO 2 reduction reaction (CO 2 RR). However, due to the synthetic challenge related to geometric requirements and poor solubility (strong aggregation), discrete shape-persistent cages consisting of site-isolated, readily accessible Pc moieties have not been available. Here, we report the synthesis of Zn- and Ni-metallated Pc-based molecular cages via one-step dynamic spiroborate linkage formation in high yields. The ZnPc cage structure is unambiguously elucidated at the atomic level by single-crystal X-ray diffraction. Moreover, owing to the site-isolated redox-active metal centers, readily accessible intrinsic cavity, and shape-persistent backbone, the Ni-metallated Pc (NiPc) cage exhibits high catalytic efficiency, selectivity, and stability, superior to the non-caged control molecules in electrocatalytic CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multi-scale organization in communicating active matter

The emergence of collective motion among interacting, self-propelled agents is a central paradigm in non-equilibrium physics. Examples of such active matter range from swimming bacteria and cytoskeletal motility assays to synthetic self-propelled colloids and swarming microrobots. Remarkably, the aggregation capabilities of many of these systems rely on a theme as fundamental as it is ubiquitous in nature: communication. Despite its eminent importance, the role of communication in the collective organization of active systems is not yet fully understood. Here we report on the multi-scale self-organization of interacting self-propelled agents that locally process information transmitted by chemical signals. We show that this communication capacity dramatically expands their ability to form complex structures, allowing them to self-organize through a series of collective dynamical states at multiple hierarchical levels. Our findings provide insights into the role of self-sustained signal processing for self-organization in biological systems and open routes to applications using chemically driven colloids or microrobots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Role of aggregates and microstructure of mixed-ionic–electronic-conductors on charge transport in electrochemical transistors

Synthetic efforts have delivered a library of organic mixed ionic–electronic conductors (OMIECs) with high performance in electrochemical transistors. The most promising materials are redox-active conjugated polymers with hydrophilic side chains that reach high transconductances in aqueous electrolytes due to volumetric electrochemical charging. Current approaches to improve transconductance and device stability focus mostly on materials chemistry including backbone and side chain design. However, other parameters such as the initial microstructure and microstructural rearrangements during electrochemical charging are equally important and are influenced by backbone and side chain chemistry. In this study, we employ a polymer system to investigate the fundamental electrochemical charging mechanisms of OMIECs. We couple in situ electronic charge transport measurements and spectroelectrochemistry with ex situ X-ray scattering electrochemical charging experiments and find that polymer chains planarize during electrochemical charging. Our work shows that the most effective conductivity modulation is related to electrochemical accessibility of well-ordered, interconnected aggregates that host high mobility electronic charge carriers. Electrochemical stress cycling induces microstructural changes, but we find that these aggregates can largely maintain order, providing insights on the structural stability and reversibility of electrochemical charging in these systems. Finally, this work shows the importance of material design for creating OMIECs that undergo structural rearrangements to accommodate ions and electronic charge carriers during which percolating networks are formed for efficient electronic charge transport.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Two‐Dimensional Excitonic Networks Directed by DNA Templates as an Efficient Model Light‐Harvesting and Energy Transfer System

Abstract Photosynthetic organisms organize discrete light‐harvesting complexes into large‐scale networks to facilitate efficient light collection and utilization. Inspired by nature, herein, synthetic DNA templates were used to direct the formation of dye aggregates with a cyanine dye, K21, into discrete branched photonic complexes, and two‐dimensional (2D) excitonic networks. The DNA templates ranged from four‐arm DNA tiles, ≈10 nm in each arm, to 2D wireframe DNA origami nanostructures with different geometries and varying dimensions up to 100×100 nm. These DNA‐templated dye aggregates presented strongly coupled spectral features and delocalized exciton characteristics, enabling efficient photon collection and energy transfer. Compared to the discrete branched photonic systems templated on individual DNA tiles, the interconnected excitonic networks showed approximately a 2‐fold increase in energy transfer efficiency. This bottom‐up assembly strategy paves the way to create 2D excitonic systems with complex geometries and engineered energy pathways.

Zhou, Xu↗
DOE OSTI2022

Two–Dimensional Excitonic Networks Directed by DNA Templates as an Efficient Model Light–Harvesting and Energy Transfer System

Photosynthetic organisms organize discrete light-harvesting complexes into large-scale networks to facilitate efficient light collection and utilization. Inspired by nature, herein, synthetic DNA templates were used to direct the formation of dye aggregates with a cyanine dye, K21, into discrete branched photonic complexes, and two-dimensional (2D) excitonic networks. The DNA templates ranged from four-arm DNA tiles, ≈10 nm in each arm, to 2D wireframe DNA origami nanostructures with different geometries and varying dimensions up to 100×100 nm. These DNA-templated dye aggregates presented strongly coupled spectral features and delocalized exciton characteristics, enabling efficient photon collection and energy transfer. Compared to the discrete branched photonic systems templated on individual DNA tiles, the interconnected excitonic networks showed approximately a 2-fold increase in energy transfer efficiency. Lastly, this bottom-up assembly strategy paves the way to create 2D excitonic systems with complex geometries and engineered energy pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

helixCAM: A platform for programmable cellular assembly in bacteria and human cells

Interactions between cells are indispensable for signaling and creating structure. The ability to direct precise cell-cell interactions would be powerful for engineering tissues, understanding signaling pathways, and directing immune cell targeting. In humans, intercellular interactions are mediated by cell adhesion molecules (CAMs). However, endogenous CAMs are natively expressed by many cells and tend to have cross-reactivity, making them unsuitable for programming specific interactions. Here, we showcase “helixCAM,” a platform for engineering synthetic CAMs by presenting coiled-coil peptides on the cell surface. helixCAMs were able to create specific cell-cell interactions and direct patterned aggregate formation in bacteria and human cells. Based on coiled-coil interaction principles, we built a set of rationally designed helixCAM libraries, which led to the discovery of additional high-performance helixCAM pairs. Finally, we applied this helixCAM toolkit for various multicellular engineering applications, such as spherical layering, adherent cell targeting, and surface patterning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

test-grid-buildouts [SWR-23-112]

Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.

Satkauskas, Ignas↗
DOE OSTI2025

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Shape Control of Colloidal Semiconductor Nanocrystals through Thermodynamically Driven Aggregative Growth

The optoelectronic properties of colloidal semiconductor nanocrystals (NCs) can be manipulated by changing their geometric shapes. The precise synthetic control over particle morphologies, however, has remained elusive. Conventional growth techniques rely on the kinetic assembly of atomic units, where supersaturation and precipitation processes can lead to a broad distribution of particle shapes. In this paper, we demonstrate that replacing atomic precursors with small-size nanocrystals as building blocks for larger colloids offers an easier, more predictive control over nanoparticle shape evolution. The reported growth strategy is illustrated via shape-selective syntheses of CdSe and CdS NC cubes, spheres, rods, as well as unprecedented “donut” and ring-like structures. Growth of desired particle morphologies was achieved by choosing an appropriate reaction solvent that minimizes the surface free energy through a unique shape formation. This so-called "aggregative growth mechanism" is explained using a thermodynamic model for interacting viscous colloids. We expect that this novel growth strategy will offer a viable platform for shape–selective synthesis of many inorganic colloids, providing pathways to optimizable optoelectronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hydrodynamically Controlled Self‐Organization in Mixtures of Active and Passive Colloids

Abstract Active particles are known to exhibit collective behavior and induce structure in a variety of soft‐matter systems. However, many naturally occurring complex fluids are mixtures of active and passive components. The authors examine how activity induces organization in such multi‐component systems. Mixtures of passive colloids and colloidal micromotors are investigated and it is observed that even a small fraction of active particles induces reorganization of the passive components in an intriguing series of phenomena. Experimental observations are combined with large‐scale simulations that explicitly resolve the near‐ and far‐field effects of the hydrodynamic flow and simultaneously accurately treat the fluid–colloid interfaces. It is demonstrated that neither conventional molecular dynamics simulations nor the reduction of hydrodynamic effects to phoretic attractions can explain the observed phenomena, which originate from the flow field that is generated by the active colloids and subsequently modified by the aggregating passive units. These findings not only offer insight into the organization of biological or synthetic active–passive mixtures, but also open avenues to controlling the behavior of passive building blocks by means of small amounts of active particles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Identification and evolution of active sites in isomorphously substituted Fe-ZSM-5 catalysts for methane dehydroaromatization (MDA)

Methane dehydroaromatization (MDA) enables the catalytic conversion of methane into aromatics, mainly benzene, along with hydrogen, in a single-step process under non-oxidative conditions. In this study, we prepared a series of isomorphously substituted Fe-ZSM-5 catalysts with exclusively isolated or low-oligomerized sites up to 3.2% Fe weight loading by adding ethylenediaminetetraacetic acid (EDTA) to the crystallization gel. These catalysts exhibit no induction/activation period and a significantly higher maximum product yield compared to Fe/ZSM-5 catalysts prepared by the incipient wetness impregnation method and containing extensively aggregated FeOx. This investigation focuses on the evolution of Fe sites during the post-synthetic treatments. Most importantly, we demonstrate the quantitative relation between Fe site isolation and catalytic activity, proving that isolated or low-oligomerized Fe species at the exchange sites formed during post-synthetic retreatment are the active sites for methane activation.

02 PETROLEUM↗
DOE OSTI2024

Development of a New Aggregation Method to Remove Nanoplastics from the Ocean: Proof of Concept Using Mussel Exposure Tests

The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and nanoplastics (NPs) are hard to detect and remove from the aquatic environment, eventually interacting with marine organisms. This research mainly aimed to achieve the aggregation of micro- and nanoplastics (MNPs) to ease their removal from the marine environment. To this end, the size and stability of polystyrene (PS) MNPs were measured in synthetic seawater with the different components of the technology (ionic liquid and chitosan). The MPs were purchased in their plain form, while the NPs displayed amines on their surface (PS NP-NH2). The results showed that this technology promoted a significant aggregation of the PS NP-NH2, whereas, for the PS MPs, no conclusive results were found, indicating that the surface charge plays an essential role in the MNP aggregation process. Moreover, to investigate the toxicological potential of MNPs, a mussel species (M. galloprovincialis) was exposed to different concentrations of MPs and NPs, separately, with and without the technology. In this context, mussels were sampled after 7, 14, and 21 days of exposure, and the gills and digestive glands were collected for analysis of oxidative stress biomarkers and histological observations. In general, the results indicate that MNPs trigger the production of reactive oxygen species (ROS) in mussels and induce oxidative stress, making gills the most affected organ. Yet, when the technology was applied in moderate concentrations, NPs showed adverse effects in mussels. The histological analysis showed no evidence of MNPs in the gill’s tissues.

Cid-Samamed, Antonio (ORCID:0000000205073394)↗
DOE OSTI2024

From small changes to big gains: pyridinium-based tetralactam macrocycle for enhanced sugar recognition in water

The complex distribution of functional groups in carbohydrates, coupled with their strong solvation in water, makes them challenging targets for synthetic receptors. Despite extensive research into various molecular frameworks, most synthetic carbohydrate receptors have exhibited low affinities, and their interactions with sugars in aqueous environments remain poorly understood. In this work, we present a simple pyridinium-based hydrogen-bonding receptor derived from a subtle structural modification of a well-known tetralactam macrocycle. This small structural change resulted in a dramatic enhancement of glucose binding affinity, increasing from 56 M −1 to 3001 M −1 . Remarkably, the performance of our synthetic lectin surpasses that of the natural lectin, concanavalin A, by over fivefold. X-ray crystallography of the macrocycle–glucose complex reveals a distinctive hydrogen bonding pattern, which allows for a larger surface overlap between the receptor and glucose, contributing to the enhanced affinity. Furthermore, this receptor possesses allosteric binding sites, which involve chloride binding and trigger receptor aggregation. This unique allosteric process reveals the critical role of structural flexibility in this hydrogen-bonding receptor for the effective recognition of sugars. We also demonstrate the potential of this synthetic lectin as a highly sensitive glucose sensor in aqueous solutions.

Zhai, Canjia↗
DOE OSTI2025

Transport of Delocalized Excitons through DNA-Based Molecular Photonic Wires

Molecular photonic wires conduct electronic energy via their rapid transport properties. In photosynthesis, nature achieves efficient transport across large distances using delocalized excitons, generated by strong excitonic coupling between chromophores. How, or even whether, delocalization facilitates long-distance energy transport in synthetic systems has been challenging to experimentally test and optimize. Thus, far, studies have been limited to strongly coupled, heterogeneous chromophore aggregates or weakly coupled chromophore monomers. Here, in this work, we employed DNA nanostructures to engineer molecular photonic wires constructed from a series of excitonically coupled indocarbocyanine chromophores─achieving the intermediate and strong coupling regimes. Using time-resolved fluorescence spectroscopy and complementary simulations, we demonstrated that an intermediate intermolecular electronic coupling (∼ k B T ) enables up to 40% faster exciton transport as compared to strongly coupled chromophores. The delocalized excitons generated in the intermediate coupling regime exhibited properties conducive to rapid diffusivity, similar to their monomeric counterparts. Thus, intermediate excitonic coupling, analogous to natural systems, achieves long-distance exciton transport with the high chromophore density required for energy capture.

DNA origami↗
DOE OSTI2024

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗
DOE OSTI2022

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

WE-Validate: An Open-Source Framework For Wind Power Validation

Grid operators rely on historical weather time series at existing and planned wind power plants to make informed decisions when planning for a future power grid with very high penetration of renewable power. While synthetic wind power time series have been developed based on historical weather models, their validation with actual power production data remains complex due to variations in modeling practices and methodologies. This paper introduces the WE-Validate framework, originally designed for wind speed validation and now enhanced for wind power validation with a graphical user interface to support users with minimal programming experience. Validation of wind power with WE-Validate is based on robust metrics consisting of RMSE, centered RMSE, average bias, average percent bias, mean absolute error, mean absolute percent error, cross correlation, and calculation of ramping magnitude, rate, and duration. This paper showcases WE-Validate with validation of synthetically derived power for a wind plant in Washington state for one month in 2018. Validation of the synthetic power from two comparison data sets compared with observations shows both comparison series have strong correlation with observed across weekly and monthly aggregations while suffering from persistent negative bias. The suite of metrics within WE-Validate facilitates immediate insight into the utility of the comparison data sets through compression across multiple axes. This user-friendly, open-source tool can be extended beyond wind power, making it a valuable resource for system planners and operators in different domains.

Moncheur de Rieudotte, Malcolm P.↗
DOE OSTI2025

MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data

Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.

Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗