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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 55 records · Page 3

A Tunable 3D Nanostructured Conductive Gel Framework Electrode for High-Performance Lithium Ion Batteries

This study develops a tunable 3D nanostructured conductive gel framework as both binder and conductive framework for lithium ion batteries. A 3D nanostructured gel framework with continuous electron pathways can provide hierarchical pores for ion transport and form uniform coatings on each active particle against aggregation. The hybrid gel electrodes based on a polypyrrole gel framework and Fe3O4 nanoparticles as a model system in this study demonstrate the best rate performance, the highest achieved mass ratio of active materials, and the highest achieved specific capacities when considering total mass, compared to current literature. This 3D nanostructured gelbased framework represents a powerful platform for various electrochemically active materials to enable the next-generation high-energy batteries.

25 ENERGY STORAGE↗

Nanostructured Conductive Polymer Gels as a General Framework Material To Improve Electrochemical Performance of Cathode Materials in Li-Ion Batteries

Controlling architecture of electrode composites is of particular importance to optimize both electronic and ionic conduction within the entire electrode and improve the dispersion of active particles, thus achieving the best energy delivery from a battery. Electrodes based on conventional binder systems that consist of carbon additives and nonconductive binder polymers suffer from aggregation of particles and poor physical connections, leading to decreased effective electronic and ionic conductivities. Here we developed a three-dimensional (3D) nanostructured hybrid inorganic-gel framework electrode by in situ polymerization of conductive polymer gel onto commercial lithium iron phosphate particles. This framework electrode exhibits greatly improved rate and cyclic performance because the highly conductive and hierarchically porous network of the hybrid gel framework promotes both electronic and ionic transport. In addition, both inorganic and organic components are uniformly distributed within the electrode because the polymer coating prevents active particles from aggregation, enabling full access to each particle. The robust framework further provides mechanical strength to support active electrode materials and improves the long-term electrochemical stability. The multifunctional conductive gel framework can be generalized for other high-capacity inorganic electrode materials to enable high-performance lithium ion batteries.

25 ENERGY STORAGE↗

A self-correcting variable-metric algorithm framework for nonsmooth optimization

Abstract An algorithm framework is proposed for minimizing nonsmooth functions. The framework is variable metric in that, in each iteration, a step is computed using a symmetric positive-definite matrix whose value is updated as in a quasi-Newton scheme. However, unlike previously proposed variable-metric algorithms for minimizing nonsmooth functions, the framework exploits self-correcting properties made possible through Broyden–Fletcher–Goldfarb–Shanno-type updating. In so doing, the framework does not overly restrict the manner in which the step computation matrices are updated, yet the scheme is controlled well enough that global convergence guarantees can be established. The results of numerical experiments for a few algorithms are presented to demonstrate the self-correcting behaviours that are guaranteed by the framework.

Mathematics↗

Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework

Driven by major scientific advances in analytical methods, biomonitoring, and computational exposure assessment, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the computationally enabled “systems approaches” used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. The AEP framework offers an intuitive approach to successful organization of exposure science data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathway and adverse outcome pathways, completing the source to outcome continuum and setting the stage for more efficient integration of exposure science and toxicity testing information. Together these frameworks form and inform a decision making framework with the flexibility for risk-based, hazard-based or exposure-based decisions.

Teeguarden, Justin G.↗

Meld: Exploring the Feasibility of a Framework-less Framework

HEP data-processing frameworks are essential ingredients in getting from raw data to physics results. But they are often tricky to use well, and they present a significant learning barrier for the beginning HEP physicist. In addition, existing frameworks typically support rigid, collider-based data models, which do not map well to neutrino-physics experiments like DUNE. Neutrino physicists thus expend significant effort working around framework limitations instead of using a framework that directly supports their needs. Presented here is Meld, a Fermilab R&D project, which intends to address these limitations. By leveraging modern C++ capabilities, state-of-the-art concurrency libraries, and a flexible data model, it is possible for beginning (and seasoned) HEP physicists to execute framework programs easily and efficiently, with minimal coupling to framework-specific constructs. Meld aims to directly support the frameworks needs of neutrino experiments like DUNE as well as the more common collider-based experiments.

Knoepfel, Kyle J.↗

Record High Hydrogen Storage Capacity in the Metal–Organic Framework Ni 2 ( m -dobdc) at Near-Ambient Temperatures

Hydrogen holds promise as a clean alternative automobile fuel, but its on-board storage presents significant challenges due to the low temperatures and/or high pressures required to achieve a sufficient energy density. The opportunity to significantly reduce the required pressure for high density H 2 storage persists for metal-organic frameworks due to their modular structures and large internal surface areas. The measurement of H 2 adsorption in such materials under conditions most relevant to on-board storage is crucial to understanding how these materials would perform in actual applications, although such data have to date been lacking. In the present work, the metal-organic frameworks M 2 (m-dobdc) (M = Co, Ni; m-dobdc 4- = 4,6-dioxido-1,3-benzenedicarboxylate) and the isomeric frameworks M 2 (dobdc) (M = Co, Ni; dobdc 4- = 1,4-dioxido-1,3-benzenedicarboxylate), which are known to have open metal cation sites that strongly interact with H 2 , were evaluated for their usable volumetric H 2 storage capacities over a range of near-ambient temperatures relevant to on-board storage. Based upon adsorption isotherm data, Ni 2 (m-dobdc) was found to be the top-performing physisorptive storage material with a usable volumetric capacity between 100 and 5 bar of 11.0 g/L at 25 °C and 23.0 g/L with a temperature swing between -75 and 25 °C. Additional neutron diffraction and infrared spectroscopy experiments performed with in situ dosing of D 2 or H 2 were used to probe the hydrogen storage properties of these materials under the relevant conditions. Finally, the results provide benchmark characteristics for comparison with future attempts to achieve improved adsorbents for mobile hydrogen storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Highly Stable Porphyrinic Zirconium Metal–Organic Framework with shp-a Topology

Through a kinetically controlled synthetic process, we synthesized PCN-223, a new porphyrinic Zr-MOF constructed from the newly reported hexagonal prismatic 12-connected Zr6 cluster through an unusual disordered arrangement, giving rise to the first example of the shp-a network in MOFs. With its extremely high connectivity, PCN-223 shows high stability in aqueous solutions with a wide range of pH. Cationic PCN-223(Fe) formed by postsynthetic treatment is an excellent recyclable heterogeneous catalyst for the hetero-Diels–Alder reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Evidence of Negative Linear Compressibility in the MIL-53 Metal-Organic Framework Family

Here, we report a series of powder X-ray diffraction experiments performed on the soft porous crystals MIL-53(Al) and NH 2 -MIL-53(Al) in a diamond anvil cell under different pressurization media. Systematic refinements of the obtained powder patterns demonstrate that these materials expand along a specific direction while undergoing total volume reduction under an increasing hydrostatic pressure. Our results confirm for the first time the negative linear compressibility behaviour of this family of materials, recently predicted from quantum chemical calculations.

36 MATERIALS SCIENCE↗

Functionalized Porous Aromatic Frameworks as High‐Performance Adsorbents for the Rapid Removal of Boric Acid from Water

Abstract This study demonstrates that functionalized, highly porous polymers are promising for the adsorptive capture of boric acid, a neutral contaminant that is difficult to remove from seawater using conventional reverse osmosis membranes. Appending N ‐methyl‐d‐glucamine (NMDG) to the pore walls of high‐surface‐area porous aromatic frameworks (PAFs) yields the adsorbents PAF‐1‐NMDG and P2‐NMDG in a simple two‐step synthesis. The boron‐selective PAFs demonstrate adsorption capacities that are up to 70% higher than those of a commercial boron‐selective resin, Amberlite IRA743, and markedly faster adsorption rates, owing to their higher NMDG loadings and greater porosities relative to the resin. Remarkably, PAF‐1‐NMDG is able to reduce the boron concentration in synthetic seawater from 2.91 to <0.5 ppm in less than 3 min at an adsorbent loading of only 0.3 mg mL −1 . The boron adsorption rate constants of both frameworks, determined via a pseudo‐second‐order rate model, represent the highest values reported in the literature—in most cases orders of magnitude higher than those of other boron‐selective adsorbents. The frameworks can also be readily regenerated via mild acid/base treatment and maintain constant boron adsorption capacities for at least 10 regeneration cycles. These results highlight the numerous advantages of PAFs over traditional porous polymers in water treatment applications.

Kamcev, Jovan↗

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗

A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations

The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.

30 DIRECT ENERGY CONVERSION↗