Dodecagonal quasicrystals of oil-swollen ionic surfactant micelles
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The energetics and dynamics of ion assembly in solution has broad influence in nanomaterials and inorganic synthesis. To investigate the fundamental processes involved, we present a time-resolved x-ray solution scattering (TR-XSS) study of the trinuclear silver and thallium complexes of the diplatinum ion PtPOP [Pt 2 (H 2 P 2 O 5 )$_4^{4−}$] in aqueous solution. These complexes, their structural properties, and their electronic structure are not well understood and afford a unique opportunity to study the metal–metal bond formation that influences molecular and material assembly in solution. We present model-independent analysis of the observed dynamics as well as an analysis incorporating time-resolved structural refinements of key bond lengths with $<$100 fs time resolution. We find that upon photoexcitation, the Pt atoms contract ∼0.25 Å toward the center of both the Ag- and the Tl-PtPOP complexes, as previously observed for the PtPOP anion. For the AgPtPOP system, an ultrafast Ag-Pt bond expansion of ∼0.2 Å is observed, whereas in contrast, the TlPtPOP system exhibits a Tl-Pt bond contraction of ∼0.3 Å upon photoexcitation. For both complexes, the change in electronic state leads to coherent (“wave-packet”) oscillations along the metal–Pt coordinates. Based on these structural dynamics, we propose an electronic structure model that describes the metal–metal bonding behavior in both the ground and excited state for both complexes.
Electrochemical compression has the possibility to outcompete mechanical compression for hydrogen end- use applications. While HyET has a compressor that can output JO kilograms (kg)/day (fully scalable from home-to-industrial application) at up to 700 bar, the energy demand and reliability require top-quality electrochemical hydrogen compression (EHC) membrane electrode assemblies (MEAs), preferably prepared by cost-effective high-capacity manufacturing. High pressure requires a special MEA design, deviating from typical proton exchange membrane fuel cell (PEMFC) MEAs with adapted catalyst layer substrates, asking for a modified coating process. The National Renewable Energy Laboratory (NREL) will help HyET by developing an automated catalyst coating process fit for EHC MEA manufacturing. In addition, inline quality inspection methods will be developed/selected to improve the MBA quality as it is used for EHC stack assembly. In a joint effort, NREL and HyET will even design an automated manufacturing process for the EHC MEA and approach potential United States (US) suppliers of manufacturing equipment.
Mitochondrial complex II, also known as succinate dehydrogenase (SDH), is an integral-membrane heterotetramer (SDHABCD) that links two essential energy-producing processes, the tricarboxylic acid (TCA) cycle and oxidative phosphorylation. A significant amount of information is available on the structure and function of mature complex II from a range of organisms. However, there is a gap in our understanding of how the enzyme assembles into a functional complex, and disease-associated complex II insufficiency may result from incorrect function of the mature enzyme or from assembly defects. Here, we investigate the assembly of human complex II by combining a biochemical reconstructionist approach with structural studies. We report an X-ray structure of human SDHA and its dedicated assembly factor SDHAF2. Importantly, we also identify a small molecule dicarboxylate that acts as an essential cofactor in this process and works in synergy with SDHAF2 to properly orient the flavin and capping domains of SDHA. This reorganizes the active site, which is located at the interface of these domains, and adjusts the pK a of SDHA R451 so that covalent attachment of the flavin adenine dinucleotide (FAD) cofactor is supported. We analyze the impact of disease-associated SDHA mutations on assembly and identify four distinct conformational forms of the complex II flavoprotein that we assign to roles in assembly and catalysis.
Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device. Its unique design creates highly localized electrical, thermal, and mechanical process parameters for continuous samples of limitless length. Advanced core shell powder materials were also created using fluidized powder bed atomic layer deposition of core/shell solid oxide electrochemical electrode/electrolyte BaCe0.7Zr0.1Y0.1Yb0.1O3 (BCZYYb) and yttrium doped BaZrO3 (BZY) to be a feedstock for the new CEFAS instrument. The innovative core/shell powder is hypothesized to have high protonic conductivity with enhanced environmental resistance. The completed project covers innovations in process control and design enabled by control theory, finite element modeling and mechanical design, three dimensionally printed carbon-carbon composite manufacturing and utilization, and green materials processing techniques.
Electric-field assisted sintering (EFAS) is an advanced manufacturing method for the consolidation and processing of ceramic and metal materials. It is a particularly excellent candidate for efficient materials processing as it has greater than 90% energy cost savings and improved CO2 emissions compared to traditional sintering in a furnace. This is due to direct rapid heating of the materials and molds leveraging an electrification phenomenon called Joule heating where electrical current is passed through the sample/mold assemblies causing direct heating. The technique does have limitations though as it is traditionally a batch-process and suffers from scale up difficulties. To overcome this, researchers at Idaho National Laboratory changed the form factor of traditional EFAS instruments to develop and construct a continuous rolling electric-field assisted sintering (CEFAS) device.
Spin-bearing molecules are promising building blocks for quantum technologies as they can be chemically tuned, assembled into scalable arrays, and readily incorporated into diverse device architectures. In molecular systems, optically addressing ground-state spins would enable a wide range of applications in quantum information science, as has been demonstrated for solid-state defects. However, this important functionality has remained elusive for molecules. Here, we demonstrate such optical addressability in a series of synthesized organometallic, chromium(IV) molecules. These compounds display a ground-state spin that can be initialized and read out using light and coherently manipulated with microwaves. In addition, through atomistic modification of the molecular structure, we vary the spin and optical properties of these compounds, indicating promise for designer quantum systems synthesized from the bottom-up.
The N-representability problem consists in determining whether, for a given p-body matrix, there exists at least one N-body density matrix from which the p-body matrix can be obtained by contraction, that is, if the given matrix is a p-body reduced density matrix (p-RDM). The knowledge of all necessary and sufficient conditions for a p-body matrix to be N-representable allows the constrained minimization of a many-body Hamiltonian expectation value with respect to the p-body density matrix and, thus, the determination of its exact ground state. However, the number of constraints that complete the N-representability conditions grows exponentially with system size, and hence, the procedure quickly becomes intractable for practical applications. This work introduces a hybrid quantum-stochastic algorithm to effectively replace the N-representability conditions. The algorithm consists of applying to an initial N-body density matrix a sequence of unitary evolution operators constructed from a stochastic process that successively approaches the reduced state of the density matrix on a p-body subsystem, represented by a p-RDM, to a target p-body matrix, potentially a p-RDM. The generators of the evolution operators follow the well-known adaptive derivative-assembled pseudo-Trotter method (ADAPT), while the stochastic component is implemented by using a simulated annealing process. The resulting algorithm is independent of any underlying Hamiltonian, and it can be used to decide whether a given p-body matrix is N-representable, establishing a criterion to determine its quality and correcting it. We apply the proposed hybrid ADAPT algorithm to alleged reduced density matrices from a quantum chemistry electronic Hamiltonian, from the reduced Bardeen–Cooper–Schrieffer model with constant pairing, and from the Heisenberg XXZ spin model. In all cases, the proposed method behaves as expected for 1-RDMs and 2-RDMs, evolving the initial matrices toward different targets.
Protein self-assembly is a common and essential biological phenomenon, and bacterial microcompartments present a promising model system to study this process. Bacterial microcompartments are large, protein-based organelles which natively carry out processes important for carbon fixation in cyanobacteria and the survival of enteric bacteria. These structures are increasingly popular with biological engineers due to their potential utility as nanobioreactors or drug delivery vehicles. However, the limited understanding of the assembly mechanism of these bacterial microcompartments hinders efforts to repurpose them for non-native functions. Here, we comprehensively investigate proteins involved in the assembly of the 1,2-propanediol utilization bacterial microcompartment from Salmonella enterica serovar Typhimurium LT2, one of the most widely studied microcompartment systems. We first demonstrate that two shell proteins, PduA and PduJ, have a high propensity for self-assembly upon overexpression, and we provide a novel method for self-assembly quantification. Using genomic knock-outs and knock-ins, we systematically show that these two proteins play an essential and redundant role in bacterial microcompartment assembly that cannot be compensated by other shell proteins. At least one of the two proteins PduA and PduJ must be present for the bacterial microcompartment shell to assemble. We also demonstrate that assembly-deficient variants of these proteins are unable to rescue microcompartment formation, highlighting the importance of this assembly property. Our work provides insight into the assembly mechanism of these bacterial organelles and will aid downstream engineering efforts.
The assembly of nematic colloids relies on long-range elastic interactions that can be manipulated through external stimuli. Confinement and the presence of a hydrodynamic field alter the defect structures and the energetic interactions between the particles. Here, the assembly landscape of nanoparticles embedded in a nematic liquid crystal confined in a nanochannel under a pressure-driven flow is determined. The dynamics of the liquid crystal tensor alignment field is determined through a Poisson-Bracket framework, namely the Stark–Lubensky equations, coupled with the zero-Reynolds momentum equations and the liquid crystal Landau-de Gennes free energy functional. A second order semi-implicit time integration and a three-dimensional Galerkin finite element method are used to resolve flow and nematic fields under several conditions. In general, the zero Reynolds flow displaces the defects around the particles in the upstream direction and renders the surface anchoring ineffective when the flow strength dominates over the nematic elasticity. More importantly, the potential of mean force for particle assembly is non-monotonic independent of surface anchoring. Our results show that the confinement length scale determines the repulsion/attraction transition between colloids, while the flow strength modifies the static defect structure surrounding the particles and determines the magnitude of the energetic barrier for successful assembly. In the attractive regime, the particles move at different rates through the nematic until one particle eventually catches up with the other. This process occurs against or along the direction of flow depending on the flow strength. Ultimately, these results provide a template for engineering and controlling the transport and assembly of nanoparticles under far-from equilibrium conditions in anisotropic media.
In the Anthropocene, human activities are intensifying stresses on biological communities across ecosystems. Knowledge on how environmental changes influence microbial community dynamics is crucial but currently limited. Here we unraveled ecological processes generating distribution patterns of bacterioplankton and phytoplankton communities in a river draining an urbanizing watershed in southern China. In this ecosystem, longitudinal environmental heterogeneity and directional flow potentially have counteracting effects on planktonic community assembly. Using simultaneously multiple approaches, we showed that the observed compositional patterns result from an interplay of stochastic and deterministic processes, indicating that dispersal via fluvial connectivity could not override local selective pressures. Successional shifts in the relative importance of the above processes were associated with trends in climatic factors. High diversity was observed at the intermediate levels of ecological processes alongside intense inter-species interactions maintained by a few keystone taxa. Altogether, interactions between climatic conditions, landscape and hydrology control plankton community dynamics.
Abstract Block copolymers spontaneously self-assemble into well-defined nanoscale morphologies. Yet equilibrium assembly gives rise to a limited set of structures. Non-equilibrium strategies can, in principle, expand diversity by exploiting self-assembly’s responsive nature. In this vein, we developed a pathway priming strategy combining control of thin film initial configurations and ordering history. We sequentially coat distinct materials to form prescribed initial states, and use thermal annealing to evolve these manifestly non-equilibrium states through the assembly landscape, traversing normally inaccessible transient structures. We explore the enormous associated hyperspace, spanning processing (annealing temperature and time), material (composition and molecular weight), and layering (thickness and order) dimensions. We demonstrate a library of exotic non-native morphologies, including vertically-oriented perforated lamellae, aqueduct structures (vertical lamellar walls with substrate-pinned perforations), parapets (crenellated lamellae), and networks of crisscrossing lamellae. This enhanced structural control can be used to modify functional properties, including accessing regimes that surpass their equilibrium analogs.
Explore the source record for details and available documents.
The multidisciplinary applications of hydrogels have motivated a thorough exploration of the relationship between their structural and mechanical properties, i.e., spatial structure–function relationships, with particular regard to strength and toughness. While this approach has driven fundamental advancements in the design of robust hydrogel structures, further complementary perspectives are needed to enable holistic, rational design schemes that integrate considerations such as fabrication and advanced functions like response and adaptation. To these ends, this review focuses on the dynamics of temporal-function relationships and their fundamental bases in order to highlight how the dynamic regulation of polymer interactions programs: 1) polymer assembly and material structure; 2) response to deformation and fracture behavior; 3) dynamic modulation of properties and structural remodeling/self-healing. Here, by exploring this intersection of hydrogel formation, function, and remodeling, this review seeks to shed light on the fundamental relationship between molecular structure, material assembly, and performance in order to connect the emerging area of bioinspired materials processing with tough hydrogel design, and further provides a lasting inspiration and impetus for future hydrogel development that enables valuable scientific and technological advancements.
Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.
Three-dimensional heterostructures are usually created either by assembling two-dimensional building blocks into hierarchical architectures or using stepwise chemical processes that sequentially deposit individual monolayers. Both approaches suffer from a number of issues, including lack of suitable precursors, limited reproducibility, and poor scalability of the preparation protocols. Therefore, development of alternative methods that enable preparation of heterostructured materials is desired. We create heterostructures with incommensurate arrangements of well-defined building blocks using a synthetic approach that comprises mechanical disassembly and simultaneous reordering of layered transition-metal dichalcogenides, MX 2 , and non-layered monochalcogenides, REX, where M = Ta, Nb, RE = Sm, La, and X = S, Se. We show that the discovered solid-state processes are rooted in stochastic mechanochemical transformations directed by electronic interaction between chemically and structurally dissimilar solids toward atomic-scale ordering, and offer an alternative to conventional heterostructuring. Details of composition–structure–properties relationships in the studied materials are also highlighted.
Colloidal synthesis is a powerful bottom-up approach for programmed self-assembly which holds promise for both research and industry. While diverse, each synthetic process is typically restricted to a specific chemistry. Many applications however require composite materials, whereas a chemical equilibrium can typically only match one material but not the other. Here, a scalable general approach is presented, alleviating the dependency on a specific chemical reaction, by resorting to a mechanical equilibrium; an isopycnic density-gradient-step is tailored to form clusters with prescribed composition. Valence control is demonstrated, making dimers, trimers, and tetramers with purity as high as 96%. The measured kinetics shows a scaleable throughput. The density gradient step plays a dual role of both filtering out undesired products and concentrating the target structures. The “Mix-and-Match” approach is general, and applies to a broad range of colloidal matter: diverse material compositions (plastics, glasses, and emulsions); a range of colloidal interactions (van der Waals, Coulomb, and DNA hybridization); and a spectrum of sizes (nanoscale to multiple micrometers). Lastly, the strength of the method is displayed by producing a monodisperse suspension from a highly polydisperse emulsion. The ability to combine colloids into architectures of hybrid materials has applications in pharmaceuticals, cosmetics, and photonics.
HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.