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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-Based Supraballs Using Combined Experimental and Simulation Techniques

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. In this work, we use a computational approach to first reconstruct the nanoparticles’ assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Controlling Amphiphilic Polymer Folding beyond the Primary Structure with Protein-Mimetic Di(Phenylalanine)

While methods for polymer synthesis have proliferated, their functionality pales in comparison to natural biopolymers–strategies are limited for building the intricate network of noncovalent interactions necessary to elicit complex, protein-like functions. Using a bioinspired di(phenylalanine) acrylamide (FF) monomer, we explored the impact of various noncovalent interactions in generating ordered assembled structures. Amphiphilic copolymers were synthesized that exhibit β-sheet-like local structure upon collapsing into single-chain assemblies in aqueous environments. Here, the systematic analysis of a series of amphiphilic copolymers illustrated that the global collapse is primarily driven by hydrophobic forces. Hydrogen-bonding and aromatic interactions stabilize local structure, as β-sheet-like interactions were identified via circular dichroism and thioflavin T fluorescence. Similar analysis of phenylalanine (F) and alanine-phenylalanine acrylamide (AF) copolymers found that distancing the aromatic residue from the polymer backbone is sufficient to induce β-sheet-like local structure akin to the FF copolymers; however, the interactions between AF subunits are less stable than those formed by FF. Further, hydrogen-bond donating hydrophilic monomers disrupt internal structure formed by FF within collapsed assemblies. Collectively, these results illuminate design principles for the facile incorporation of multiple facets of protein-mimetic, higher-order structure within folded synthetic polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tubulin Double Helix: Lateral and Longitudinal Curvature Changes of Tubulin Protofilament

By virtue of their native structures, tubulin dimers are protein building blocks that are naturally pre-programmed to assemble into cytoskeletal polymers known as microtubules (MTs). Here we demonstrate polycation-directed (i.e. electrostatically tunable) assembly of tubulins through tubulin protofilament conformational changes in the longitudinal and lateral directions, creating novel tubulin double helices and various tubular architectures. Synchrotron small angle X-ray scattering and transmission electron microscopy reveal a remarkable range of nanoscale assembly structures: single- and double-layered double-helix tubulin tubules. The phase transitions from MTs into the new assemblies are dependent on the size and concentration of polycations. Two characteristic scales that determine the number of observed phases are the size of polycation compared to the size of tubulin (≈4 nm) and MT diameter (≈25 nm). This work suggests the feasibility of “programmable breakdown” of protein nanotubes, tearing MTs into double-stranded tubulins and building up previously undiscovered nanostructures, by using polycations with scissor- and glue-like properties. Importantly, we define a new role of tubulins as two-dimensionally shape-controllable building blocks for novel supramolecular architectures. Furthermore, these findings provide insight into the design of protein-based functional materials, for example, as metallization templates for nanoscale electronic devices, kinesin motor-driving molecular screws, and anticancer drug delivery vehicles.

2D shape‐control↗
DOE OSTI2023

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3 rd among 26 CASP15 server predictors and MULTICOM_human ranked 7 th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Towards a predictive, physics-based friction model for the dynamics of jointed structures

Bolted connections are ubiquitous in mechanical designs and pose a significant challenge to understanding and predicting the vibration response of assembled structures. The present paper develops a physics-based rough contact model of the frictional interactions within a joint. This model sums over the probable interactions of asperities – defined as locally maximum surface features – to determine the contact forces. Here, the tangential contact forces vary smoothly between sticking and slipping and allow the model to better capture the qualitative trends of experimental amplitude dependent frequency and damping than previous studies. Furthermore, the novel model is generalized to allow for arbitrarily varying normal pressure including potential separation to better represent the interfacial dynamics. This includes developing a new, computationally tractable approximation to the analytical Mindlin partial slip solution for tangential loading of contacting spheres. Further, the results highlight the importance of accurately characterizing the as-built topology of the interface, the plastic behavior of the contacting asperities, the relevant length scale of asperities, and the eccentricity of asperities. A predictive friction coefficient based on plasticity provides a poor match to experiments, so fitting the friction coefficient is also considered. Numerical results are compared to experiments on the Brake-Reuß Beam to assess the predictive potential of the models. While blind predictions over-predict the slip limit, the current model presents a significant improvement in physics-based modeling and highlights areas for ongoing research.

42 ENGINEERING↗
DOE OSTI2022

Observations of phase changes in monoolein during high viscous injection

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Designing Imidazolium Poly(amide-amide) and Poly(amide-imide) Ionenes and Their Interactions with Mono- and Tris(imidazolium) Ionic Liquids

Here we introduce the synthesis and thermal properties of a series of sophisticated imidazolium ionenes with alternating amide-amide or amide-imide backbone functionality, and investigate the structural effects of mono(imidazolium) and unprecedented tris(imidazolium) ionic liquids (ILs) in these ionenes. The new set of poly(amide-amide) (PAA) and poly(amide-imide) (PAI) ionenes represent the intersection of conventional high-performance polymers with the ionene archetype–presenting polymers with alternating functional and ionic elements precisely sequenced along the backbone. The effects of polymer composition on the thermal properties and morphology were analyzed. Five distinct polymer backbones were synthesized and combined with a stoichiometric equivalent of the IL 1-benzyl-3-methylimidazolium bistriflimide ([Bnmim][Tf 2 N]), which were studied to probe the self-assembly, structuring, and contributions of intermolecular forces when IL is added. Furthermore, three polyamide (PA) or polyimide (PI) ionenes with simpler xylyl linkages were interfaced with [Bnmim][Tf 2 N] as well as a novel amide-linked tris(imidazolium) IL, to demonstrate the structural changes imparted by the inclusion of functional, ionic additives dispersed within the ionene matrix. This work highlights the possibilities for utilizing concepts from small molecules which exhibit supramolecular self-assembly to guide creative design and manipulate the structuring of ionenes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fundamental Processes and Practical Considerations of Lead Chalcogenide Mesocrystals Formed via Self-Assembly and Directed Attachment of Nanocrystals at a Fluid Interface

Significant advances in the synthesis and processing of colloidal nanocrystals have given scientists and engineers access to a vast library of building blocks with precisely defined size, shape, and composition. These materials have inspired exciting prospects to enable bottom-up fabrication of programmable materials with properties by design. Successfully assembling and connecting the building blocks into superstructures in which constituent nanocrystals can purposefully interact requires robust understanding of and control over a complex interplay of dynamic physicochemical processes. Fluid interfaces provide an advantageous experimental workbench to both probe and control these processes. Despite the ostensible simplicity of fabricating nanocrystal assemblies at a fluid interface, sensitivity to processing conditions and limited reproducibility have underscored the complexity of this process. In situ studies have provided mechanistic insights into the competing dynamics of key subprocesses including solvent spreading and evaporation, superlattice formation, ligand detachment kinetics, and nanocrystal attachment. Understanding how these subprocesses influence the complex choreography of self-assembly, structure transformation, and oriented attachment processes presents a rich research challenge. In this context, we present a detailed methodology for self-assembly and attachment of lead chalcogenide nanocrystals at a liquid–gas interface as a model system for the fabrication of mono- and multilayer cubic connected superlattices. We discuss key experimental parameters such as the characteristics of the building blocks and processing conditions and detailed steps from colloidal nanocrystal injection to superlattice transfer. Furthermore, we hope that this Methods/Protocols paper will provide guidance for future advances in the exciting path toward bringing the prospect of nanocrystal-based programmable materials to fruition.

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

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Protein-Mimetic Self-Assembly with Synthetic Macromolecules

Protein-mimetic amphiphiles have significant promise as a platform to access the complex functions of natural biological materials and incorporate the tunability and environmental resilience of synthetic materials. The fields of polymer chemistry and chemical biology have concurrently approached the development of biomimetic amphiphiles with materials ranging from random amphiphilic copolymers to peptide–lipid conjugates. In this Perspective, we incorporate strategies from diverse chemical arenas for controlling assembled morphologies and dynamics of protein-mimetic synthetic macromolecules. An overview of significant advances in peptide amphiphiles and single-chain polymer nanoparticles provides the foundation for comparing recent advances in the implementation of multiple intermolecular interactions and computational strategies to fine-tune the assembled structures. We aim to bridge these fields, combining insights from multiple disciplines to inspire new approaches for the development of protein-mimetic materials, as these assemblies have far-reaching applications including in the development of new sensors, catalysts, and therapeutics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Device-quality, reconfigurable metamaterials from shape-directed nanocrystal assembly

Significance Colloidal nanocrystals with defined sizes and shapes are ideal building blocks for nanofabrication. However, the ability to arbitrarily arrange them on surfaces with control over their orientation remains elusive. Here we report a shallow-template-assisted DNA-mediated assembly strategy to precisely arrange colloidal nanocrystals on surfaces, with single-particle control across submillimeter areas. In addition, the oligonucleotide bonds between the nanocrystals and substrate can be reversibly expanded and contracted enabling postsynthetic tunability of the assembled structures. Using this approach, we synthesized a nanocrystal-based, dynamically tunable metasurface (an anomalous reflector), thereby illustrating the potential for unique device construction via DNA programmable assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Self‐Assembled LuFeO 3 /LuFe 2 O 4 Heterostructure with Emergent Ferroic Orderings

Abstract Achieving self‐assembling structures that exhibit emergent properties and functionalities is one of the holy grails in nanotechnology and holds great promise for a wide range of potential applications. Herein, a self‐assembled LuFeO 3 –(1/3)LuFe 2 O 4 –LuFeO 3 heterostructure that consists of two model multiferroics, i.e., hexagonal LuFeO 3 and rhombohedral LuFe 2 O 4 , is reported in single‐layer epitaxial LuFeO 3 thin films. Atomic‐scale electron microscopy investigations reveal the spontaneous organization of ferroelectric polarization in each building block, which forms a series of polar configurations. Specifically, the charge and lattice of neighboring LuFeO 3 and LuFe 2 O 4 blocks are closely coupled with competing degrees of freedom. A combination of the quantitative analysis of atomically resolved images and spectroscopy with theoretical calculations determines how charge‐ordering‐induced polarization accommodates charge naturality across the interfaces to reduce the system energy and unravels the formation mechanism of this heterostructure. The results point to the possibilities of generation and control of multiferroic self‐assembled systems, which may provide a basis for engineering novel materials with emergent properties.

Deng, Shiqing↗
DOE OSTI2021

Mesoscale Frank–Kasper Crystal Structures from Dendron Assembly by Controlling Core Apex Interactions

Single-component polymeric materials open up a great potential for self-assembly into mesoscale complex crystal structures that are known as Frank-Kasper (FK) phases. Predicting the packing structures of the soft-matter spheres, however, remains a challenge even when the molecular design is precisely known. Here, we investigate the role of the molecules' enthalpic interaction in determining the low-symmetry crystal structures. To this end, we synthesize architecturally asymmetric dendrons by varying their apex functionalities and examine the packing structures of the second-generation (G2) dendritic wedges. Our work shows that weakening the hydrogen bonding of the dendron apex makes the particles softer and smaller, and leads to the formation of various FK structures at lower temperatures, including the new observation of a FK C14 phase in the cone-shaped dendron systems. As a consequence of the free energy balance between the particle's interfacial tension and the chain's stretching, various packing structures are mainly tuned by designing the hydrogen bonding interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Precise Control of Dissipative Self-assembly by Light and Electricity

Nature-inspired synthetic dissipative self-assemblies have attracted much attention recently. However, it remains a major challenge to achieve precise control over dissipative supramolecular assembly structures and functions of self-contained systems. Here we combine light and electricity as two clean, and spatiotemporally addressable fuels to provide precise control over the morphology for dissipative self-assembly of a perylene bisimide glycine (PBIg) building block in a self-contained solution. In this design, electrochemical oxidation provides the positive fuel to activate PBIg self-assembly while photoreduction supplies the negative fuel to deactivate the system for disassembly. Further, through programming the two counteracting fuels, we demonstrated the control of PBIg self-assembly into a variety of assembly morphologies in a self-contained system. In addition, by exerting light and electrical dual fuels simultaneously, we could create an active homeostasis exhibiting dynamic instability, leading to morphological change to asymmetric assemblies with curvatures. Such precise control over self-assembly of self-contained systems may find future applications in programming complex active materials as well as formulating pharmaceutical reagents with desired morphologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Characterisation of nano-assemblies inside mesopores using neutron scattering

Adsorption of molecular and nanoscale matter in mesoporous materials is important in filtration and chromatography as well as membrane processes. However, the morphology and distribution of self-assembled structures of adsorbate formed within nanoconfined environments is largely unknown. Small Angle Neutron Scattering (SANS) with porous matrix matching the neutron scattering length density of the solvent has the potential to provide detailed information on the self-assemblies formed in pore spaces. However, analysis of such SANS profiles remains a challenge. In this study, we extend the SANS analysis method previously developed by Findenegg and co-workers to include interparticle correlations, providing a qualitative characterisation of the adsorption state of surfactants and nanoparticles in the cylindrical pores of silica nanomaterials. We find that the pore filling fraction and the self-assembled state of the adsorbate governs the scattering profile. We apply the model to two materials namely, triethyleneglycol monohexyl ether (C 6 E 3 ) surfactant and gold nanoparticles adsorbed in SBA-15 mesoporous silica. In contrast to the C 6 E 3 system, Bragg scattering dominates the diffuse scattering in gold nanoparticle system, which we attribute to the immobile internal structure of the nanoparticles. In conclusion, this new SANS analysis method has potential to elucidate structures of soft matter nanoassemblies inside mesopores.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Perspectives on three-dimensional printing of self-assembling materials and structures

Spiders, silks, and webs are marvels of nature that have inspired high-performance material design, resilient structural design, and innovative manufacturing in the materials science and engineering fields. In this article, we review the roles and mechanisms of self-assembly and spinning processes for making hierarchical structures of synthetic and natural fibers with multifunctionality. We discuss the ability of spider webs to maintain their functionality under construction while withstanding predator, human, and environmental threats, which comes from their self-assembled structures from nanoscales to macroscales. We conclude by exploring the future of novel mobile, autonomous, time- and cost-effective spider-inspired three-dimensional printing technology for making resilient biomaterials, structures, and synthetic silk materials.

42 ENGINEERING↗