Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Assembly”

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.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MAL TIR ) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88 TIR ). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88 TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MAL TIR . We demonstrate via mutagenesis that the MyD88 TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88 TIR . Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Many-Body Potential for Simulating Self-Assembly of Polymer-Grafted Nanoparticles in a Polymer Matrix

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In vitro functional analysis of gRNA sites regulating assembly of hepatitis B virus

The roles of RNA sequence/structure motifs, Packaging Signals (PSs), for regulating assembly of an HBV genome transcript have been investigated in an efficient in vitro assay containing only core protein (Cp) and RNA. Variants of three conserved PSs, within the genome of a strain not used previously, preventing correct presentation of a Cp-recognition loop motif are differentially deleterious for assembly of nucleocapsid-like particles (NCPs). Cryo-electron microscopy reconstruction of the T = 4 NCPs formed with the wild-type gRNA transcript, reveal that the interior of the Cp shell is in contact with lower resolution density, potentially encompassing the arginine-rich protein domains and gRNA. Symmetry relaxation followed by asymmetric reconstruction reveal that such contacts are made at every symmetry axis. We infer from their regulation of assembly that some of these contacts would involve gRNA PSs, and confirmed this by X-ray RNA footprinting. Mutation of the ε stem-loop in the gRNA, where polymerase binds in vivo, produces a poor RNA assembly substrate with Cp alone, largely due to alterations in its conformation. The results show that RNA PSs regulate assembly of HBV genomic transcripts in vitro, and therefore may play similar roles in vivo, in concert with other molecular factors.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Coarse-grained molecular dynamics simulation of the interface behaviour and self-assembly of CTAB cationic surfactants

Here, we study the behaviour at interfaces and the micelle self-assembly of a cationic surfactant (CTAB) by Molecular Dynamics (MD) simulations of coarse-grained models. We consider both the standard (with explicit water) Martini force field and the implicit solvent version of the Martini force field (Dry Martini). First, we study the behaviour of CTAB at a water/vacuum interface, at a water/organic solvent interface and in a pre-assembled CTAB micelle using both standard and Dry Martini and all-atomic simulations. Our results indicate that there are significant quantitative differences between the predictions of the two models. Interestingly, implicit solvent simulations with Dry Martini show good quantitative agreement with all-atomic MD simulations, better than explicit solvent Martini MD simulations. The computational efficiency of the Martini and Dry Martini models allowed us to study the self-assembly of CTAB in a large system with many micelles. We observe the self-assembly of CTAB into micelles and also the exchange of CTAB molecules between micelles by events such as micelle fusion and fission which are difficult to observe in all-atomic MD simulations due to the time and length scales involved. Under the studied conditions, both Martini models predict a rather different self-assembly behaviour. The standard Martini model predicts a final equilibrium state with spherical micelles with an average size of ≈70 CTAB molecules. In contrast, the Dry Martini model predicts the formation of large tubular micelles with ≈330 CTAB molecules. Compared with experiments, standard Martini and Dry Martini underestimate and overestimate, respectively, the micelle size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Assembly of three-dimensional binary superlattices from multi-flavored particles

Binary superlattices constructed from nano- or micron-sized colloidal particles have a wide variety of applications, including the design of advanced materials. Self-assembly of such crystals from their constituent colloids can be achieved in practice by, among other means, the functionalization of colloid surfaces with single-stranded DNA sequences. However, when driven by DNA, this assembly is traditionally premised on the pairwise interaction between a single DNA sequence and its complement, and often relies on particle size asymmetry to entropically control the crystalline arrangement of its constituents. The recently proposed “multi-flavoring” motif for DNA functionalization, wherein multiple distinct strands of DNA are grafted in different ratios to different colloids, can be used to experimentally realize a binary mixture in which all pairwise interactions are independently controllable. Here we use various computational methods, including molecular dynamics and Wang–Landau Monte Carlo simulations, to study a multi-flavored binary system of micron-sized DNA-functionalized particles modeled implicitly by Fermi–Jagla pairwise interactions. We show how self-assembly of such systems can be controlled in a purely enthalpic manner, and by tuning only the interactions between like particles, demonstrate assembly into various morphologies. Although polymorphism is present over a wide range of pairwise interaction strengths, we show that careful selection of interactions can lead to the generation of pure compositionally ordered crystals. Additionally, we show how the crystal composition changes with the like-pair interaction strengths, and how the solution stoichiometry affects the assembled structures.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Structurally colored protease responsive nanoparticle hydrogels with degradation-directed assembly

A tunable protease responsive nanoparticle hydrogel (PRNH) that demonstrates large non-iridescent color changes due to a degradation-directed assembly of nanoparticles is reported. Structurally colored composites are fabricated with silica particles, 4-arm poly(ethylene glycol) norbornene (4PEGN), and a proteolytically degradable peptide. When placed in a protease solution, the peptide crosslinks degrade causing electrostatic binding and adsorption of the polymer to the particle surface which leads to the assembly of particles into compact amorphous arrays with structural color. The particle surface charge and size is investigated to probe their effect on the assembly mechanism. Interestingly, only PRNHs with highly negative particle surface charge exhibit color changes after degradation. Ultra-small angle X-ray scattering revealed that the particles become coated in polymer after degradation, producing a material with less order compared to the initial state. Altering the particle diameter modulates the composites’ color, and all sizes investigated (178–297 nm) undergo the degradation-directed assembly. Varying the amount of 4PEGN adjusts the swollen PRNH color and has no effect on the degradation-directed assembly. Finally, taken together, the effects of surface charge, particle size, and polymer concentration allow for the formulation of new design rules for fabricating tunable PRNHs that display vivid changes in structural color upon degradation.

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

Peptoid-directed assembly of CdSe nanoparticles

The high information content of proteins drives their hierarchical assembly and complex function, including the organization of inorganic nanomaterials. Peptoids offer an organic scaffold very similar to proteins, but with a wider solubility range and easily tunable side chains and functional groups to create a variety of self-assembling architectures with atomic precision. If we could harness this paradigm and understand the factors that govern how they direct nucleation and assembly of inorganic materials to design order within such materials, new dimensions of function and fundamental science would emerge. In this work, peptoid tubes and sheets were explored as platforms to assemble colloidal quantum dots (QDs) and clusters. We have successfully synthesized CdSe QDs with difunctionalized capping ligands containing both carboxylic acid and thiol groups and mixed them with maleimide containing peptoids, to create an assembly of the QDs on the peptoid surface via a covalent linkage. This conjugation was seen to be successful with peptoid tubes, sheets and CdSe QDs and clusters. The particles were seen to have a high preference for the peptoid surface but non-specific interactions with carboxylic acid groups on the peptoids limited control over QD density via maleimide conjugation. Replacing the carboxylic acid groups with methoxy ethers, however, allowed for control over QD density as a function of maleimide concentration. 1 H NMR analysis demonstrated that binding of QDs to peptoids involved a subset of surface ligands bound through the carboxylate functional group, allowing the distal thiol to engage in a covalent linkage to the maleimide. Overall, we have shown the compatibility and control of CdSe-peptoid interactions via a covalent linkage with varying peptoid structures and CdSe particles to create complex hybrid structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems

Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Directing the far-from-equilibrium assembly of nanoparticles in confined liquid crystals by hydrodynamic fields

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.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Layered structures of assembled imine-linked macrocycles and two-dimensional covalent organic frameworks give rise to prolonged exciton lifetimes

Ordered organic materials and assemblies have great potential to be tailored to have desirable properties for optoelectronic applications, such as long exciton lifetime and high directional exciton mobility. Framework materials, such as two-dimensional covalent organic frameworks (2D COFs), as well as their truncated macrocyclic analogues, are versatile platforms to organize functional aromatic systems into designed assemblies and robust materials. In this study we investigate the exciton dynamics in a 2D COF, its corresponding hexagonal macrocycle, and extended nanotubes comprised of stacked macrocycles. The excitonic behavior of these three systems provide an understanding of excitonic processes that occur in the plane of the covalently bonded 2D macromolecules and between layers of the nanotubes and 2D COF. The nanotube and analogous 2D COF exhibit longer excited-state lifetimes (~100 ps) compared to the individual, solvated macrocycles (<0.5 ps). These differences are attributed to the internal conversion facilitated by the internal motions of the imine linkages which are significantly reduced in the assembled macrocycles in the nanotube and 2D COF sheets in the layered structures. The exciton diffusion processes in the assembled nanotubes and 2D COF systems were characterized by the autocorrelations of the transition dipole moment of the excitons, giving the depolarization time constants for both systems to be ~1 ps. This work also reveals the anisotropic exciton dynamics related to the in-plane and inter-plane structural factors in these systems. These studies provide guidance for the design of future COF materials, where the longer excited state lifetimes imparted by assembly are beneficial for optoelectronic applications.

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

Designing 1D multiheme peptide amphiphile assemblies reminiscent of natural systems

We discuss protein assemblies that bind and organize ordered arrays of cofactors yield function structures. Multiheme assemblies found in nature yield electronically conductivity 1D nanoscale fibers and are employed in anaerobic respiration. To understand the fundamental characteristics of these organized arrays, the design of peptide amphiphiles that assemble into 1D nanostructures and yield metalloporphyrin binding sites is presented. One challenge with this class of peptide amphiphiles is identifying the correct sequence composition for high affinity binding with high heme density. Here, the peptide c16-AH(Kx)n-CO 2 H is explored to identify the impact of sequence length (n) and amino acid identity (x = L, I, or F) on binding affinity and midpoint potential. When n = 2, the peptide assembly yields the greatest affinity. The resulting nanoscale assemblies yield ordered arrays of the redox active molecule heme and have potential utility in the development of supramolecular bioelectronic materials useful in sensing as well as the development of enzymatic materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Sequence-dependent self-assembly of supramolecular nanofibers in periodic dynamic block copolymers

Block copolymers (BCPs) can spontaneously self-assemble into various nanostructured morphologies which enable their diverse applications in selective membranes, polymer electrolytes, and optoelectronics. To expand the range of nanostructures accessible to block copolymers, we designed dynamic block copolymers (DBCPs) that combine the phase separation of traditional block copolymers with the supramolecular self-assembly of periodic dynamic polymers. We demonstrate that DBCPs synthesized with a periodic block sequence self-assemble into high aspect ratio supramolecular nanofibers with well-ordered PEG and PDMS domains, in contrast to those synthesized with a random sequence which do not form nanofibers but have disordered morphologies. The periodicity of the block sequence ensures regular placement of dynamic bonds along the polymer chain, which enables stacking of the hydrogen bonding units into ordered 1D supramolecular nanofibers and delays the onset of terminal flow by up to 60 °C compared to the random block sequence. The hierarchically assembled supramolecular nanofibers display complex mechanical and thermal phase behavior arising from the interplay between phase separation of the dissimilar polymer backbones and supramolecular interactions between dynamic bonds. Despite identical bulk composition, the periodic DBCPs demonstrate ionic conductivity values over two orders of magnitude higher than their random counterparts due to the formation of well-ordered, interconnected, high aspect ratio ion-transporting PEG domains. In conclusion, these results highlight the potential for DBCPs as an emerging material platform to achieve advanced, self-assembled nanostructured morphologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assembly of small silica nanoparticles using lipid-tethered DNA ‘bonds’

Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.

Chiang, Huat Thart [Univ. of Washington, Seattle, ↗
DOE OSTI2025

Electrosome assembly: Structural insights from high voltage-activated calcium channel (CaV)–chaperone interactions

Ion channels are multicomponent complexes (termed here as“electrosomes”) that conduct the bioelectrical signals required for life. It has been appreciated for decades that assembly is critical for proper channel function, but knowledge of the factors that undergird this important process has been lacking. Although there are now exemplar structures of representatives of most major ion channel classes, there has been no direct structural information to inform how these complicated, multipart complexes are put together or whether they interact with chaperone proteins that aid in their assembly. Recent structural characterization of a complex of the endoplasmic membrane protein complex (EMC) chaperone and a voltage-gated calcium channel (CaV) assembly intermediate comprising the pore-forming CaVα1 and cytoplasmic CaVβ subunits offers the first structural view into the assembly of a member of the largest ion channel class, the voltagegated ion channel (VGIC) superfamily. The structure shows how the EMC remodels the CaVα1/CaVβ complex through a set of rigid body movements for handoff to the extracellular CaVα2δ subunit to complete channel assembly in a process that involves intersubunit coordination of a divalent cation and ordering of CaVα1 elements. These findings set a new framework for deciphering the structural underpinnings of ion channel biogenesis that has implications for understanding channel function, how drugs and disease mutations act, and for investigating how other membrane proteins may engage the ubiquitous EMC chaperone.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Free energy of metal-organic framework self-assembly

Metal-organic frameworks (MOFs) represent an important class of materials. Careful selection of building blocks allows for tailoring of the properties of the resulting framework. The self-assembly process, however, is not understood, and without detailed knowledge of the underlying molecular mechanism, it is difficult to anticipate whether a particular design can be realized, or whether the material adopts a metastable, kinetically arrested state. We present a detailed examination of early-stage self-assembly pathways of the MOF-5. Enhanced sampling techniques are used to model a self-assembly in an explicit solvent (dimethylformamide, DMF). We identify several free energy barriers encountered during the assembly of the final MOF, which arise from structural rearrangements preceding MOF formation and from disrupted MOF-solvent interactions as formation proceeds. In all cases considered here, MOFs exhibit favorable entropic gains during the assembly. More generally, the strategy presented provides a step toward the experimental design characterizing the formation of ordered frameworks and possible sources of polymorphism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Dissipative particle dynamics for directed self-assembly of block copolymers

The dissipative particle dynamics (DPD) simulation method has been shown to be a promising tool to study self-assembly of soft matter systems. In particular, it has been used to study block copolymer (BCP) self-assembly. However, previous parameterizations of this model are not able to capture most of the rich phase behaviors of BCPs in thin films nor in directed self-assembly (chemoepitaxy or graphoepitaxy). Here, we extend the applicability of the DPD method for BCPs to make it applicable to thin films and directed self-assembly. Our new reparameterization not only is able to reproduce the bulk phase behavior but also manages to predict thin film structures obtained experimentally from chemoepitaxy or graphoepitaxy. A number of different complex structures, such as bilayer nanomeshes, 90° bend structures, circular cylinders/lamellae and Frank-Kasper phases directed by trenches, and post arrays or chemically patterned substrates, have all been reproduced in this work. This reparameterized DPD model should serves as a powerful tool to predict BCP self-assembly, especially in some complex systems where it is difficult to implement self-consistent field theory.

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

Photophysics of graphene quantum dot assemblies with axially coordinated cobaloxime catalysts

We report a study of chromophore-catalyst assemblies composed of light harvesting hexabenzocoronene (HBC) chromophores axially coordinated to two cobaloxime complexes. The chromophore-catalyst assemblies were prepared using bottom-up synthetic methodology and characterized using solid-state NMR, IR, and x-ray absorption spectroscopy. Detailed steady-state and time-resolved laser spectroscopy was utilized to identify the photophysical properties of the assemblies, coupled with time-dependent DFT calculations to characterize the relevant excited states. The HBC chromophores tend to assemble into aggregates that exhibit high exciton diffusion length (D = 18.5 molecule 2 /ps), indicating that over 50 chromophores can be sampled within their excited state lifetime. We find that the axial coordination of cobaloximes leads to a significant reduction in the excited state lifetime of the HBC moiety, and this finding was discussed in terms of possible electron and energy transfer pathways. By comparing the experimental quenching rate constant (1.0 × 10 9 s -1 ) with the rate constant estimates for Marcus electron transfer (5.7 × 10 8 s -1 ) and Förster/Dexter energy transfers (8.1 × 10 6 s -1 and 1.0 × 10 10 s -1 ), we conclude that both Dexter energy and Marcus electron transfer process are possible deactivation pathways in CoQD-A. No charge transfer or energy transfer intermediate was detected in transient absorption spectroscopy, indicating fast, subpicosecond return to the ground state. Finally, these results provide important insights into the factors that control the photophysical properties of photocatalytic chromophore-catalyst assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Upsampling Monte Carlo reactor simulation tallies in depleted LWR assemblies fueled with LEU and HALEU using a convolutional neural network

Simulating nuclear reactor cores at the highest achievable spatial and energy resolution is critical in modeling these systems accurately. Increasing the resolution, however, can dramatically increase the memory and central processing unit time required to run simulations. A convolutional neural network was shown previously to accurately upsample tally results of simulated light water reactor assemblies fueled with fresh, low enriched uranium. Here, we show that a convolutional neural network can be used to upsample tally results in assemblies containing fresh and depleted fuel enriched from 1.6 to 19.9 atom percent. The network was trained using neutron flux tallies from simulations of light water reactor assemblies with a range of fuel and coolant temperatures and a diverse selection of geometries. Accurate predictions of flux tallies are possible even on test assemblies with geometries and burnup levels well outside the range of those present in the training and validation data. The network improves the data density by a factor of 8 over a broad range of light water reactor assemblies while incurring insignificant additional computational cost to a Monte Carlo simulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗