Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cluster assembled materials”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
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 OSTI2020

Morphology and reactivity of size-selected titanium oxide nanoclusters on Au(111)

The morphology and reactivity of mass-selected titania clusters, Ti 3 O 6 and Ti 3 O 5 , deposited onto Au(111) were studied by scanning tunneling microscopy (STM) and temperature programmed desorption (TPD). Despite differing by only one oxygen atom, the stoichiometric Ti 3 O 6 and the sub-stoichiometric (“reduced”) Ti 3 O 5 clusters exhibit very different structures and preferred binding sites. The Ti 3 O 6 clusters preferentially bind at step edges and form small assemblies (2-4 clusters) on Au terraces, while the “reduced” Ti 3 O 5 clusters form much larger fractal-like assemblies that can extend across step boundaries. Annealing the Ti 3 O 5,6 /Au(111) systems to higher temperatures causes changes in the size-distributions of cluster assemblies but does not lead to the formation of TiO x nanoislands for temperatures ≤ 700 K. Reactivity studies show that the reduced Ti 3 O 5 cluster has higher activity than Ti 3 O 6 for 2-propanol dehydration, although both clusters exhibit substantial activity for dehydrogenation to acetone. Calculations using DFT+U suggest that the differences in aggregate morphology and reactivity are associated with the number of undercoordinated Ti 3c sites in the supported clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Confocal Raman Microscopy as a Probe of Material Deconstruction in Processed Low-Density Polyethylene Particles

Confocal Raman microscopy was applied to detect structural change within individual particles of low-density polyethylene (LDPE) following chemical and electrochemical processing steps that aimed to facilitate material decomposition. A high numerical aperture (NA) oil-immersion objective enabled depth-profiling through the near surface region (20 μm–40 μm) of irregularly shaped particles with an axial spatial resolution < 2 μm estimated from measurements of instrument detection efficiency profiles. Changes in vibrational bands sensitive to polyethylene crystallinity were evident following treatments and linked to the release of low molecular weight compounds present as additives and products of processing. Effects of processing were probed by monitoring the rise of Raman scattering intensity in vibrational modes associated with polyethylene chains in a zig-zag (trans) conformation near 1128 cm –1 , 1294 cm –1 , and 1418 cm –1 , signaling chain clustering and development of organized, crystalline-like assemblies. Pristine LDPE particles displayed a uniform structure across the near surface region, while particles treated initially with chemical extractant and then further processed displayed increasingly enhanced crystallinity up to the maximum depth probed (40 μm). As a step toward measurements on ensembles of particles, least squares modeling was adapted to derive pure component spectra reflecting crystallinity change within spectral datasets. The work demonstrates high spatial resolution Raman depth-profiling for the characterization of processed polymers using a high NA immersion objective to overcome the limitations of air-objectives often used for confocal Raman microscopy.

Wahiduzzaman, Md. [Department of Chemistry and Bio↗
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

Exploring electron beam induced atomic assembly via reinforcement learning in a molecular dynamics environment

We report atom-by-atom assembly of functional materials and devices is perceived as one of the ultimate targets of nanotechnology. Recently it has been shown that the beam of a scanning transmission electron microscope can be used for targeted manipulation of individual atoms. However, the process is highly dynamic in nature rendering control difficult. One possible solution is to instead train artificial agents to perform the atomic manipulation in an automated manner without need for human intervention. As a first step to realizing this goal, we explore how artificial agents can be trained for atomic manipulation in a simplified molecular dynamics environment of graphene with Si dopants, using reinforcement learning. We find that it is possible to engineer the reward function of the agent in such a way as to encourage formation of local clusters of dopants under different constraints. This study shows the potential for reinforcement learning in nanoscale fabrication, and crucially, that the dynamics learned by agents encode specific elements of important physics that can be learned.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Covalent adaptable polymer networks with CO 2 -facilitated recyclability

Cross-linked polymers with covalent adaptable networks (CANs) can be reprocessed under external stimuli owing to the exchangeability of dynamic covalent bonds. Optimization of reprocessing conditions is critical since increasing the reprocessing temperature costs more energy and even deteriorates the materials, while reducing the reprocessing temperature via molecular design usually narrows the service temperature range. Exploiting CO 2 gas as an external trigger for lowering the reprocessing barrier shows great promise in low sample contamination and environmental friendliness. Herein, we develop a type of CANs incorporated with ionic clusters that achieve CO 2 -facilitated recyclability without sacrificing performance. The presence of CO 2 can facilitate the rearrangement of ionic clusters, thus promoting the exchange of dynamic bonds. The effective stress relaxation and network rearrangement enable the system with rapid recycling under CO 2 while retaining excellent mechanical performance in working conditions. This work opens avenues to design recyclable polymer materials with tunable dynamics and responsive recyclability.

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

Peroxide-Templated Assembly of a Trimetal Neodymium Complex Single-Molecule Magnet

In this study, we present a tri-metal neodymium complex with two notable qualities. Firstly, the assembly of the complex is templated by peroxide derived from atmospheric oxygen. Secondly, the bulk material behaves as a super-paramagnet, implying that the individual complexes are molecular magnets. The peroxide-templated assembly is possible due to the confluence of the high oxophilicity of neodymium along with the use of an azeotropic distillation synthesis method, which excludes water but admits oxygen. SQUID magnetometer measurements show an extremely high magnetic susceptibility as well as a lack of remanence.

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

Learning and Predicting Photonic Responses of Plasmonic Nanoparticle Assemblies via Dual Variational Autoencoders

In this work, the application of machine learning is demonstrated for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational autoencoder (dual-VAE). In this approach, the information is shared between the latent spaces of two VAEs acting on the particle shape data and spectral data, respectively, but enforcing a common encoding on the shape-spectra pairs. It is shown that this approach can establish the relationship between the geometric characteristics of nanoparticles and their far-field photonic responses, demonstrating that hyperspectral darkfield microscopy can be used to accurately predict the geometry (number of particles, arrangement) of a multiparticle assemblies below the diffraction limit in an automated fashion with high fidelity (for monomers (0.96), dimers (0.86), and trimers (0.58). This approach of building structure-property relationships via shared encoding is universal and should have applications to a broader range of materials science and physics problems in imaging of both molecular and nanomaterial systems.

variational autoencoder↗
DOE OSTI2025

Effect of heteroatom incorporation on electronic communication in metal chalcogenide nanoclusters

Metal chalcogenide nanoclusters (NC), specifically of type TM 6 E 8 (L) 6 (TM = transition metal, E = chalcogen, L = ligand) have garnered attention in recent years as promising catalysts and biosensors due to their remarkable electronic and magnetic properties, as well as their ability to undergo supramolecular assembly into 2D materials. Furthermore, the undercoordinated metal chalcogenide NCs have shown distinct surface reactivity, which is strongly dependent on the composition of the TM core. The differences in the reactivity of the undercoordinated species have been attributed to differences in ligand binding energies. Although ligand binding energies in homometallic NCs have been extensively studied, little is known about the effect of heteroatoms in the core on the strength of ligand binding in metal chalcogenide NCs. In this work, we provide new insights into this topic by examining the relative stability of [Co 6−x Fe x S 8 (PEt 3 ) 6 ] + (x = 0–6) NCs towards fragmentation using collision energy-resolved collision-induced dissociation (CID) experiments. We observe that the ligand binding energy gradually decreases until four Fe atoms are incorporated into the cluster core and then gradually increases until all the Co atoms are replaced with Fe. This experimental trend was compared with the results of density functional theory (DFT) calculations, which indicate drastic differences in the electronic communication between Co and Fe atoms in the TM core. By understanding the effect of heteroatom incorporation on ligand binding energy to the NC core, our work provides important insights into the effect of atom-by-atom substitution on the functional properties of tunable nanostructures.

Havenridge, Shana [Argonne National Laboratory (AN↗
DOE OSTI2022

Continued Verification of MOOSE Structural Mechanics Tools for Modeling Core Bowing Phenomena in Fast Reactors

Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism whereby increased power (which leads to temperature and flux gradients) influences the core to bow into less reactive configurations when the restraint system is properly designed. The phenomenon includes a complex interplay of radiation transport, duct temperature calculations involving fluid flow and heat transfer, and thermo-mechanical responses to the induced temperature and flux gradients. Structural material properties are also important to determining inelastic response to longer term flux gradients which cause irradiation creep and swelling. While core bowing provides a strong negative reactivity feedback when the restraint system is designed properly, it also results in additional forces between assemblies which increase the loads required to extricate them during refueling or control rod movement. Therefore, the restraint system must be designed with these tradeoffs in mind. The first stage of the work, which commenced in FY21 and continues through FY22, assesses thermo-mechanical modeling tools for producing core bowing predictions consistent with conventional tools. The Multiphysics Object Oriented Simulation Environment (MOOSE) Tensor Mechanics and Contact Modules are employed. This status report describes work on additional thermo-mechanical benchmark verification problems with increased complexity from the examples demonstrated in FY21. Several benchmark verification examples were selected from the IAEA verification and validation report. These examples involve clusters of ducts representative of a sector of a hexagonal reactor core which bow into each other and cause contact and load pad elevations, as well as single ducts subjected to irradiation fields undergoing swelling and subsequent bowing. The MOOSE-based results were compared to both IAEA benchmark participants’ results, analytic equations as available, and NUBOW-3D, a beam model code developed by Argonne National Laboratory. In every case, the MOOSE results agreed with other simulations results, providing additional verification basis of the tools for this particular physics application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Construction of Reconfigurable and Polymorphic DNA Origami Assemblies with Coiled‐Coil Patches and Patterns

Abstract DNA origami nanodevices achieve programmable structure and tunable mechanical and dynamic properties by leveraging the sequence‐specific interactions of nucleic acids. Previous advances have also established DNA origami as a useful building block to make well‐defined micron‐scale structures through hierarchical self‐assembly, but these efforts have largely leveraged the structural features of DNA origami. The tunable dynamic and mechanical properties also provide an opportunity to make assemblies with adaptive structures and properties. Here the integration of DNA origami hinge nanodevices and coiled‐coil peptides are reported into hybrid reconfigurable assemblies. With the same dynamic device and peptide interaction, it is made multiple higher‐order assemblies (i.e., polymorphic assembly) by organizing clusters of peptides into patches or arranging single peptides into patterns on the surfaces of DNA origami to control the relative orientation of devices. The coiled‐coil interactions are used to construct circular and linear assemblies whose structure and mechanical properties can be modulated with DNA‐based reconfiguration. Reconfiguration of linear assemblies leads to micron scale motions and ≈2.5‐10‐fold increase in bending stiffness. The results provide a foundation for stimulus‐responsive hybrid assemblies that can adapt their structure and properties in response to nucleic acid, peptide, protein, or other triggers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

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

Supramolecular assembly of blue and green halide perovskites with near-unity photoluminescence

The metal-halide ionic octahedron is the optoelectronic unit for halide perovskites, and a crown ether–assisted supramolecular assembly approach can pack various ionic octahedra into tunable symmetries. In this work, we demonstrate near-unity photoluminescence quantum yield (PLQY) blue and green emission with the supramolecular assembly of hafnium (Hf) and zirconium (Zr) halide octahedral clusters. (18C6@K) 2 HfBr 6 powders showed blue emission with a near-unity PLQY (96.2%), and green emission was also achieved with (18C6@K) 2 ZrCl 4 Br 2 powders at a PLQY of 82.7%. In conclusion, these highly emissive powders feature facile low-temperature solution-based synthesis conditions and maintain high PLQY in solution-processable semiconductor inks under ambient conditions, and they were used in thin-film displays and emissive three-dimensional–printed architectures that exhibited high spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phase separation and state oscillation of active inertial particles

Active matter systems are of great interest for their novel out-of-equilibrium collective behavior. Active Brownian particles (ABPs) are known to exhibit clustering and motility-induced phase separation, and there have been many studies revealing this rich behavior in the overdamped limit of Brownian motion, where inertial effects are insignificant. In this work, we simulate an Active Inertial Particle (AIP) model where we focus on the underdamped, rather than overdamped limit, to study the interplay between particle inertia and collective behavior, such as phase separation. We show that inertia reduces particle motility due to collisions and a longer time delay for particles to regain speed, thereby suppressing phase separation relative to that observed in the overdamped limit. Additionally, we observe interesting oscillatory behavior between a phase separated steady-state and a homogeneous fluid state that results from inertia-induced collective motion within active clusters due to momentum transfer. Such oscillatory behavior has been reported for ABP systems with particle shape anisotropy, where collective motion is mediated by particle shape anisotropy. Furthermore, we confirm that there is no single characteristic frequency for the oscillatory behavior. The power spectral density is a power law in the high frequency domain, with an exponent close to -2.5.

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

Synthesis of Free-Standing Pd-Ni-P Metallic Glass Nanoparticles with Durable Medium-Range Ordered Structure for Enhanced Electrocatalytic Properties

Topologically disordered metallic glass nanoparticles (MGNPs) with highly active and tailorable surface chemistries have immense potential for functional uses. The synthesis of free-standing MGNPs is crucial and intensively pursued because their activity strongly depends on their exposed surfaces. Herein, a novel laser-evaporated inert-gas condensation method is designed and successfully developed for synthesizing free-standing MGNPs without substrates or capping agents, which is implemented via pulse laser-induced atomic vapor deposition under an inert helium atmosphere. In this way, the metallic atoms vaporized from the targets collide with helium atoms and then condense into short-range-order (SRO) clusters, which mutually assemble to form the MGNPs. Using this method, free-standing Pd 40 Ni 40 P 20 MGNPs with a spherical morphology are synthesized, which demonstrates satisfactory electrocatalytic activity and durability in oxygen reduction reactions. Moreover, local structure investigations using synchrotron pair distribution function techniques reveal the transformation of SRO cluster connection motifs of the MGNPs from face-sharing to edge-sharing modes during cyclic voltammetry cycles, which enhances the electrochemical stability by blocking crystallization. Further, this approach provides a general strategy for preparing free-standing MGNPs with high surface activities, which may have widespread functional applications

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploration of Tertiary Structure in Sequence-Defined Polymers Using Molecular Dynamics Simulations

Peptoids are a class of sequence-defined biomimetic polymers with peptide-like backbones and side chains located on backbone nitrogens rather than alpha carbons. These materials demonstrate a strong ability for precise control of single-chain structure, multiunit self-assembly, and macromolecular assembly through careful tuning of sequence due to the diversity of available side chains, although the driving forces behind these assemblies are often not understood. Prior experimental work has shown that linked 15mer peptoids can mimic the protein helical hairpin structure by leveraging the chirality-inducing nature of bulky side chains and hydrophobicity, but there are still gaps in our understanding of the relationship between sequence, stability, and particular secondary or tertiary structure. Here, we present a molecular dynamics (MD) study on the folding behavior of these polymers into hairpins, discussing the differences in structure from sequences with various characteristics in water and acetonitrile, and then compare the handedness preference of common helical motifs between solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗