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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modulating the Extent of Anisotropic Cuprophilicity via High Pressure with Piezochromic Luminescence Sensitization

We report metallophilicity has been widely studied as a fundamental supramolecular interaction. However, the extent and directionality thereof remain controversial. A major obstacle lies in the difficulty to separately control the geometry and chemical composition. Herein, we address this challenge by modulating metallophilicity with mechanical pressure. Using a multinuclear Cu(I) complex as model system, we report anomalous anisotropies of (supra)molecular structures, vibrations, and interaction energies upon isotropic compression as well as concomitant (essentially turn-on) piezochromic luminescence enhancement with ~10 3 modulation. The in situ characterizations indicate opposite behaviors of contact distances and cuprophilic interactions for intermolecular vs intramolecular Cu-Cu pairs under pressure. Theoretical calculations break down the attractive and repulsive forces associated with cuprophilicity, its spontaneous 4p-3d hybridization origin, and direction-dependent interaction strength. The use of isotropic mechanical force reveals the intrinsic anisotropy of metallophilicity in multinuclear systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2022

Patterning of magneto-optical nanomaterials

Patterning of colloidal particles in precisely organized architectures has attracted intense research interest for decades. This is due to their potential applications in flexible electronics, magnetic and optical devices, sensors, biotechnology, communications, etc. However, creation of mesoscale assemblies at commercial scales have received less attention. The mesoscale systems reside between the micro- and macroscopic scales, with length dimensions from ≈ 100 µm to 5 mm. By leveraging decades of experimental and theoretical research in nanomaterial fields, we were able to precisely create and control the placement of nanoscale materials, allowing us to create mesoscale materials. We developed a versatile and automatic mesoscale patterning technology (via SEM-FIB and 3D printing) that provides precise and consistent control and special arrangement of functional nanomaterials. The versatility of the strategy is demonstrated by patterning nanoparticles with different dimensions, shapes and compositions, tethered with various functionalities and subjected to different external stimuli.

42 ENGINEERING↗
DOE OSTI2021

Hydrophobe Containing Polypeptoids Complex with Lipids and Induce Fusogenesis of Lipid Vesicles

The hydrophobic effect of alkyl group insertion into phospholipid bilayers is exploited in modifying and modulating vesicle structure. We show that amphiphilic polypeptoids (peptide mimics) with n-decyl side chains, which we term as hydrophobe-containing polypeptoids (HCPs), can insert the alkyl hydrophobes into the membrane bilayer of phospholipid-based vesicles. Such insertion leads to disruption of the liposomes and the formation of HCP–lipid complexes that are colloidally stable in aqueous solution. Interestingly, when these complexes are added to fresh liposomes, remnant uncomplexed hydrophobes (the n-decyl groups) bridge liposomes and fuse them. The fusion leads to the engulfing of liposomes and the formation of multilayered vesicles. The morphology of the liposome system can be changed from stopping fusion and forming clustered vesicles to the continued formation of multilayered liposomes simply by controlling the amount of the HCP–lipid complex added. The entire procedure occurs in aqueous systems without the addition of any other solvents. There are several implications to these observations including the biological relevance of mimicking fusogenic proteins such as the SNARE proteins and the development of new drug delivery technologies to impact delivery to cell organelles.

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

A simple catch: Fluctuations enable hydrodynamic trapping of microrollers by obstacles

It is known that obstacles can hydrodynamically trap bacteria and synthetic microswimmers in orbits, where the trapping time heavily depends on the swimmer flow field and noise is needed to escape the trap. Here, we use experiments and simulations to investigate the trapping of microrollers by obstacles. Microrollers are rotating particles close to a bottom surface, which have a prescribed propulsion direction imposed by an external rotating magnetic field. The flow field that drives their motion is quite different from previously studied swimmers. We found that the trapping time can be controlled by modifying the obstacle size or the colloid-obstacle repulsive potential. We detail the mechanisms of the trapping and find two remarkable features: The microroller is confined in the wake of the obstacle, and it can only enter the trap with Brownian motion. While noise is usually needed to escape traps in dynamical systems, here, we show that it is the only means to reach the hydrodynamic attractor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Colloidal quasicrystals engineered with DNA

In principle, designing and synthesizing almost any class of colloidal crystal is possible. Nonetheless, the deliberate and rational formation of colloidal quasicrystals has been difficult to achieve. Here we describe the assembly of colloidal quasicrystals by exploiting the geometry of nanoscale decahedra and the programmable bonding characteristics of DNA immobilized on their facets. Further, this process is enthalpy-driven, works over a range of particle sizes and DNA lengths, and is made possible by the energetic preference of the system to maximize DNA duplex formation and favour facet alignment, generating local five- and six-coordinated motifs. This class of axial structures is defined by a square–triangle tiling with rhombus defects and successive on-average quasiperiodic layers exhibiting stacking disorder which provides the entropy necessary for thermodynamic stability. Taken together, these results establish an engineering milestone in the deliberate design of programmable matter.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanoscale Spatial Distribution of Supported Nanoparticles Controls Activity and Stability in Powder Catalysts for CO Oxidation and Photocatalytic H 2 Evolution

Here we discuss, supported metal nanoparticles are essential components of high-performing catalysts, and their structures are intensely researched. In comparison, nanoparticle spatial distribution in powder catalysts is conventionally not quantified, and the influence of this collective property on catalyst performance remains poorly investigated. Here, we demonstrate a general colloidal self-assembly method to control uniformity of nanoparticle spatial distribution on common industrial powder supports. We quantify distributions on the nanoscale using image statistics and show that the type of nanospatial distribution determines not only the stability, but also the activity of heterogeneous catalysts. Widely investigated systems (Au–TiO 2 for CO oxidation thermocatalysis and Pd–TiO 2 for H 2 evolution photocatalysis) were used to showcase the universal importance of nanoparticle spatial organization. Spatially and temporally resolved microkinetic modeling revealed that nonuniformly distributed Au nanoparticles suffer from local depletion of surface oxygen, and therefore lower CO oxidation activity, as compared to uniformly distributed nanoparticles. Nanoparticle spatial distribution also determines the stability of Pd–TiO 2 photocatalysts, because nonuniformly distributed nanoparticles sinter while uniformly distributed nanoparticles do not. This work introduces new tools to evaluate and understand catalyst collective (ensemble) properties in powder catalysts, which thereby pave the way to more active and stable heterogeneous catalysts.

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

Incoherent nonadiabatic to coherent adiabatic transition of electron transfer in colloidal quantum dot molecules

Electron transfer is a fundamental process in chemistry, biology, and physics. One of the most intriguing questions concerns the realization of the transitions between nonadiabatic and adiabatic regimes of electron transfer. Using colloidal quantum dot molecules, we computationally demonstrate how the hybridization energy (electronic coupling) can be tuned by changing the neck dimensions and/or the quantum dot sizes. This provides a handle to tune the electron transfer from the incoherent nonadiabatic regime to the coherent adiabatic regime in a single system. We develop an atomistic model to account for several states and couplings to the lattice vibrations and utilize the mean-field mixed quantum-classical method to describe the charge transfer dynamics. Here, we show that charge transfer rates increase by several orders of magnitude as the system is driven to the coherent, adiabatic limit, even at elevated temperatures, and delineate the inter-dot and torsional acoustic modes that couple most strongly to the charge transfer dynamics.

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

Using active matter to introduce spatial heterogeneity to the susceptible infected recovered model of epidemic spreading

Abstract The widely used susceptible-infected-recovered (S-I-R) epidemic model assumes a uniform, well-mixed population, and incorporation of spatial heterogeneities remains a major challenge. Understanding failures of the mixing assumption is important for designing effective disease mitigation approaches. We combine a run-and-tumble self-propelled active matter system with an S-I-R model to capture the effects of spatial disorder. Working in the motility-induced phase separation regime both with and without quenched disorder, we find two epidemic regimes. For low transmissibility, quenched disorder lowers the frequency of epidemics and increases their average duration. For high transmissibility, the epidemic spreads as a front and the epidemic curves are less sensitive to quenched disorder; however, within this regime it is possible for quenched disorder to enhance the contagion by creating regions of higher particle densities. We discuss how this system could be realized using artificial swimmers with mobile optical traps operated on a feedback loop.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Initial Engineering Framework for Species Tracking in MSRs Involving Fuel Salt and Structures

This report implements a high-fidelity multiphysics modeling framework using the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program tools to track leaching and plating of materials between the fuel salt and structures in Molten Salt Reactors (MSRs). Specifically, this framework is demonstrated in modeling various processes within MSRs including hot and cold leg corrosion, redox potential driven corrosion, colloid precipitation and deposition, and noble metal plating and decay heat modeling. The model integrates neutronics, thermal-hydraulics, depletion, and thermochemistry to simulate the evolving chemical behavior of the fuel salt in interactions with structural materials. Initial findings suggest that hot-cold leg corrosion in MSR systems may become significant if the redox potential of the fuel salt is not sufficiently controlled. Additionally, the impact of noble metal decay heat deposition in large power reactors is explored. The resulting engineering framework for species tracking will be applied in the future toward specific validation work with ongoing experimental efforts focusing on both chloride and fluoride salt loop experiments with in-situ corrosion and redox control instrumentation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2024

Radiation-induced transients on solid and molten Li and K iodides

The study, quantification, and monitoring of iodine in nuclear power generation systems have been paramount due to its environmental and health implications. Thorough speciation and transport studies strengthened the development and deployment of water reactors, which are now required for the new generation of Molten Salt Reactors (MSR), where the fuel and coolant are a complex liquid system of suitable halides. The speciation, radiation-induced chemistry, and transport of iodine (I-127, I-129 and I-131) under extreme conditions of temperature and ionizing radiation are among the challenges for the future implementation of MSR’s. In aqueous systems, the triiodide-iodine-iodide (I3--I2-I-) equilibrium is strongly dependent on the conditions of the medium. In molten iodides and chlorides, the triiodide detection (and its disproportionation) poses challenges due to the extreme conditions of temperature and radiation, but studies have shown a dependence on temperature, absorbed dose and salt composition. Through absorption spectroscopy techniques (diffuse reflectance and high-temperature UV-Vis), as well as resonance (Electron Paramagnetic Resonance) it is possible to identify primary transients induced by ionizing radiation trapped in the solid phase (Solid-state radiolysis), and steady-state main absorption components with a fast-acquisition real-time spectroscopy. The presence of heterogeneous phase (colloids), viscosity changes, and gas evolution are among the observed processes. A specific case of study is speciation in the presence of Ni. A corrosion product with magnetic properties due to unpaired electrons in its electronic structure. Ferromagnetic materials are monitored in solidified salts to identify aggregation and phase separation. Comparative studies of eutectic mixtures of LiI-KI and LiCl-KCl with known addition of dopants will be presented, with a perspective of radiation chemistry and its possible implications in complex systems.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Tuning Stoichiometry to Promote Formation of Binary Colloidal Superlattices

The self-assembly of binary nanoparticle superlattices from colloidal mixtures is a promising method for the fabrication of complex colloidal cocrystal structures. However, binary mixtures often form amorphous or metastable phases instead of the thermodynamically stable phase. Here we show that in binary mixtures of differently sized spherical particles, an excess of the smaller component can promote—and, in some cases, may be necessary for—the self-assembly of a binary cocrystal. Using computer simulations, we identify two mechanisms responsible for this phenomenon. First, excess small particles act like plasticizers and enable systems to reach a greater supersaturation before kinetic arrest occurs. Second, they can disfavor competing structures that may interfere with the growth of the target structure. We find the phase behavior of simulated mixtures of nearly hard spheres closely matches published experimental results. We demonstrate the generality of our findings for mixtures of particles of arbitrary shape by presenting a binary mixture of hard shapes that only self-assembles with an excess of the smaller component.

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

Optical and Magneto-Optical Properties of Donor-Bound Excitons in Vacancy-Engineered Colloidal Nanocrystals

Controlled insertion of electronic states within the band gap of semiconductor nanocrystals (NCs) is a powerful tool for tuning their physical properties. One compelling example is II–VI NCs incorporating heterovalent coinage metals in which hole capture produces acceptor-bound excitons. To date, the opposite donor-bound exciton scheme has not been realized because of the unavailability of suitable donor dopants. Here, we produce a model system for donor-bound excitons in CdSeS NCs engineered with sulfur vacancies (V S ) that introduce a donor state below the conduction band (CB), resulting in long-lived intragap luminescence. V S -localized electrons are almost unaffected by trapping, and suppression of thermal quenching boosts the emission efficiency to 85%. Magneto-optical measurements indicate that the V S are not magnetically coupled to the NC bands and that the polarization properties are determined by the spin of the valence-band photohole, whose spin flip is massively slowed down due to suppressed exchange interaction with the donor-localized electron.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Polariton-assisted incoherent to coherent excitation energy transfer between colloidal nanocrystal quantum dots

Here, we explore the dynamics of energy transfer between two nanocrystal quantum dots placed within an optical microcavity. By adjusting the coupling strength between the cavity photon mode and the quantum dots, we have the capacity to fine-tune the effective coupling between the donor and acceptor. Introducing a non-adiabatic parameter, γ, governed by the coupling to the cavity mode, we demonstrate the system’s capability to shift from the overdamped Förster regime (γ $\ll$ 1) to an underdamped coherent regime (γ $\gg$ 1). In the latter regime, characterized by swift energy transfer rates, the dynamics are influenced by decoherence time. To illustrate this, we study the exciton energy transfer dynamics between two closely positioned CdSe/CdS core/shell quantum dots with sizes and separations relevant to experimental conditions. Employing an atomistic approach, we calculate the excitonic level arrangement, exciton–phonon interactions, and transition dipole moments of the quantum dots within the microcavity. These parameters are then utilized to define a model Hamiltonian. Subsequently, we apply a generalized non-Markovian quantum Redfield equation to delineate the dynamics within the polaritonic framework.

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

Targeting Gut Bacteria Using Inulin‐Conjugated Mesoporous Silica Nanoparticles

Abstract To facilitate the creation of novel nanocarrier systems targeting the intestinal microbiome, inulin‐conjugated mesoporous silica nanoparticles (MSNs) are described herein for the first time. Surface functionalization is achieved on either hydrophilic or hydrophobic mesoporous nanoparticles using different conjugation methods. The targeting performance of the resulting materials is assessed and compared upon incubation with human stool. It appears that amide formation is the most favorable coupling method on hydrophilic MSNs to achieve the desired bioconjugate. Remarkably, high affinity of gut bacteria to the conjugated particles can be obtained, paving the way to novel targeted drug delivery systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A machine learning inversion scheme for determining interaction from scattering

Small angle scattering techniques have now been routinely used to quantitatively determine the potential of mean force in colloidal suspensions. However the numerical accuracy of data interpretation is often compounded by the approximations adopted by liquid state analytical theories. To circumvent this long standing issue, here we outline a machine learning strategy for determining the effective interaction in the condensed phases of matter using scattering. Via a case study of colloidal suspensions, we show that the effective potential can be probabilistically inferred from the scattering spectra without any restriction imposed by model assumptions. Comparisons to existing parametric approaches demonstrate the superior performance of this method in accuracy, efficiency, and applicability. This method can effectively enable quantification of interaction in highly correlated systems using scattering and diffraction experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Non-ideal stoichiometry and thermochemistry of aqueous iridium oxide nanoparticles in proton-coupled electron transfer and oxygen-atom transfer

Reported here are reactions of aqueous colloidal IrO x nanoparticles (NPs) with proton-coupled electron transfer (PCET) and oxygen-atom transfer (OAT) organic reagents, determining the reaction stoichiometries and thermochemistry. IrO x NPs have attracted much attention for their high electrocatalytic activity, but understanding of their fundamental reaction chemistry is limited. This IrO x NP model system is simple, with UV-vis titrations demonstrating reversible interconversion between predominantly Ir IV and predominantly Ir III NPs. This simplicity allows studies that reveal their complex non-idealities. The NP redox chemistry has a “super-Nernstian” stoichiometry of ∼1.3H + per 1e − transferred during both PCET and OAT reactions, as measured with electrochemistry and chemical methods. Spectroelectrochemistry revealed a broad distribution of surface IrO x –H bond dissociation free energies (BDFEs), becoming weaker as more H is added. Such variation in binding strengths—a non-ideal binding isotherm—is common for surface adsorbates. For IrO x , the variation of BDFE(IrO–H)s is fit well to a Frumkin isotherm with a width of 6.5 kcal mol −1 . For OAT from the reactive oxygen atoms of IrO x NPs, bracketing experiments gave 93 ± 24 kcal mol −1 for the average BDFE(O x Ir–O), with a predicted spread much larger than that for the BDFE(IrO–H). Taken together, the results show the importance of non-ideal stoichiometry and thermochemistry for IrO x NPs, and they open a path to more complete models to understand catalytic redox reactions at such surfaces.

Iridium Oxide Nanoparticles (NPs)↗