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At least 361 records · Page 20

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↗

Light Microsopy Module, International Space Station Premier Automated Microscope

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began science operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2015, if all goes as planned, five experiments will be completed: [1] Advanced Colloids Experiments with a manual sample base -3 (ACE-M-3), [2] the Advanced Colloids Experiment with a Heated Base -1 (ACE-H-1), [3] (ACE-H-2), [4] the Advanced Plant Experiment -03 (APEX-03), and [5] the Microchannel Diffusion Experiment (MDE). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] New York University: Paul Chaikin, Andrew Hollingsworth, and Stefano Sacanna, [2] University of Pennsylvania: Arjun Yodh and Matthew Gratale, [3] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al., [4] from the University of Florida and CASIS: Anna-Lisa Paul and Rob Ferl, and [5] from the Methodist Hospital Research Institute from CASIS: Alessandro Grattoni and Giancarlo Canavese.

Microscopy↗

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↗

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↗

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↗

SAMS Acceleration Measurements on MIR

During NASA Increment 3 (September 1996 to January 1997), about 5 gigabytes of acceleration data were collected by the Space Acceleration Measurement System (SAMS) onboard the Russian Space Station, Mir. The data were recorded on 11 optical disks and were returned to Earth on STS-81. During this time, SAMS data were collected in the Priroda module to support the following experiments: the Mir Structural Dynamics Experiment (MiSDE) and Binary Colloidal Alloy Tests (BCAT). This report points out some of the salient features of the microgravity environment to which these experiments were exposed. Also documented are mission events of interest such as the docked phase of STS-81 operations, a Progress engine burn, attitude control thruster operation, and crew exercise. Also included are a description of the Mir module orientations, and the panel notations within the modules. This report presents an overview of the SAMS acceleration measurements recorded by 10 Hz and 100 Hz sensor heads. Variations in the acceleration environment caused by unique activities such as crew exercise and life-support fans are presented. The analyses included herein complement those presented in previous mission summary reports published by the Principal Investigator Microgravity Services (PIMS) group.

Moskowitz, Milton E.↗

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↗

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↗

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↗

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↗

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↗

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↗

Evaluation of Thermal Control Coatings for Flexible Ceramic Thermal Protection Systems

This report summarizes the evaluation and testing of high emissivity protective coatings applied to flexible insulations for the Reusable Launch Vehicle technology program. Ceramic coatings were evaluated for their thermal properties, durability, and potential for reuse. One of the major goals was to determine the mechanism by which these coated blanket surfaces become brittle and try to modify the coatings to reduce or eliminate embrittlement. Coatings were prepared from colloidal silica with a small percentage of either SiC or SiB6 as the emissivity agent. These coatings are referred to as gray C-9 and protective ceramic coating (PCC), respectively. The colloidal solutions were either brushed or sprayed onto advanced flexible reusable surface insulation blankets. The blankets were instrumented with thermocouples and exposed to reentry heating conditions in the Ames Aeroheating Arc Jet Facility. Post-test samples were then characterized through impact testing, emissivity measurements, chemical analysis, and observation of changes in surface morphology. The results show that both coatings performed well in arc jet tests with backface temperatures slightly lower for the PCC coating than with gray C-9. Impact testing showed that the least extensive surface destruction was experienced on blankets with lower areal density coatings.

Kourtides, Demetrius↗

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↗

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↗

The fluid mechanics of continuous flow electrophoresis

The overall objective is to establish theoretically and confirm experimentally the ultimate capabilities of continuous flow electrophoresis chambers operating in an environment essentially free of particle sedimentation and buoyancy. The efforts are devoted to: (1) studying the effects of particle concentration on sample conductivity and dielectric constant. The dielectric constant and conductivity were identified as playing crucial roles in the behavior of the sample and on the resolving power and throughput of continuous flow devices; and (2) improving the extant mathematical models to predict flow fields and particle trajectories in continuous flow electrophoresis. A dielectric spectrometer was designed and built to measure the complex dielectric constant of a colloidal dispersion as a function of frequency between 500 Hz and 200 kHz. The real part of the signal can be related to the sample's conductivity and the imaginary part to its dielectric constant. Measurements of the dielectric constants of several different dispersions disclosed that the dielectric constants of dilute systems of the sort encountered in particle electrophoresis are much larger than would be expected based on the extant theory. Experiments were carried out to show that, in many cases, this behavior is due to the presence of a filamentary structure of small hairs on the particle surface. A technique for producing electrokinetically ideal synthetic latex particles by heat treating was developed. Given the ubiquitous nature of hairy surfaces with both cells and synthetic particles, it was deemed necessary to develop a theory to explain their behavior. A theory for electrophoretic mobility of hairy particles was developed. Finally, the extant computer programs for predicting the structure of electro-osmotically driven flows were extended to encompass flow channels with variable wall mobilities.

Saville, D. A.↗

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)↗

Electrochemical Synthesis of Monodisperse Platinum-Cobalt Nanocrystals

The synthesis of platinum-cobalt nanocrystals (NCs) using colloidal solvothermal techniques is well understood. However, for monodisperse NCs to form, high temperatures and environmentally detrimental solvents are needed. We report a room temperature, aqueous method of platinum-cobalt NC synthesis using electrochemical reduction as the driving force for nucleation and growth. It is found that colloidal NCs will form in both the presence and absence of surfactant. Additionally, we report a monodisperse electrochemical deposition of NCs utilising a transparent conducting oxide electrode. The methods developed here will allow for a synthetic method to produce nanocatalysts with minimal environmental impact and should be readily applicable to other NC systems, including single- and multi-component alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗