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At least 361 records · Page 20

Cocrystals combining order and correlated disorder via colloidal crystal engineering with DNA

Colloidal cocrystallization enables the formation of multicomponent materials with unique physicochemical properties, yet the role of nanoparticle (NP) shape and specific ligand interactions to cocrystallize anisotropic and isotropic NPs, with order and correlated disorder, remains underexplored. Here, geometry-inspired strategies along with programmable DNA interactions are combined to achieve structural control of colloidal cocrystal assemblies. Coassembling polyhedral and spherical NPs with complementary DNA yields two classes of cocrystals: one where both components order, and another where polyhedral NPs form a periodic lattice, while spherical NPs remain disordered but spatially correlated with polyhedral edges and corners. The size ratio of the building blocks can be used to control the ordering of spherical NPs—smaller octahedral-to-sphere size ratios favor fully ordered cocrystals. Molecular dynamics simulations further elucidate the role of NP shapes and dimensions in the structural outcome of the cocrystal. This work provides a framework for deliberately targeting and accessing crystals with exotic multicomponent structures.

Li, Yuanwei [Northwestern Univ., Evanston, IL (Uni↗

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

The CALPHAD approach for HEAs: Challenges and opportunities

Phases are key microstructural features that determine material properties. The most intuitive way of representing phase stability in a material is by its phase diagram. The vastness of the composition space is the most compelling reason for investigating high-entropy alloys (HEAs), but it also creates major challenges in controlling phases and microstructures of HEAs due to lack of experimental phase diagrams in highly concentrated multicomponent space. The CALPHAD (Calculation of Phase Diagram) approach, although it needs improvements, is the only viable way to calculate multicomponent phase diagrams. The two major property databases in CALPHAD, Gibbs energy and mobility, when coupled, can provide not only the equilibrium phase information, but also information about diffusion and kinetics. In this article, we will review the use of the CALPHAD approach in understanding phase stability and diffusion in high-entropy alloys. Finally, we will discuss the notable trend of coupling the high-throughput CALPHAD approach with machine learning in HEA design.

36 MATERIALS SCIENCE↗

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗

High Performance non-PGM Transition Metal Oxide ORR Catalysts of PEMFCs

This project was designed to develop acid-stable PGM-free transition metal oxide oxygen reduction reaction (ORR) electrocatalysts to meet or exceed the performance and durability of the DOE 2020 Technical Targets for platinum-group metal (PGM) free electrocatalysts from first-principles to incorporation into membrane-electrode assemblies (MEAs) for polymer electrolyte membrane (PEM) fuel cells. The planned project was to accomplish this goal with a multi-step approach: 1) materials modeling and experimental screening to identify acid-stable oxides with high ORR activity, 2) optimization of catalyst particle size and catalyst/carbon/ionomer catalyst layer composition, 3) fabrication of MEAs for performance and durability testing. During the course of this project: 1) acid-stability descriptors were developed for manganese oxides; 2) a family of acid-stable multicomponent oxides based on antimony were developed; 3) a flexible synthesis for the formation of nanocrystalline nonstoichiometric oxides was developed; 4) limited ORR activity but modest and improving oxygen evolution reaction (OER) activity was measured for multicomponent antimony oxides. The project was programmed into five technical tasks: The development of acid-stable ORR electrocatalytic oxides through 1) identification and optimization of acid-stable oxide compositions, and 2) electrochemical characterization; 3) optimization of catalyst layer composition for MEAs using identified ORR electrocatalysts; 4) MEA fabrication and performance testing to result in performance of 44 mA-cm-2 at 0.9 V vs. RHE; and 5) accelerated-stress testing of optimized MEAs. Because no acid-stable oxide was identified with the requisite activity for ORR (4.4 µA-cm-2oxide intrinsic activity at 0.9 V vs. RHE) within the time and budget allotted in Tasks 1 and 2, the project was halted at the end of phase 1, with no activity in Tasks 3-5. The research output, while not succeeding in developing ORR electrocatalysts, advanced the development of acid-stable oxide materials, showing potential for further improvement as OER electrocatalysts.

08 HYDROGEN↗

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FY24 Task 4: Studies of Phosphate and Fluoride Solubility for Dissolution of High Phosphate Tank Waste

Knowledge gaps have been identified in phosphate solubility in almost every single- and multi-component system, and particularly for aluminate in phosphate/hydroxide, where uncertainties in predicted values of aluminum solubility are greater than 50%. Solubility data of multicomponent, aqueous electrolytes containing sodium hydroxide, sodium fluoride, sodium phosphate, sodium nitrite, sodium nitrate, and dissolved gibbsite are also sparse. For example, for solutions of (i) sodium nitrate and sodium phosphate, data are only available at 30 and 50 °C, and for (ii) dissolved gibbsite in sodium hydroxide and sodium phosphate, only two data points are available at 20 and 40 °C. There is no data available on mixtures of sodium hydroxide, sodium phosphate, sodium fluoride, and dissolved gibbsite. These knowledge gaps were identified in a technical review of waste solubility data and the impact of dilution on solution stabilities and will be addressed in this work to predict aluminum hydroxide and sodium phosphate solubility in multicomponent electrolytes upon dilution, and upon variation of temperature. Results will provide the technical basis to develop accurate models for (i) gibbsite solubility and mass transfer of aluminum between solid and liquid forms following the sluicing of sludge and saltcake with water; and (ii) further blending of these suspensions with bismuth from bismuth phosphate waste, and zirconium and uranium left from the fuel decladding. This work will be essential to developing a disposition path for retrieval solutions from bismuth phosphate wastes. This effort would also support sludge washing to further reduce phosphate concentration if that process were to be added back to the flowsheet in the future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Effect of Polymer Removal on the Morphology and Phase of the Nanoparticles in All-Inorganic Heterostructures Synthesized via Two-Step Polymer Infiltration

Polymer templates play an essential role in the robust infiltration-based synthesis of functional multicomponent heterostructures with controlled structure, porosity, and composition. Such heterostructures are be used as hybrid organic–inorganic composites or as all-inorganic systems once the polymer templates are removed. Using iron oxide/alumina heterostructures formed by two-step infiltration of polystyrene-block-polyvinyl pyridine block copolymer with iron and aluminum precursors from the solution and vapor-phases, respectively, we show that the phase and morphology of iron oxide nanoparticles dramatically depend on the approach used to remove the polymer. We demonstrate that thermal and plasma oxidative treatments result in iron oxide nanoparticles with either solid or hollow morphologies, respectively, that lead to different magnetic properties of the resulting materials. Our study extends the boundaries of structure manipulations in multicomponent heterostructures synthesized using polymer infiltration synthesis, and hence their properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Flight contaminant trace analyser. Phase 1: Chromatographic input system

The development of a chromatographic column capable of resolving compounds associated with spacecraft atmospheres is presented. Consideration is given to sampling techniques, column parameters and operation, and column interface with a mass spectrometer. A capillary column coated with a mixture of polyalkylene glycols is found to provide the best selectivity for resolving multicomponent mixtures found in spacecraft atmospheres. Temperature programming and isothermal operation of the column are evaluated and it is found that temperature programming has a shorter analysis time for a given carrier gas flow rate and overall superior resolution. It is observed that hydrogen provides a 15% savings in analysis time over helium. Following the optimization of column operational parameters, a mixed phase Ucon capillary is prepared for evaluation during the column test period in which the test sample is automatically analyzed. Analysis of the multicomponent test mixture is completed within 45 minutes provided temperature programming is used. All but two of the test compounds are well resolved.

Source record↗

A similarity solution of the Navier-Stokes equations with wall catalysis and slip for hypersonic, low Reynolds number flow over spheres

The slip conditions for a multicomponent mixture with diffusion, wall-catalyzed atom recombination and thermal radiation are derived. The more realistic multicomponent species slip conditions are shown to be necessary for accurate merged shock layer solutions on a sphere. These slip conditions are used in a first-order similarity solution of the Navier-Stokes equations with nonequilibrium chemistry for the merged shock layer. Results of this quick numerical solution are compared with a time dependent solution around the sphere and with measured arc jet results at low Reynolds numbers. The similarity solution, unlike the time dependent solution, shows smooth radial profiles of the pressure and smooth variations of velocity slip, skin friction, temperature slip and heat transfer around the body. The present first-order similarity solution is valid up to 25 deg from the stagnation point and takes less than 1% of the computer time to run a time dependent scheme. The smaller stand-off distance obtained from the similarity solution is supported by experimental data. The measured heat flux is closer to the similarity solution than the time dependent method at the stagnation point and shows the proper variation with circumferential angle up to at least 40 deg.

Hendricks, W. L.↗

Ultrapure glass optical waveguide development in microgravity by the sol-gel process

Multicomponent, homogeneous, noncrystalline oxide gels can be prepared by the sol-gel process and these gels are promising starting materials for melting glasses in the space environment. The sol-gel process referred to here is based on the polymerization reaction of alkoxysilane with other metal alkoxy compounds or suitable metal salts. Many of the alkoxysilanes or other metal alkoxides are liquids and thus can be purified by distillation. The use of gels offers several advantages such as high purity and lower melting times and temperatures. The sol-gel process is studied for utilization in the preparation of multicomponent ultrapure glass batches for subsequent containerless melting of the batches in space to prepare glass blanks for optical waveguides.

Mukherjee, S. P.↗

Superalloy composition modeling

Development of a predictive method for determination of the gamma/gamma prime phase fields, i.e., gamma prime volume fraction as a function of the multicomponent composition, is described. The cluster variation method used for binary alloys in which the precipitated phase is coherent with the matrix phase is extended for application to the multicomponent coherent gamma/gamma prime nickel-based superalloys. It is shown that the cluster variation method can accurately describe the equilibrium (incoherent) gamma/gamma prime phase fields in the binary Ni-Al phase diagram. The gamma/gamma prime phase field for the Ni-Cr-Al ternary phase diagram is computed as a function of temperature. A reasonable fit results between the calculated and the experimental diagrams. The modeling of the six-component Ni-Cr-Al-Co-Mo-Ti base superalloy and the effect of Ni substitution of Co are discussed.

Barefoot, J.↗

Gels and gel-derived glasses in the Na2O-B2O3-SiO2 system

The containerless melting of high-purity multicomponent homogeneous gels and gel-monoliths offers a unique approach to making ultrapure multicomponent optical glasses in the reduced gravity environment of space. Procedures for preparing and characterizing gels and gel-derived glasses in the Na2O-B2O3-SiO2 system are described. Preparation is based on the polymerization reactions of alkoxysilane with trimethyl borate or boric acid and a suitable sodium compound. The chemistry of the gelling process is discussed in terms of process parameters and the gel compositions. The physicochemical nature of gels prepared by three different procedures were found to be significantly different. IR absorption spectra indicate finite differences in the molecular structures of the different gels. The melting of the gel powders and the transformation of porous gel-monoliths to transparent 'glass' without melting are described.

Mukherjee, S. P.↗

Gels and gel-derived glasses in the system Na2O-B2O3-SiO2

The containerless melting of high-purity multicomponent homogeneous gels and gel monoliths offers a unique approach to making ultrapure multicomponent optical glasses in the reduced gravity environment of space. Procedures for preparing and characterizing gels and gel-derived glasses in the system Na2O-B2O3-SiO2 are described. Preparation is based on the polymerization reactions of alkoxysilane with trimethyl borate or boric acid and a suitable sodium compound. The chemistry of the gelling process is discussed in terms of process parameters and the gel compositions. The physicochemical nature of gels prepared by three different procedures was found to be significantly different. Infrared absorption spectra indicate finite differences in the molecular structures of the different gels. The melting of the gel powders and the transformation of porous gel monoliths to transparent 'glass' without melting are described.

Mukherjee, S. P.↗

New eutectic alloys and their heats of transformation

Eutectic compositions and congruently melting intermetallic compounds in binary and multicomponent systems among common elements such as Al, Ca, Cu, Mg, P, Si, and Zn may be useful for high temperature heat storage. In this work, heats of fusion of new multicomponent eutectics and intermetallic phases are reported, some of which are competitive with molten salts in heat storage density at high temperatures. The method used to determine unknown eutectic compositions combined results of differential thermal analysis, metallography, and microprobe analysis. The method allows determination of eutectic compositions in no more than three steps. The heats of fusion of the alloys were measured using commercial calorimeters, a differential thermal analyzer, and a differential scanning calorimeter.

Farkas, D.↗

The C IV doublet ratio intensity effect in symbiotic stars

High-resolution UV spectra in the 1200-2000 wavelength range of the symbiotic variable R Aqr and its nebular jet were obtained in July 1987 with the IUE. The line profile structure of the C IV 1548, 1550 doublet in the jet indicates multicomponent velocity structure from an optically thin emitting gas. The C IV doublet profiles in the compact H II region engulfing the Mira and hot companion binary also suggest multicomponent structure with radial velocities up to about -100 km/s. The value of the doublet intensity ratio in the R Aqr H II region has been observed in other similar symbiotic stars, such as RX Pup. It is suggested that the anomalous behavior of the C IV doublet intensities may be useful for studying the spatial structure and temporal nature of winds in symbiotic stars.

Michalitsianos, A. G.↗

Response Of Ceramic Insulation To Aerothermodynamic Heating

Thermal conductivities determined from engineering model used to predict accurately thermal responses of multicomponent insulation on spacecraft. Types of insulation studied include such composite parts as alumina-enhanced thermal barrier backed by low-density fibrous refractory material. Internal responses of various types of multicomponent insulation to aerothermodynamic heating calculated with help of computer program that implements engineering model for thermal conductivity. Transfer of heat by internal radiation plays major role in responses of fibrous materials at high temperatures and incorporated into model and program. Used in future spacecraft and exposed during reentry and aerobraking maneuvers in outer atmosphere to environments even harsher than that of Space Shuttle.

Stewart, David A.↗

Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

Zoladz, T. F.↗