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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Pattern Language for High-Performance Computing Resilience

High-performance computing systems (HPC) provide powerful capabilities for modeling, simulation, and data analytics for a broad class of computational problems. They enable extreme performance of the order of quadrillion floating-point arithmetic calculations per second by aggregating the power of millions of compute, memory, networking and storage components. With the rapidly growing scale and complexity of HPC systems for achieving even greater performance, ensuring their reliable operation in the face of system degradations and failures is a critical challenge. System fault events often lead the scientific applications to produce incorrect results, or may even cause their untimely termination. The sheer number of components in modern extreme-scale HPC systems and the complex interactions and dependencies among the hardware and software components, the applications, and the physical environment makes the design of practical solutions that support fault resilience a complex undertaking. To manage this complexity, we developed a methodology for designing HPC resilience solutions using design patterns. We codified the well-known techniques for handling faults, errors and failures that have been devised, applied and improved upon over the past three decades in the form of design patterns. In this paper, we present a pattern language to enable a structured approach to the development of HPC resilience solutions. The pattern language reveals the relations among the resilience patterns and provides the means to explore alternative techniques for handling a specific fault model that may have different efficiency and complexity characteristics. Using the pattern language enables the design and implementation of comprehensive resilience solutions as a set of interconnected resilience patterns that can be instantiated across layers of the system stack.

Hukerikar, Saurabh↗
DOE OSTI2019

Impact of Catalyst Ink Dispersing Methodology on Fuel Cell Performance Using in-Situ X-ray Scattering

This work presents a study of the effects of ultrasonic dispersing methodology and time on catalyst agglomerate size in polymer electrolyte membrane fuel cell catalyst ink dispersions. Cathode catalyst inks were prepared and characterized to elucidate the influences of ultrasonic dispersing method and time on catalyst ink particle size and CCL electrochemical properties. In situ ultra-small-, small-, and wide-angle X-ray scattering analyses were used to study the impact of ultrasonication time and methodology on changes in the agglomerate, aggregate, and particle size and distribution during the dispersing process. Ex-situ transmission electron microscopy was also used to investigate the particle size of these inks. Fuel cell membrane electrode assemblies (MEAs) were prepared and tested to determine the influence of ink properties on CCL electrochemical properties, including the electrochemical active surface area, mass activity, H2/air polarization curves, and oxygen mass-transport resistances. It was found that a combination of brief tip sonication followed by bath sonication was most effective at breaking up agglomerates, leading to maximum catalyst activity and MEA performance. Extended tip sonication was found to be too aggressive and resulted in detachment of the platinum nanoparticles from the carbon black support, which decreased electrochemical surface area and MEA performance. Quantification of oxygen mass transport resistance showed that electrodes with large catalyst agglomerates due to insufficient sonication had a higher non-Fickian (pressure independent) than properly dispersed catalyst. Through correlation of the performance with catalyst particle size, the desired CCL structure was proposed, which will provide insight into dispersion strategies for lab-scale spray coating and other processing techniques, as well as for large-scale manufacturing.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Governing Constraints of Chromium(VI) Formation from Chromium(III)-Bearing Minerals in Soils and Sediments

The potential for geogenic Cr(VI) contamination is vast, yet it is difficult to predict susceptible environments as groundwater Cr(VI) concentrations vary significantly, even within a given aquifer, due to physical and hydrologic heterogeneity. The physical structure of soils and sediments exerts a dominant control on Cr(VI) production by dictating the separation distance of reactive phases, the diffusion distance from Cr(VI) generation sites to advecting groundwater, and by influencing infiltration rates and porewater velocity. Here, we used a dual-pore domain model to investigate the relative control of these parameters on Cr(VI) production. The reaction distance between Cr(III)-bearing minerals and Mn oxides predominantly controls Cr(VI) export to advecting groundwater, while changes in diffusion distance between sites of Cr(VI) generation and advective flow channels generally have little impact on steady-state Cr(VI) concentrations. Changes in Cr(VI) diffusion distance can, however, increase the time required for groundwater Cr(VI) concentrations to reach a steady-state; thus, under fluctuating hydrologic and biogeochemical conditions, long diffusion distances still have the potential to suppress Cr(VI) supply to advecting water. Furthermore, we show that high porewater flow velocities effectively dilute Cr(VI) diffusing from soil/sediment aggregates, thus minimizing Cr(VI) concentrations relative to lower porewater velocities. The strong control that the physical/hydrologic parameters exert on Cr(VI) production appears to overwhelm the impact of Cr(III)-mineral solubility within soils and sediments.

Hausladen, Debra (ORCID:0000000342356294)↗
DOE OSTI2023

Amorphous 1-D nanowires of calcium phosphate/pyrophosphate: A demonstration of oriented self-growth of amorphous minerals

Amorphous inorganic solids are traditionally isotropic, thus, it is believed that they only grow in a non-preferential way without the assistance of regulators, leading to the morphologies of nanospheres or irregular aggregates of nanoparticles. However, in the presence of (ortho)phosphate (Pi) and pyrophosphate ions (PPi) which have synergistic roles in biomineralization, the highly elongated amorphous nanowires (denoted ACPPNs) form in a regulator-free aqueous solution (without templates, additives, organics, etc). Based on thorough characterization and tracking of the formation process (e.g., Cryo-TEM, spherical aberration correction high resolution TEM, solid state NMR, high energy resolution monochromated STEM-EELS), the microstructure and its preferential growth behavior are elucidated. In ACPPNs, amorphous calcium orthophosphate and amorphous calcium pyrophosphate are distributed at separated but close sites. The ACPPNs grow via either the preferential attachment of ~2 nm nanoclusters in a 1-dimension way, or the transformation of bigger nanoparticles, indicating an inherent driving force-governed process. Here, we propose that the anisotropy of ACPPNs microstructure, which is corroborated experimentally, causes their oriented growth. This study proves that, unlike the conventional view, amorphous minerals can form via oriented growth without external regulation, demonstrating a novel insight into the structures and growth behaviors of amorphous minerals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.

Arumugam, Kamesh↗
DOE OSTI2026

Conserving asphalt resources: Rethinking rejuvenator performance evaluation through peptizing efficiency

Timely rejuvenation and restoration of asphalt are essential conservation practices that help preserve and extend the service life of roads, bridges, driveways, and parking lots. The performance of asphalt rejuvenators is often assessed based on their diffusion rates and softening power, yet these metrics alone fail to capture true rejuvenation potential. Here, this study integrates density functional theory (DFT) modeling with experimental analysis to show that rejuvenation effectiveness is primarily governed by molecular interactions with oxidized asphaltene nanoaggregates. DFT results revealed that amide- and unsaturated-chain compounds, such as hexadecanamide, oleic acid, and 9,17-octadecadienal, act cooperatively to disrupt π–π stacking and exfoliate asphaltene layers, reducing binding strength and enhancing dispersion. Unlike bulky, rigid molecules that remain trapped, these components remain mobile and repeatedly interact with multiple aggregation sites. Experimental validation using rheometry and FTIR confirmed that such molecularly compatible rejuvenators restore the binder flexibility and polydispersity, even when diffusion is relatively slow. Building on this mechanistic foundation, six rejuvenators (A2, A5, A7, A8, A9, and A10) were evaluated using a three-metric performance framework encompassing cracking resistance (Glover–Rowe parameter), UV stability, and surface hydrophobicity. Among the six rejuvenators evaluated, A9 exhibited the highest overall performance, reducing the Glover–Rowe cracking parameter by 85% (from 351 kPa to 53 kPa), demonstrating the greatest resistance to UV-induced aging with a stability index of 4.17 h·kPa⁻¹, and increasing surface hydrophobicity to a contact angle of 103.6°. Its superior performance is primarily attributed to its amide- and unsaturated-chain components, which act cooperatively to disrupt π–π stacking interactions and exfoliate asphaltene layers, thereby promoting molecular deagglomeration and enhancing long-term durability. These results shift the criteria for selecting rejuvenators: effective candidates must pair the electronic capability to unlock aged asphaltenes with sufficient structural stability to resist secondary aging and restore hydrophobicity. Restoring hydrophobicity is critical, as aging reduces the asphalt’s water repellency and increases water diffusion, which in turn accelerates moisture-related damage; consequently, a high-performing rejuvenator must effectively restore the binder’s hydrophobic characteristic. Collectively, these findings provide a framework for the rational design of next-generation of bio-based rejuvenators that enhance pavement longevity and promote long-term sustainability.

Aging↗
DOE OSTI2023

1,8-Dihydroxy Naphthalene—A New Building Block for the Self-Assembly with Boronic Acids and 4,4′-Bipyridine to Stable Host–Guest Complexes with Aromatic Hydrocarbons

The new Lewis acid–base adducts of general formula X(nad)B←NC5H4-C5H4N→B(nad)X [nad = 1,8-O2C10H6, X = C6H5 (2c), 3,4,5-F3-C6H2 (2d)] were synthesized in high yields via reactions of 1,8-dihydroxy naphthalene [nadH2] and 4,4′-bipyridine with the aryl boronic acids C6H5B(OH)2 and 3,4,5-F3-C6H2B(OH)2, respectively, and structurally characterized by multi-nuclear NMR spectroscopy and SCXRD. Self-assembled H-shaped Lewis acid–base adduct 2d proved to be effective in forming thermally stable host–guest complexes, 2d × solvent, with aromatic hydrocarbon solvents such as benzene, toluene, mesitylene, aniline, and m-, p-, and o-xylene. Crystallographic analysis of these solvent adducts revealed host–guest interactions to primarily occur via π···π contacts between the 4,4′-bipyridyl linker and the aromatic solvents, resulting in the formation of 1:1 and 1:2 host–guest complexes. Thermogravimetric analysis of the isolated complexes 2d × solvent revealed their high thermal stability with peak temperatures associated with the loss of solvent ranging from 122 to 147 °C. 2d, when self-assembled in an equimolar mixture of m-, p-, and o-xylene (1:1:1), preferentially binds to o-xylene. Collectively, these results demonstrate the ability of 1,8-dihydroxy naphthalene to serve as an effective building block in the selective self-assembly to supramolecular aggregates through dative covalent N→B bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Confinement of Iodine Molecules into Triple-Helical Chains within Robust Metal–Organic Frameworks

During nuclear waste disposal process, radioactive iodine as a fission product can be released. The widespread implementation of sustainable nuclear energy thus requires the development of efficient iodine stores that have simultaneously high capacity, stability and more importantly, storage density (and hence minimized system volume). Here, we report high I 2 adsorption in a series of robust porous metal–organic materials, MFM-300(M) (M = Al, Sc, Fe, In). MFM-300(Sc) exhibits fully reversible I 2 uptake of 1.54 g g –1 , and its structure remains completely unperturbed upon inclusion/removal of I 2 . Direct observation and quantification of the adsorption, binding domains and dynamics of guest I 2 molecules within these hosts have been achieved using XPS, TGA-MS, high resolution synchrotron X-ray diffraction, pair distribution function analysis, Raman, terahertz and neutron spectroscopy, coupled with density functional theory modeling. These complementary techniques reveal a comprehensive understanding of the host–I 2 and I 2 –I 2 binding interactions at a molecular level. The initial binding site of I 2 in MFM-300(Sc), I 2 I , is located near the bridging hydroxyl group of the [ScO 4 (OH) 2 ] moiety [I 2 I ···H–O = 2.263(9) Å] with an occupancy of 0.268. I 2 II is located interstitially between two phenyl rings of neighboring ligand molecules [I 2 II ···phenyl ring = 3.378(9) and 4.228(5) Å]. I 2 II is 4.565(2) Å from the hydroxyl group with an occupancy of 0.208. Significantly, at high I 2 loading an unprecedented self-aggregation of I 2 molecules into triple-helical chains within the confined nanovoids has been observed at crystallographic resolution, leading to a highly efficient packing of I 2 molecules with an exceptional I 2 storage density of 3.08 g cm –3 in MFM-300(Sc).

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

Quantum-enhanced photoprotection in neuroprotein architectures emerges from collective light-matter interactions

Background Superradiance is the phenomenon of many identical quantum systems absorbing and/or emitting photons collectively at a higher rate than any one system can individually. This phenomenon has been studied analytically in idealized distributions of electronic two-level systems (TLSs), each with a ground and excited state, as well as numerically in realistic photosynthetic nanotubes and cytoskeletal architectures. Methods Superradiant effects are studied here in idealized toy model systems and realistic biological mega-networks of tryptophan (Trp) molecules, which are strongly fluorescent amino acids found in many proteins. Each Trp molecule acts as a chromophore absorbing in the ultraviolet spectrum and can be treated approximately as a TLS, with its 1 L a excited singlet state; thus, organized Trp networks can exhibit superradiance. Such networks are found, for example, in microtubules, actin filaments, and amyloid fibrils. Microtubules and actin filaments are spiral-cylindrical protein polymers that play significant biological roles as primary constituents of the eukaryotic cytoskeleton, while amyloid fibrils have been targeted in a variety of neurodegenerative diseases. We treat these proteinaceous Trp networks as open quantum systems, using a non-Hermitian Hamiltonian to describe interactions of the chromophore network with the electromagnetic field. We numerically diagonalize the Hamiltonian to obtain its complex eigenvalues, where the real part is the energy and the imaginary part is its associated enhancement rate. We also consider multiple realizations of increasing static disorder in either the site energies or the decay rates. Results We obtained the energies and enhancement rates for realistic microtubules, actin filament bundles, and amyloid fibrils of differing lengths, and we use these values to calculate the quantum yield, which is the ratio of the number of photons emitted to the number of photons absorbed. We find that all three of these structures exhibit highly superradiant states near the low-energy portion of the spectrum, which enhances the magnitude and robustness of the quantum yield to static disorder and thermal noise. Conclusion The high quantum yield and stable superradiant states in these biological architectures may play a photoprotective rolein vivo, downconverting energetic ultraviolet photons—absorbed from those emitted by reactive free radical species—to longer, safer wavelengths and thereby mitigating biochemical stress and photophysical damage. Contrary to conventional assumptions that quantum effects cannot survive in large biosystems at high temperatures, our results suggest that macropolymeric collectives of TLSs in microtubules, actin filaments, and amyloid fibrils exhibit increasingly observable and robust effects with increasing length, up to the micron scale, due to quantum coherent interactions in the single-photon limit. Superradiant enhancement and high quantum yield exhibited in neuroprotein polymers could thus play a crucial role in information processing in the brain, the development of neurodegenerative diseases such as Alzheimer’s and related dementias, and a wide array of other pathologies characterized by anomalous protein aggregates.

Physics↗
DOE OSTI2017

Modelling the evolution of complex conductivity during calcite precipitation on glass beads

When pH and alkalinity increase, calcite frequently precipitates and hence modifies the petrophysical properties of porous media. The complex conductivity method can be used to directly monitor calcite precipitation in porous media because it is sensitive to the evolution of the mineralogy, pore structure and its connectivity. Here, we have developed a mechanistic grain polarization model considering the electrochemical polarization of the Stern and diffuse layers surrounding calcite particles. Our complex conductivity model depends on the surface charge density of the Stern layer and on the electrical potential at the onset of the diffuse layer, which are computed using a basic Stern model of the calcite/water interface. The complex conductivity measurements of Wu et al. on a column packed with glass beads where calcite precipitation occurs are reproduced by our surface complexation and complex conductivity models. The evolution of the size and shape of calcite particles during the calcite precipitation experiment is estimated by our complex conductivity model. At the early stage of the calcite precipitation experiment, modelled particles sizes increase and calcite particles flatten with time because calcite crystals nucleate at the surface of glass beads and grow into larger calcite grains. Finally, at the later stage of the calcite precipitation experiment, modelled sizes and cementation exponents of calcite particles decrease with time because large calcite grains aggregate over multiple glass beads and only small calcite crystals polarize.

58 GEOSCIENCES↗
DOE OSTI2016

Self-assembly of pi-conjugated peptides in aqueous environments leading to energy-transporting bioelectronic nanostructures

The realization of new supramolecular pi-conjugated organic structures inspired and driven by peptide-based self-assembly will offer a new approach to interface with the biotic environment in a way that will help to meet many DOE-recognized grand challenges. Previously, we developed pi-conjugated peptides that undergo supramolecular self-assembly into one-dimensional (1-D) organic electronic nanomaterials under benign aqueous conditions. The intermolecular interactions among the pi-conjugated organic segments within these nanomaterials lead to defined perturbations of their optoelectronic properties and yield nanoscale conduits that support energy transport within individual nanostructures and throughout bulk macroscopic collections of nanomaterials. Our objectives for future research are to construct and study biomimetic electronic materials for energy-related technology optimized for harsher non-biological environments where peptide-driven self-assembly enhances pi-stacking within nanostructured biomaterials, as detailed in the following specific tasks: (1) synthesis and detailed optoelectronic characterization of new pi-electron units to embed within homogeneous self assembling peptides, (2) molecular and data-driven modeling of the nanomaterial aggregates and their higher-order assemblies, and (3) development of new hierarchical assembly paradigms to organize multiple electronic subunits within the nanomaterials leading to heterogeneous electronic properties (i.e. gradients and localized electric fields). These intertwined research tasks will lead to the continued development and fundamental mechanistic understanding of a powerful bioinspired materials set capable of making connections between nanoscale electronic materials and macroscopic bulk interfaces, be they those of a cell, a protein or a device.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Investigation of zinc recovery by hydrogen reduction assisted pyrolysis of alkaline and zinc-carbon battery waste

Highlights: • Recycling of alkaline and zinc-carbon battery waste by pyrolysis. • Thermodynamic investigation for hydrogen reduction of alkaline battery waste. • Recovery of Zn as submicron particle from alkaline battery waste. • Production of manganese oxide particles from alkaline battery waste. • Controlling oxidation state of manganese oxide product in the process. - Abstract: Zinc (Zn) recovery from alkaline and zinc-carbon (Zn-C) battery waste were studied by a laboratory scale pyrolysis process at a reaction temperature of 950 °C for 15–60 min residence time using 5%H{sub 2(g)}-N{sub 2(g)} mixture at 1.0 L/min gas flow rate. The effect of different cooling rates on the properties of pyrolysis residue, manganese oxide particles, were also investigated. Morphological and structural characterization of the produced Zn particles were performed. The battery black mass was characterized with respect to the properties and chemical composition of the waste battery particles. The thermodynamics of the pyrolysis process was studied using the HSC Chemistry 5.11 software. A hydrogen reduction reaction of the battery black mass (washed with Milli-Q water) takes place at the chosen temperature and makes it possible to produce fine Zn particles by rapid condensation following the evaporation of Zn from the pyrolysis batch. The amount of Zn that can be separated from the black mass increases by extending the residence time. Recovery of 99.8% of the Zn was achieved at 950 °C for 60 min residence time using 1.0 L/min gas flow rate. The pyrolysis residue contains MnO and Mn{sub 2}O{sub 3} compounds, and the oxidation state of manganese can be controlled by cooling rate and atmosphere. The Zn particles exhibit spherical and hexagonal particle morphology with a particle size varying between 200 nm and 3 µm. However the particles were formed by aggregation of nanoparticles which are primarily nucleated from the gas phase.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Apparent Disk-mass Reduction and Planetisimal Formation in GravitationallyUnstable Disks in Class 0/I Young Stellar Objects

We investigate the dust structure of gravitationally unstable disks undergoing mass accretion from the envelope, envisioning its application to Class 0/I young stellar objects (YSOs). We find that the dust disk quickly settles into a steady state and that, compared to a disk with interstellar medium (ISM) dust-to-gas mass ratio and micron-sized dust, the dust mass in the steady state decreases by a factor of 1/2 to 1/3, and the dust thermal emission decreases by a factor of 1/3 to 1/5. The latter decrease is caused by dust depletion and opacity decrease owing to dust growth. Our results suggest that the masses of gravitationally unstable disks in Class 0/I YSOs are underestimated by a factor of 1/3 to 1/5 when calculated from the dust thermal emission assuming an ISM dust-to-gas mass ratio and micron-sized dust opacity, and that a larger fraction of disks in Class 0/I YSOs is gravitationally unstable than was previously believed. We also investigate the orbital radius r{sub P} within which planetesimals form via coagulation of porous dust aggregates and show that r{sub P} becomes ∼20 au for a gravitationally unstable disk around a solar mass star. Because r{sub P} increases as the gas surface density increases and a gravitationally unstable disk has maximum gas surface density, r{sub P}∼20 au is the theoretical maximum radius for planetesimal formation. We suggest that planetesimal formation in the Class 0/I phase is preferable to that in the Class II phase because a large amount of dust is supplied by envelope-to-disk accretion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Carbon nanodot precursors enable ultrahigh-loading copper single-atom catalysts for oxygen reduction reaction

Single-atom catalysts (SACs) have attracted significant attention in electrocatalysis due to their high metal utilization and tunable electronic structures; however, their practical implementation is often limited by poor atomic dispersion, low metal loadings (typically < 1 wt%), and insufficient anchoring of single metal atoms on catalyst supports. Herein, we report a simple and versatile strategy to synthesize copper single-atom catalysts (Cu-SACs) with ultrahigh metal loading using citric-acid-derived carbon nanodots as metal-capturing precursors. Through hydrothermal treatment followed by pyrolysis in the presence of urea, atomically dispersed copper atoms coordinated with nitrogen are incorporated into a carbon framework, achieving a Cu loading of up to 20 wt% while maintaining atomic dispersion. Notably, a significant fraction of the copper single atoms exists as Cu+–N2 coordination, which provides under-coordinated and catalytically active sites. The resulting Cu-SAC exhibits promising oxygen reduction reaction (ORR) activity in alkaline media, delivering a limiting current density comparable to that of commercial 20 wt% Pt/C with a predominant four-electron reduction pathway. Despite this high intrinsic activity, durability tests reveal gradual performance degradation under prolonged electrochemical operation, which is attributed to demetallation and aggregation of copper single atoms into metallic nanoparticles. These results demonstrate the potential of carbon nanodot-based platforms for synthesizing high-loading SACs, while underscoring the critical need to simultaneously control carbon porosity and metal–nitrogen coordination to enhance active-site accessibility and durability.

Sharma, Prakhar [University of Kentucky]↗
DOE OSTI2025

Mesoscale fractal whey protein particles derived from microscale linear-shaped protein assemblies (Part 1): Manufacturing method and particle characteristics

Whey protein isolates (WPI) are widely used in processed foods for their versatile functional properties. Modifying the structural properties of proteins by assembling them into mesoscale or microscale particles may improve their functionality and broaden their applications. This study aims to manufacture and characterize mesoscale whey protein particles (WPP) derived from WPI. Two types of WPP, WPP1 (0.05 mL/min) and WPP2 (0.25 mL/min), were prepared through a multistep approach involving liquid antisolvent (LAS) precipitation, heat treatment, and microfluidization. Liquid antisolvent precipitation was performed by injecting a 20% (wt/vol) WPI dispersion (pH 7) into an ethanol-glycerol mixture (75:25, vol/vol) under laminar flow, followed by heat treatment at 80°C for 20 min as a particle hardening step. This process produced stable fiber- and ribbon-shaped whey protein assemblies (WPA), which served as precursors to WPP. Subsequent microfluidization (150 MPa, 6 passages) reduced the size of WPA, yielding mesoscale WPP with irregular morphologies and a more uniform size distribution, as revealed by microscopy and dynamic light scattering. ζ-Potential and fluorescence labeling indicated higher surface charge and surface hydrophobicity of WPP compared with untreated WPI. The WPP showed internal mass fractal and surface fractal structures at larger length scales, analyzed using small-angle X-ray scattering. Fourier transform infrared spectroscopy demonstrated an increased fraction of intermolecular β-sheets in WPP, suggesting that hydrogen bonding contributed to their formation. Gel electrophoresis confirmed that disulfide bonds served as the primary cross-links stabilizing the WPP structure. Furthermore, turbidity measurements showed that WPP exhibited superior colloidal phase stability compared with untreated WPI and maintained high colloidal stability under both acidic and neutral pH conditions.

Antisolvent precipitation↗
DOE OSTI2023

Effects of diffusion barriers on reaction wave stability in Co/Al reactive multilayers

Bimetallic, reactive multilayers are uniformly structured materials composed of alternating sputter-deposited layers that may be ignited to produce self-propagating mixing and formation reactions. These nanolaminates are most commonly used as rapid-release heat sources. The specific chemical composition at each metal/metal interface determines the rate of mass transport in a mixing and formation reaction. The inclusion of engineered diffusion barriers at each interface will not only inhibit solid-state mixing but also may impede the self-propagating reactions by introducing instabilities to wavefront morphology. Here, this work examines the effect of adding diffusion barriers on the propagation of reaction waves in Co/Al multilayers. The Co/Al system has been shown to exhibit a reaction propagation instability that is dependent on the bilayer thickness, which allows for the occurrence of unstable modes in otherwise stable designs from the inclusion of diffusion barriers. Based on the known stability criteria in the Co/Al multilayer system, the way in which the inclusion of diffusion barriers changes a multilayer's heat of reaction, thermal conductivity, and material mixing mechanisms can be determined. These factors, in aggregate, lead to changes in the wavefront velocity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Observed Enhancement of Reflectivity and Electric Field in Long-Lived Florida Anvils

A study of two long-lived Florida anvils showed that reflectivity >20 dBZ increased in area, thickness and sometimes magnitude at mid-level well downstream of the convective cores. In these same regions electric fields maintained strengths >10 kV m1 for many tens of minutes and became quite uniform over tens of kilometers. Millimetric aggregates persisted at 9 to 10 km for extended times and distances. Aggregation of ice particles enhanced by strong electric fields might have contributed to reflectivity growth in the early anvil, but is unlikely to explain observations further out in the anvil. The enhanced reflectivity and existence of small, medium and large ice particles far out into the anvil suggest that an updraft was acting, perhaps in weak convective cells formed by instability generated from the evaporation and melting of falling ice particles. We conclude that charge separation must have occurred in these anvils, perhaps at the melting level but also at higher altitudes, in order to maintain fields >10 kV m 1 at 9 to 10 km for extended periods of time over large distances. We speculate that charge separation occurred as a result of ice-ice particle collisions (without supercooled water being present) via either a non-inductive or perhaps even an inductive mechanism, given the observed broad ice particle spectra, the strong pre-existing electric fields and the many tens of minutes available for particle interactions. The observations, particularly in the early anvil, show that the charge structure in these anvils was quite complex.

Dye, James E.↗