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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A solid-state extrusion pathway extensible to upcycling aluminum scrap and end-of-life permanent magnets into ductile Al-6061/SmCo 5 structural magnetic composites

Permanent magnets offer strong potential for multifunctional structural components, but their inherent brittleness limits direct integration. Here, SolidStir® Extrusion (SSE) is used to embed SmCo5 powder into AA6061 in the solid state, and the resulting microstructure, interfacial chemistry, mechanical properties, and magnetic response are systematically characterized. SSE fragments the initial SmCo 5 powder into predominantly fine particles dispersed within an ultrafine Al matrix, with a volume fraction of ∼ 4–6 % in this proof-of-concept study. Interfacial reactions form a continuous Al–Co reaction layer, with local atomic-resolution indexing consistent with Al 13 Co 4 , together with Sm–Si-rich reaction products, while the matrix contains Sm–Co–Si-rich precipitates and Mg 2 Si, producing features from nanometers to micrometers. Compared with an Al extrudate, this architecture increases yield strength by ∼ 42 % and tensile strength by ∼ 31 %, while preserving uniform elongation, and it sustains work hardening in compression from 150 to 400 °C. The composite retained hard-magnetic behavior, with axial magnetization of 12.7 A·m 2 kg −1 at 6 T and intrinsic coercivity of 9.6 kOe. These findings demonstrate that SSE can produce Al-based load-bearing magnetic composites while preserving useful SmCo5 functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lie–Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries

An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and the Hamiltonian. Hamiltonian systems with symmetries, whose paradigm examples are the Lie–Poisson systems, have been shown to describe a broad category of physical phenomena, from satellite motion to underwater vehicles, fluids, geophysical applications, complex fluids, and plasma physics. The Poisson bracket in these systems comes from the symmetries, while the Hamiltonian comes from the underlying physics. We view the symmetry of the system as primary, hence the Lie–Poisson bracket is known exactly, whereas the Hamiltonian is regarded as coming from physics and is considered not known, or known approximately. Using this approach, we develop a network based on transformations that exactly preserve the Poisson bracket and the special functions of the Lie–Poisson systems (Casimirs) to machine precision. We present two flavors of such systems: one, where the parameters of transformations are computed from data using a dense neural network (LPNets), and another, where the composition of transformations is used as building blocks (G-LPNets). We also show how to adapt these methods to a larger class of Poisson brackets. We apply the resulting methods to several examples, such as rigid body (satellite) motion, underwater vehicles, a particle in a magnetic field, and others. The methods developed in this paper are important for the construction of accurate data-based methods for simulating the long-term dynamics of physical systems.

Data-based modeling↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
DOE OSTI2023

Commissioning results of the BNL Alternating Gradient Synchrotron booster AC dipole

Here, an AC dipole has been installed in the AGS booster as part of polarized beam developments for the future Electron Ion Collider (EIC). This will allow preserving helion beam polarization through two intrinsic resonances during acceleration to an energy corresponding to |$Gγ$| = 10.5. AC dipoles can preserve polarization by forcing the beam to undergo large amplitude vertical betatron oscillations. These coherent oscillations cause all particles to sample the strong horizontal fields of quadrupoles, and result in a full spin flip. In preparation for the AC dipole being used for polarized helions, it was first commissioned with polarized protons. The proton extraction energy was raised to allow protons to cross $Gγ$ = 0 + $v_y$ = 4.8087. As an artifact of the experiment using polarized protons, the booster settings for bunch extraction interfered with the coherent oscillations and limited the maximum coherent amplitude. This interference will be well separated in the case of polarized helions. Polarized protons crossed the $Gγ$ = 0 + $v_y$ intrinsic resonance with a full spin flip through use of the AC dipole. Simulations of the resonance crossing using Zgoubi accurately predict the polarization relative to the coherent amplitude.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A late glacial paleoenvironmental and climate record from the Sierra de Juarez, Baja California

Ciénegas are desert wetlands that are strongly correlated with the stability of the hydrologic cycle in arid landscapes. However, these environments are particularly vulnerable to climate change, drought, water diversion, and fire suppression which all have contributed to the degradation of ciénegas along the U.S.-Mexican borderlands. Therefore, identifying the timing of precipitation patterns in this region is of particular interest because of its relationship to many ecological responses of the landscape such as groundwater recharge and fire. Here, we present the first-ever fire paleoenvironmental record from Ciénega Chimeneas, a ciénega complex in the Sierra de Juárez of Baja California. We explore how changes in the amount and seasonality of moisture affected ciénega complexes and fire activity from across the southwestern North American region over the past 45,000 years. Further, our record suggests that during the late glacial period, 41,000–21,000 cal yr BP, the increase of Larrea and Quercus indicate an increase in summer precipitation. Subsequently, when summer precipitation increased, pollen preservation and pollen accumulation rates (PAR) also increased. Increased vegetation allowed for increased fire activity during the late glacial period. Regionally, most of the comparison sites also indicated wet conditions during the full glacial period. However, around 21,000 cal yr BP, effective moisture decreased resulting in a dramatic change in the vegetation assemblage. Specifically, the summer wet taxa disappeared, while pollen preservation and PAR decreased, suggesting a dry period until ~14,000 cal yr BP. Little fire activity is recorded after 21,000 cal yr BP, likely due to the absence of fuels. At ~14,000 cal yr BP, Larrea and Quercus reappear suggesting increased summer precipitation. However, the appearance of Cyperaceae and increases in grasses suggest increased winter precipitation. We suggest that the combination of summer wet and winterwet taxa ~14,000 cal yr BP represents an increase in ENSO conditions, while the summer moisture controls remained relatively constant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Satellite remote sensing for environmental sustainable development goals: A review of applications for terrestrial and marine protected areas

With few years left to achieve the vital United Nations Sustainable Development Goals (SDGs), member nations must urgently leverage technological advancements in environmental monitoring to succeed. Remote sensing now provides decades of global observations at a variety of spatio-temporal scales and a litany of data products to guide comprehensive measures for climate action, and aquatic and terrestrial biota preservation. Protected areas, such as national parks and wildlife preserves, represent largely untapped resources for both applying robust conservation measures and testing ambitious new approaches to sustainable development that could jumpstart the much-needed adoption of strategies to efficiently pursue global sustainability. This review summarizes recent demonstrated utilities of remotely sensed data applied to protected areas for research related to SDG goals 13, 14, and 15: “Climate Action”, “Life below Water”, and “Life on Land”. We identify successful uses of such data for each SDG, identify areas for improvement, and provide recommendations from the literature on how to expand what others have done to achieve lofty goals with global impact. We demonstrate that remote sensing provides a valuable tool for achieving SDGs as it facilitates monitoring vegetation health, water quality and condition, and climate variables at large spatial and fine temporal scales, while also evaluating the effectiveness of management and conservation practices. Issues remain, however, in that there is currently no reference from which to relate goal progress to human livelihoods. Further, the current relationship between remotely sensed indices and ecological services that determine sustainable development omit steps that would establish this connection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Green solvent-processable poly(3-hexylthiophene) derivative maintains high hole mobility in diodes

The development of environmentally sustainable fabrication methods for organic solar cells (OSCs) is critical to enable their large-scale adoption. Conventional solution-processed OSCs often rely on halogenated, toxic solvents that pose health and environmental risks, limiting their scalability. This is because π-conjugated polymers tend to have a low solubility in non-halogenated solvents. A common strategy to enhance solubility in alternative solvents is through the incorporation of polar solubilizing groups, often on every repeat unit of at least one monomer. However, too many polar side chains tend to disrupt favorable morphology and decrease charge transport properties. In this study, we demonstrate that a minimal degree of side chain functionalization can improve green solvent processability while preserving electrical performance. We tested this hypothesis using our previously reported random copolymer derivative of poly(3-hexylthiophene) (P3HT) where ∼10 mol% of the side chains are 6-pentanoatehexyl side chains. We find that this low-level functionalization significantly broadens the solvents that can be used to process P3HT to less toxic solvents such as o-xylene and anisole. Furthermore, the copolymer processed from greener solvents showed high hole mobilities (∼10⁻ 3 cm 2 /Vs by the Space-Charge Limiting Current method in diodes), comparable to P3HT films cast from toxic chloroform. These findings suggest that minimal side-chain modification is a viable strategy for expanding green solvent compatibility while preserving electrical performance, paving the way toward more sustainable organic semiconductor designs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

How volatile isoprenoids improve plant thermotolerance

Volatile isoprenoids mainly include isoprene and monoterpenes, which improve the thermotolerance of the emitting plant by lowering reactive oxygen species (ROS) levels, preserving chloroplast membrane ultrastructure, maintaining photosynthesis and primary metabolism, inducing heat shock proteins, and preserving growth and development. Recent data showed that isoprenoids can act as signaling molecules to improve plant thermotolerance by altering related gene expression through Ca 2+ -mediated signaling pathways. Here, to promote further understanding of isoprenoid-mediated thermotolerance mechanisms, we review current understanding of isoprenoid-induced plant thermotolerance, along with new findings describing the corresponding underlying mechanisms and putative signaling pathways. This information is beneficial for the potential utilization of isoprenoids for enhancing crop tolerance to global warming either by enhancing the emission of isoprenoids or by using isoprenoid-inspired anti-high temperature agents.

Ca2+ signal↗
DOE OSTI2022

Improved accuracy in degenerate variational integrators for guiding centre and magnetic field line flow

First-order-accurate degenerate variational integration (DVI) was introduced in Ellison et al. ( Phys. Plasmas , vol. 25, 2018, 052502) for systems with a degenerate Lagrangian, i.e. one in which the velocity-space Hessian is singular. In this paper we introduce second-order-accurate DVI schemes, both with and without non-uniform time stepping. We show that it is not in general possible to construct a second-order scheme with a preserved two-form by composing a first-order scheme with its adjoint, and discuss the conditions under which such a composition is possible. We build two classes of second-order-accurate DVI schemes. We test these second-order schemes numerically on two systems having non-canonical variables, namely the magnetic field line and guiding centre systems. Variational integration for Hamiltonian systems with non-uniform time steps, in terms of an extended phase space Hamiltonian, is generalized to non-canonical variables. It is shown that preservation of proper degeneracy leads to single-step (one-step) methods without parasitic modes, i.e. to non-uniform time step DVIs. This extension applies to second-order-accurate as well as first-order schemes, and can be applied to adapt the time stepping to an error estimate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Root carbon interation with soil minerals is dynamic, leaving a legacy of microbially derived residues

Minerals preserve the oldest most persistent soil carbon, and mineral characteristics appear to play a critical role in the formation of soil organic matter (SOM) associations. To test the hypothesis that carbon source and soil microorganisms also influence mineral-SOM associations, we incubated permeable minerals bags in soil microcosms with and without plants, in a 13CO2 labelling chamber. Mineral bags contained quartz, ferrihydrite, kaolinite, or native soil minerals isolated via density separation. Using 13C-NMR, FTICR-MS, and lipidomics, we traced plant-derived carbon onto minerals harvested from microcosms at three plant growth stages, characterizing total carbon, 13C enrichment, and SOM chemistry. While C accumulation was rapid and mineral-dependent, the accumulated amount was not significantly affected by the presence of plant roots. However, the rhizosphere did shape the chemistry of mineral-associated SOM. Minerals incubated in the rhizosphere were associated with a more diverse array of compounds with different C functional groups (carbonyl, aromatics, carbohydrates, lipids) than minerals incubated in a bulk soil control. These diverse rhizosphere-derived compounds may represent a “transient fraction” of mineral SOM, rapidly exchanging with mineral surfaces. Our results also suggest that many of the lipids which persist on minerals are microbially-derived with a large fraction of fungal lipids.

Rhizosphere, soil organic matter, grassland, 13C-N↗
DOE OSTI2021

3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds

The prerequisite of therapeutic drug design is to identify novel molecules with desired biophysical and biochemical properties. Deep generative models have demonstrated their ability to find such molecules by exploring a huge chemical space efficiently. An effective way to obtain molecules with desired target properties is the preservation of critical scaffolds in the generation process. To this end, we propose a domain aware generative framework called 3D-Scaffold that takes 3D coordinates of a desired scaffold as an input and generates 3D coordinates of novel therapeutic candidates as an output while always preserving the desired scaffolds in generated structures. We show that our framework generates predominantly valid, unique, novel, and experimentally synthesizable molecules that have drug-like properties similar to the molecules in the training set. Using domain specific datasets, we generate covalent and non-covalent antiviral inhibitors. Therefore, to measure the success of our framework in generating therapeutic candidates, generated structures were subjected to high throughput virtual screening via docking simulations, which shows favorable interaction against SARS-CoV-2 main protease and non-structural protein endoribonuclease (NSP15) targets. Most importantly, our model performs well with relatively small volumes of training data and generalizes to new scaffolds, making it applicable to other domain.

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

Adsorption and Catalytic Activity of Gold Nanoparticles in Mesoporous Silica: Effect of Pore Size and Dispersion Salinity

The assembled state of nanoparticles (NPs) within porous matrices plays a governing role in directing their biological, electronic, and catalytic properties. However, the effects of the spatial confinement and environmental factors, such as salinity, on the NP assemblies within the pores are poorly understood. In this study, we use adsorption isotherms, spectrophotometry, and small-angle neutron scattering to develop a better understanding of the effect of spatial confinement on the assembled state and catalytic performance of gold (Au) NPs in propylamine-functionalized SBA-15 and MCM-41 mesoporous silica materials (mSiO 2 ). We carry out a detailed investigation of the effect of pore diameter and ionic strength on the packing and spatial distribution of AuNPs within mSiO 2 to get a comprehensive insight into the structure, functioning, and activity of these NPs. We demonstrate the ability of the adsorbed AuNPs to withstand aggregation under high salinity conditions. We attribute the observed preservation of the adsorbed state of AuNPs to the strong electrostatic attraction between oppositely charged pore walls and AuNPs. The preservation of the structure allows the AuNPs to retain their catalytic activity for a model reaction in high salinity aqueous solution, here, the reduction of p-nitrophenol to p-aminophenol, which otherwise is significantly diminished due to bulk aggregation of the AuNPs. This fundamental study demonstrates the critical role of confinement and dispersion salinity on the adsorption and catalytic performance of NPs.

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

Ionic Liquid Gating of SrTiO 3 Lamellas Fabricated with a Focused Ion Beam

Here, in this work, we combine two previously incompatible techniques for defining electronic devices: shaping three-dimensional crystals by focused ion beam (FIB), and two-dimensional electrostatic accumulation of charge carriers. The principal challenge for this integration is nanometer-scale surface damage inherent to any FIB-based fabrication. We address this by using a sacrificial protective layer to preserve a selected pristine surface. The test case presented here is accumulation of 2D carriers by ionic liquid gating at the surface of a micron-scale SrTiO 3 lamella. Preservation of surface quality is reflected in superconductivity of the accumulated carriers. This technique opens new avenues for realizing electrostatic charge tuning in materials that are not available as large or exfoliatable single crystals, and for patterning the geometry of the accumulated carriers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Magnetic La 0.7 Sr 0.3 MnO 3 Membranes Synthesized by Etching a Sr 3 Al 2 O 6 Sacrificial Layer Using an Intermediary Manganite Protection Layer

The integration of perovskite oxides onto flexible substrates has witnessed significant advancements owing to the development of an epitaxial lift-off technique utilizing a Sr 3 Al 2 O 6 sacrificial layer. However, Sr 3 Al 2 O 6 is susceptible to instability in both air and high-temperature oxygen atmospheres, potentially leading to degradation during the growth of the functional oxide layer. In this study, we investigate the use of an oxygen-deficient La 0.7 Sr 0.3 MnO 3 as capping layer, and demonstrate its ability to stabilize Sr 3 Al 2 O 6 films in ambient air. We successfully synthesized freestanding La 0.7 Sr 0.3 MnO 3 membranes by etching this sacrificial layer and transferring them onto flexible polymer substrates. Importantly, the magnetic properties of the La 0.7 Sr 0.3 MnO 3 films are preserved in these membranes. Furthermore, our results underline that employing a thin manganite capping layer ensures both high structural quality and the preservation of functional properties in the resulting membranes.

Deposition↗
DOE OSTI2026

Calcium Gradient-Doped LiNi 0.5 Mn 1.5 O 4 Cathode for Long Cycle Life Lithium-Ion Batteries

High-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) has attracted considerable attention as a cathode material for next-generation lithium-ion batteries due to its high operating voltage and intrinsically fast lithium-ion diffusion kinetics. However, the practical implementation of LNMO remains limited by its rapid capacity decay, primarily associated with bulk structural instability and parasitic interfacial reactions. To address these issues, we innovatively introduced calcium (Ca) as a dopant to enhance both the oxygen framework and surface stabilities of the LNMO crystal through gradient doping. Observations from the electronic microscopies, X-ray diffraction, and the elemental analysis confirmed that Ca is preferentially enriched at the particle surface, and a disordered crystal phase is preserved in the bulk in the gradient-doped LNMO cathodes. As cathodes in LIBs, the Ca gradient-doped (Ca gr) LNMO materials delivered formation capacities of ∼126−130 mAh/g and exhibited Coulombic efficiencies of 88−95%, which are consistently higher than those of the uniform-doped samples at the same doping level and undoped sample. Especially, the Ca gr 0.05 LNMO cathode demonstrated significantly improved rate capability with ∼113 mAh/g preserved at 10 C, while ∼92 mAh/g and ∼110 mAh/g for undoped and Ca uniform 0.05 LNMO, respectively, and excellent cycling stability, retaining ∼124.1 mAh/g (∼96.3% capacity retention) after 500 cycles. The analysis of cyclic voltammetry, differential capacity, and electrochemical impedance revealed that the excellent electrochemical performance is attributed to the structural and morphological advantages of gradient-doped LNMO cathodes with a disordered bulk structure for fast Li + diffusion and a Ca-enriched surface for minimizing the Mn dissolution.

25 ENERGY STORAGE↗
DOE OSTI2025

Rapid Solidification Effects in Additively Manufactured Si and SiGe Compositions

SiGe alloys have a proven track record as robust high-temperature thermoelectric materials, powering NASA missions like SNAP-10A, LES-9, and Voyager 1 and 2. Enhancing thermoelectric efficiency hinges on minimizing thermal conductivity while preserving electrical conductivity. Rapid solidification via LPBF can generate microstructural features such as subgrain cellular boundaries and twinning, which may help reduce thermal conductivity while preserving semiconducting behavior. Here, this study investigates the potential of laser powder bed fusion (LPBF) additive manufacturing to fabricate nanostructured Si and SiGe thermoelectric materials. High cooling rates (10 5 to 10 7 K/s) rates inherent to the LPBF process are conducive to forming such nanostructures. Moreover, this fabrication technique could also be suitable for fabricating complex geometries needed to achieve improved device level performance. Process mapping of commercial Si powder with irregular morphology was first performed to understand the LPBF processing behavior of this semiconductor material. Subsequent studies included in-house synthesized B-doped (p-type) Si7 8 Ge 22 spherical powder that was produced via ultrasonic atomization. Scan strategies involved multiple laser exposures to mitigate solidification cracking: a high density of >98% was achieved, but solidification cracking could not be fully eliminated. Subsequently, a high electrical resistivity (i.e., low conductivity) was observed, but the measured Seebeck coefficient, ∼230 μV/K @ 500 °C, proved that good semiconductor material was being fabricated. A subgrain cellular structure (5–10 μm) was observed as defined by Ge segregation to the intercellular boundaries. The remelting strategies helped lower the cooling rates in processing SiGe, but this still resulted in high residual stresses, which induced a remarkably high density of twins (78–95%) to accommodate the deformation. This unique grain structure offers an avenue for phonon scattering and potential improvements in thermoelectric performance.

figure of merit↗
DOE OSTI2021

Tandem Catalytic Antioxidant Nanoparticles Comprising Cerium Carbonate and Photoactive Metal Oxides

While photoactive metal oxides such as TiO 2 find widespread use in paints and coatings as well as cosmetics and suncare products, they also generate reactive oxygen species (ROS), which degrade materials and are associated with human-health pathologies. Here, we demonstrate a robust and potent catalytic antioxidant consisting of earth-abundant cerium carbonate nanoparticles and micron-size Ce 2 (CO 3 ) 3 . 8H 2 O, which are characterized by powder X-ray diffraction and scanning nanobeam electron diffraction. When dispersed with photoactive metal oxides, these cerium carbonate catalysts decrease the photodecomposition rate of organic dyes and commercial pigment colorants in aqueous media by up to 820-fold, as well as in acrylic coatings. X-ray photoelectron spectroscopy and kinetic experiments support the same tandem catalysis mechanism of photoprotection when using both micron-size Ce 2 (CO 3 ) 3 . 8H 2 O and cerium carbonate nanoparticles. This mechanism involves ROS disproportionation (catalyzed by cerium carbonate) and H 2 O 2 decomposition (partially catalyzed by TiO 2 ) pathways, both of which cerium carbonate also catalyzes on its own, crudely mimicking the function of the cascade system of superoxide dismutase and catalase enzymes. When cerium carbonate nanoparticles were dispersed at 2 wt % in polymethylmethacrylate, the transparency of the polymer film was preserved and the photo-oxidative degradation of the polymer was prevented following UV irradiation at 254 nm, which otherwise resulted in the loss of optical properties and hydroxylation as characterized by ATR-FTIR spectroscopy, in the control polymer lacking cerium carbonate. Similar observations were made regarding color preservation in paint films comprising dye and insoluble commercial colorant pigments. The material chemistry associated with this photoprotection catalysis is subtle and emphasizes the importance of both Ce(III) and carbonate together, as both CePO 4 and Na 2 CO 3 are inactive. In conclusion, this emphasis is also apparent in comparisons of photoprotection catalysis with previously reported cerium oxide nanoparticles, which are significantly less active compared with Ce 2 (CO 3 ) 3 . 8H 2 O under the same conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗