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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Deep Eutectic Solvents: A Review of Fundamentals and Applications

Deep eutectic solvents (DESs) are an emerging class of mixtures characterized by significant depressions in melting points compared to those of the neat constituent components. These green materials are promising for applications as inexpensive ’designer’ solvents exhibiting a host of tunable physicochemical properties. Here, a detailed review of the current literature reveals the lack of predictive understanding of the microscopic mechanisms that govern the structure-property relationships in this class of solvents. Complex hydrogen bonding behavior is postulated as the root cause of their melt-ing point depressions and physicochemical properties; to understand these hydrogen bonded networks, it is imperative to study these systems as dynamic entities using both simulations and experiments. This review emphasizes recent research efforts in order to elucidate the next steps needed to develop a fundamental framework for understanding DESs. It covers recent developments in DES research, frames outstanding scientific questions, and identifies gainful research thrusts that would advance the field towards predictive models and fundamental understanding of these solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Comparison between explicit and implicit discretization strategies for a dissipative thermal environment

We investigate strategies for simulating open quantum systems coupled to dissipative baths by comparing explicit wave function-based discretization [via multi-layer multi-configuration time-dependent Hartree (ML-MCTDH)] and the implicit density matrix-based master equation method [via tree tensor network hierarchical equations of motion (TTN-HEOM)]. For dissipative baths characterized by exponentially decaying bath correlation functions, the implicit discretization approach of HEOM—rooted in bath correlation function decompositions—proves significantly more efficient than explicit discretization of the bath into discrete harmonic modes. Explicit methods, like ML-MCTDH, require extensive mode discretization to approximate continuum baths, leading to computational bottlenecks. Case studies for two-level systems and a Fenna–Matthews–Olson complex model highlight TTN-HEOM’s superiority in capturing dissipative dynamics with relaxations with a minimal number of auxiliary modes, while the explicit methods are as exact as the HEOM in pure dephasing regimes. This comparison is enabled by the TENSO package, which has both ML-MCTDH and TTN-HEOM implemented using the same computational structure and propagation strategy.

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

Analysis of Dynamical Peculiarities in Nanoalloys at Subsystems Level: Dynamical Degrees of Freedom, Temperature Differences, and the Chameleon Effect

Abstract A novel analysis of the dynamical behavior of nanoalloy systems, as represented by model Ni/Al 13‐atom clusters, over a broad range of energies that cover the stage‐wise transition of the systems from their solid‐like to liquid‐like state is presented. Conceptually, the analysis is rooted in partitioning the systems into judiciously chosen subsystems and characterizing the latter in terms of subsystem‐specific dynamical descriptors that include dynamical degrees of freedom , root‐mean‐square bond‐length fluctuation , and element‐specific subsystem temperature . The analysis reveals a host of intriguing new peculiarities in the dynamical behavior of the Ni/Al 13‐mers, among which are what we call the chameleon effect and the difference in the temperatures of the Ni and Al subsystems at high energies, a difference that strongly depends on the cluster composition and also changes with energy. These do not have an analog in pure Ni 13 and Al 13 and are explained in terms of the coupled effects of the difference between the masses of the Ni and Al atoms (the mass effect) and of the difference in the anharmonicity of the overall interaction potential as experienced by the Ni and Al subsystems of the clusters (the potential effect).

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

A classical model for three-body interactions in aqueous ionic systems

We present a classical induction model to evaluate the three-body ion–water–water (I–W–W) and water–water–water (W–W–W) interactions in aqueous ionic systems. The classical description of the induction energy is based on electrostatic distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole on the O and H atoms of water. The monatomic ions were described by a point charge and a dipole–dipole polarizability, while for the polyatomic ions, distributed multipoles up to hexadecapole and distributed polarizabilities up to quadrupole–quadrupole were used. The accuracy of the classical model is benchmarked against an accurate dataset of 936 (I–W–W) and 2184 (W–W–W) three-body terms for 13 different monatomic and polyatomic cation and anion systems. The classical model shows excellent agreement with the reference second order Moller–Plesset and coupled-cluster single double and perturbative triple [CCSD(T)] three-body energies. The Root-Mean-Square-Errors (RMSEs) for monatomic cations, monatomic anions, and polyatomic ions were 0.29, 0.25, and 0.12 kcal/mol, respectively. The corresponding RMSE for 1744 CCSD(T)/aVTZ three-body (W–W–W) energies, used to train MB-pol, was 0.12 kcal/mol. The accuracy of the proposed classical model demonstrates that the three-body term for aqueous ionic systems can be accurately modeled classically. This approach provides a fast, efficient, and as-accurate path toward modeling the three-body term in aqueous ionic systems that is fully transferable across systems with different ions without the need to fit to tens of thousands of ab initio calculations for each ion to extend existing many-body force fields to interactions between water and ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Microbially mediated iron redox cycling of subsurface sediments from Hanford Site, Washington State, USA

Iron-bearing clay minerals are predominant in soils and sediments, and they undergo oxidation-reduction cycles as a result of natural processes such as wetting/drying cycles and plant root respiration. However, the kinetics and mechanisms of multiple redox cycles of iron in clay-rich sediments and consequences of such cycling on sediment properties are poorly understood. The objective of this study was to understand how multiple redox cycles of Fe in clay-rich sediment affect the rate and extent of Fe bioreduction and the physicochemical properties of the sediment. A natural sediment sample containing Fe-bearing montmorillonite from Hanford, Washington, USA was size-fractionated [2.0 to 0.5 μm (Hanford-C) and 0.5 to 0.02 μm (Hanford-F)] and redox-cycled for four times. Bioreduction was achieved utilizing Geobacter sulfurreducens and re-oxidization was performed with sparged air. Time-course change of total Fe (II) was monitored to measure the rate and extent of Fe (III) bioreduction. Redox-cycled sediments were characterized to determine the physicochemical changes. Both the initial rate and extent of bioreduction fluctuated across the four redox cycles, but they ultimately decreased from 5.3 μmol g -1 h -1 and 22.9% to nearly zero by the fourth cycle. These fluctuation patterns were likely due to a combined effect of reductive dissolution of small/poorly crystalline clay particles (by 3–5%) and clay mineral structural changes, as evidenced by redox induced changes of aqueous chemistry, surface area, cation exchange capacity, mineralogy, and Mössbauer parameters. Once these small/poorly crystalline clay particles were dissolved, structural Fe in residual larger and more crystalline clay particles was largely reversible across additional redox cycles, as revealed by Mössbauer spectroscopy through the first three cycles.

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

Hyphae move matter and microbes to mineral microsites: Integrating the hyphosphere into conceptual models of soil organic matter stabilization

Associations between soil minerals and microbially derived organic matter (often referred to as mineral-associated organic matter or MAOM) form a large pool of slowly cycling carbon (C). Here, the rhizosphere, soil immediately adjacent to roots, is thought to control the spatial extent of MAOM formation because it is the dominant entry point of new C inputs to soil. However, emphasis on the rhizosphere implicitly assumes that microbial redistribution of C into bulk (non-rhizosphere) soils is minimal. We question this assumption, arguing that because of extensive fungal exploration and rapid hyphal turnover, fungal redistribution of soil C from the rhizosphere to bulk soil minerals is common, and encourages MAOM formation. First, we summarize published estimates of fungal hyphal length density and turnover rates and demonstrate that fungal C inputs are high throughout the rhizosphere–bulk soil continuum. Second, because colonization of hyphal surfaces is a common dispersal mechanism for soil bacteria, we argue that hyphal exploration allows for the non-random colonization of mineral surfaces by hyphae-associated taxa. Third, these bacterial communities and their fungal hosts determine the chemical form of organic matter deposited on colonized mineral surfaces. Collectively, our analysis demonstrates that omission of the hyphosphere from conceptual models of soil C flow overlooks key mechanisms for MAOM formation in bulk soils. Moving forward, there is a clear need for spatially explicit, quantitative research characterizing the environmental drivers of hyphal exploration and hyphosphere community composition across systems, as these are important controls over the rate and organic chemistry of C deposited on minerals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Adaptive tau-leaping methods for microscopic-lattice kinetic Monte Carlo simulations

Traditional Kinetic Monte Carlo (KMC) approaches, rooted in Gillespie’s stochastic simulation algorithm, become computationally demanding in systems with a large range of timescales. The goal of this work is to propose and study new adaptive lattice-KMC time integration strategies for spatially non-uniform systems. To that end, two novel adaptive tau-leaping methods and their corresponding time integration strategies are developed based on the idea of the “n-fold” direct KMC method. These strategies allow for the simultaneous execution of multiple reactions, advancing time by adaptively selected coarse increments. We present numerical experiments comparing the proposed methods with existing approaches in a catalytic surface kinetics application involving ammonia decomposition.

Bimolecular reactions↗
DOE OSTI2024

Organic carbon feedbacks to soil structure in Profundihumic and Haplic Ferralsols in Campinas, Sao Paulo, Brazil

Increasing soil organic matter content coincides with increasing soil porosity and decreasing bulk density, but the mechanisms that lead to changes in soil structure are unclear. We quantified and compared soil characteristics across two contrasting soils (heavily weathered ferralsols in Brazil) to clarify the effects of organic matter content on soil porosity. We found that high organic matter content fosters higher biologic activity, including root growth and animal burrowing, which in turn increase soil porosity and decreases bulk density.This dataset includes soil physical, morophological, and chemical variables from 6 soil profiles were sampled in Campinas, Sa ̃o Paulo state, southeastern Brazil to 1 m depth. Sites are regenerated mixed savanna and rainforest in the protected area of Viracopos Airport in Campinas, lightly grazed by cattle.This dataset includes soil color, bulk density, texture (percent sand, silt, clay, and coarse fragments as well as class), soil pH, cation exchange capacity, C stock, C concentration, N stock, N concentration, delta 13C, Delta 14C, and soil porosity in Excel and csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Ligand accommodation causes the anti-centrosymmetric structure of Au 13 Cu 4 clusters with near-infrared emission

Here, we synthesized an [Au 13 Cu 4 (PPh 3 ) 4 (SPy) 8 ] + nanocluster co-capped by phosphine and thiolate ligands. Interestingly, this Au 13 Cu 4 cluster corresponds to an anti-centrosymmetric structure with the four copper atoms coordinated to the mixed ligands on the same side of the Au 13 icosahedron, which is in sharp contrast to the [Au 13 Cu 4 (PPh 2 Py) 4 (SPhtBu) 8 ] + and [Au 13 Cu 2 (PPh 3 ) 6 (SPy) 6 ] + clusters which possess highly symmetric structures with well-separated Cu adatoms. Both [Au 13 Cu 4 (PPh 3 ) 4 (SPy) 8 ] + and [Au 13 Cu 2 (PPh 3 ) 6 (SPy) 6 ] + clusters correspond to 8 valence electron superatoms with large HOMO–LUMO gaps, respectively. The difference in structure is rooted in the nature of the mixed ligands, with the bidentate SPy binding strongly to Cu on both binding sites (–N–Cu and Au-SR-Cu) leading to the co-linking of adjacent Cu atoms, while the bidentate PPh 2 Py binds Cu on one site and Au on the other giving rise to a separation of the Cu atoms even in the presence of relatively higher monomer concentration. Both [Au 13 Cu 4 (PPh 3 ) 4 (SPy) 8 ] + and [Au 13 Cu 2 (PPh 3 ) 6 (SPy) 6 ] + display emissions in the near-IR regions. TD-DFT calculations reproduce the spectroscopic results with specified excited states, shedding light on the geometric and electronic behaviors of the ligand-protected Au 13 M x clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A matrix completion algorithm for efficient calculation of quantum and variational effects in chemical reactions

This work examines the viability of matrix completion methods as cost-effective alternatives to full nuclear Hessians for calculating quantum and variational effects in chemical reactions. The harmonic variety-based matrix completion (HVMC) algorithm, developed in a previous study (https://doi.org/10.1063/5.0018326), exploits the low-rank character of the polynomial expansion of potential energy to recover, using a small sample, vibrational frequencies (square roots of nuclear Hessian eigenvalues) constituting the reaction path. Furthermore, these frequencies are essential for calculating rate coefficients using variational transition state theory with multidimensional tunneling (VTST-MT). HVMC performance is examined for four SN2 reactions and five hydrogen transfer reactions, with each H-transfer reaction consisting of at least one vibrational mode strongly coupled to the reaction coordinate. HVMC is robust and captures zero-point energies, vibrational free energies, zero-curvature tunneling, and adiabatic ground state and free energy barriers as well as their positions on the reaction coordinate. For medium to large reactions involving H-transfer, with the exception of the most complex Ir catalysis system, less than 35% of total eigenvalue information is necessary for accurate recovery of key VTST-MT observables.

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

Atom Equivalent Energies for the Rapid Estimation of the Heat of Formation of Explosive Molecules from Density Functional Tight Binding Theory

Atom equivalent energies have been derived from which the gas-phase heat of formation of explosive molecules can be estimated from fast, semiempirical density functional tight binding total energy calculations. The root-mean-square deviation and maximum deviation of the heats of formation from the experimental values for the set of 45 energetic molecules compiled by Byrd and Rice [ J. Phys. Chem. A, 2006, 110, 1005–1013] are 10.4 and 25.5 kcal/mol, respectively, using 4 atom equivalent energies and 7.4 and 15.0 kcal/mol, respectively, using 7 atom equivalent energies. These errors are around a factor of 2–3 larger than those obtained from density functional theory calculations but are smaller than those obtained from other semiempirical electronic structure methods. Heats of formation calculated with density functional tight binding theory using the 4 and 7 atom equivalent energies, the Byrd and Rice scheme, and the atom pair contribution method for a new set of 531 energetic molecules that contain only carbon, hydrogen, nitrogen, and oxygen are provided.

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

Design of nematic liquid crystals to control microscale dynamics

The dynamics of small particles, both living such as swimming bacteria and inanimate, such as colloidal spheres, has fascinated scientists for centuries. If one could learn how to control and streamline their chaotic motion, that would open technological opportunities in the transformation of stored or environmental energy into systematic motion, with applications in micro-robotics, transport of matter, guided morphogenesis. This review presents an approach to command microscale dynamics by replacing an isotropic medium with a liquid crystal. Orientational order and associated properties, such as elasticity, surface anchoring, and bulk anisotropy, enable new dynamic effects, ranging from the appearance and propagation of particle-like solitary waves to self-locomotion of an active droplet. By using photoalignment, the liquid crystal can be patterned into predesigned structures. In the presence of the electric field, these patterns enable the transport of solid and fluid particles through nonlinear electrokinetics rooted in anisotropy of conductivity and permittivity. Director patterns command the dynamics of swimming bacteria, guiding their trajectories, polarity of swimming, and distribution in space. This guidance is of a higher level of complexity than a simple following of the director by rod-like microorganisms. Namely, the director gradients mediate hydrodynamic interactions of bacteria to produce an active force and collective polar modes of swimming. The patterned director could also be engraved in a liquid crystal elastomer. When an elastomer coating is activated by heat or light, these patterns produce a deterministic surface topography. The director gradients define an activation force that shapes the elastomer in a manner similar to the active stresses triggering flows in active nematics. Finally, the patterned elastomer substrates could be used to define the orientation of cells in living tissues. The liquid-crystal guidance holds a major promise in achieving the goal of commanding microscale active flows.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of Vegetation on Fluxes of Nitric Oxide, Nitrogen Dioxide, and Nitrous Oxide in a Mixed Deciduous Forest Clearing

Atmosphere-terrestrial exchange of nitrogen oxides, such as nitric oxide (NO), nitrogen dioxide (NO2) and nitrous oxide (N2O), plays an important role in controlling atmospheric composition and the radiative forcing of Earth’s atmosphere. In this study, the impact of vegetation ground cover on NOx (NOx = NO + NO2) and N2O fluxes in a deciduous forest clearing was studied using dynamic flow chambers located on three experimental plots with differing vegetation ground cover. Microbial emissions of NO and N2O were observed throughout the measurement period, while NO2 was exclusively deposited. Vegetation had no observable impact on NO2 deposition. Under dry conditions, total measured nitrogen emissions were numerically similar across all plots, although the N2O:NO ratio was higher for plots containing plants. Vegetation elevates soil water content through enhanced water retention, a condition that favors denitrification and more N2O production, relative to NO. Two rain events induced pulses of NO and N2O that were higher for bare soil compared to the vegetated plots. Lower NO and N2O emissions in plant-containing chambers stemmed from enhanced root uptake of N following rewetting, which diminished the amount of N substrate available for microbial NO and N2O production. The sensitivity of soil N emissions to vegetation ground cover highlights the need for more studies that investigate this effect over a wide range of ecosystems and to include vegetation effects in future parameterizations of soil NOx and N2O used in atmospheric models. This dataset includes processed data collected from 4 dynamic flux chambers and 17 sensors. Data includes ambient gas measurements made 1 m from the surface and soil flux measurements of NO, NO2, N2O, ozone (O3) and carbon dioxide (CO2). Also included is a suite of meteorological (air temperature, humidity, pressure) and soil parameters (water filled pore space, soil temperature). Refer to the readme for more information about each of the data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Ground State Electronic Energy of Benzene

We report here on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground-state energy of the benzene molecule in a standard correlation-consistent basis set of double-ζ quality. As a broad international endeavor, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around -863 mE H . However, we find the root-mean-square deviation of the energies from the studied methods to be considerable (1.3 mE H ), which in light of the acclaimed performance of each of the methods for smaller molecular systems clearly displays the challenges faced in extending reliable, near-exact correlation methods to larger systems. While the discrepancies exposed by our study thus emphasize the fact that the current state-of-the-art approaches leave room for improvement, we still expect the present assessment to provide a valuable community resource for benchmark and calibration purposes going forward.

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

Influence of intermolecular interactions on the infrared complex indices of refraction for binary liquid mixtures

This paper investigates the accuracy of deriving the composite optical constants of binary mixtures from only the complex indices of refraction of the neat materials. These optical constants enable the reflectance spectra of the binary mixtures to be modeled for multiple scenarios (e.g., different substrates, thicknesses, volume ratios), which is important for contact and standoff chemical detection. Using volume fractions, each mixture's complex index of refraction was approximated via three different mixing rules. To explore the impact of intermolecular interactions, these predictions are tested by experimental measurements for two representative sets of binary mixtures: (1) tributyl phosphate combined with n-dodecane, a non-polar medium, to represent mixtures which primarily interact via dispersion forces and (2) tributyl phosphate and 1-butanol to represent mixtures with polar functional groups that can also interact via dipole–dipole interactions, including hydrogen bonding. The residuals and the root-mean-square error between the experimental and calculated index values are computed and demonstrate that for miscible liquids in which the average geometry of the cross-interactions can be considered isotropic (e.g., dispersion), the refractive indices of the mixtures can be modeled using composite n and k values derived from volume fractions of the neat liquids. Conversely, in spectral regions where the geometry of the cross-interactions is more restricted and anisotropic (e.g., hydrogen bonding), the calculated n and k values vary from the measured values. The impact of these interactions on the reflectance spectra are then compared by modeling a thin film of the binary mixtures on an aluminum substrate using both the measured and the mathematically computed indices of refraction.

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

Quantitative insights for diagnosing performance bottlenecks in lithium–sulfur batteries

Lithium–sulfur (Li–S) batteries hold significant promise for electric vehicles and aviation due to their high energy density and cost-effectiveness. However, understanding the root causes of performance degradation remains a formidable challenge, as the interplay of multiple factors obscures key failure mechanisms. A major limitation has been the inability to quantify soluble sulfur species within practical detection limits accurately and to correlate electrochemical processes with associated physical inventory changes. Here, we introduce the high-performance liquid chromatography-ultraviolet spectroscopy and gas chromatography sequential characterization (HUGS) toolkit, capable of precisely quantifying seven distinct sulfur and polysulfide species at concentrations as low as 40 ppb. HUGS has been successfully applied to practical coin and pouch cells without requiring cell modification. Furthermore, our self-developed software, Dr HUGS, enhanced the data analysis speed by over 30 times, enabling multi-source data integration and delivering comprehensive analysis results within minutes. Using HUGS, we identify significant capacity losses from inactive lithium and sulfur during initial cycles and sulfide-rich solid–electrolyte interphase (SEI) formation on the anode during later cycles. Notably, our findings reveal that soluble polysulfides have minimal contributions to capacity loss, challenging long-standing assumptions. Moreover, HUGS demonstrates that constant-pressure setups in Li–S pouch cells improve compositional uniformity compared to constant-gap configurations. For sulfurized polyacrylonitrile (SPAN) cathodes, unique issues such as non-sulfide SEI formation and lithium pulverization are observed, which can be mitigated through localized high-concentration electrolytes to enhance lithium inventory retention. By enabling precise quantification of critical inventory components, HUGS provides transformative insights into failure mechanisms across various electrolytes and cathode chemistries, guiding rational design strategies for next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2019

Stochastic embedding DFT: Theory and application to p -nitroaniline in water

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham density functional theory (DFT) method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here in this paper, we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected subsystem(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest, the properties are often determined by only a small subsystem. In stochastic embedding DFT, two sets of orbitals are used: a deterministic one associated with the embedded subspace and the rest, which is described by a stochastic set. The method agrees exactly with deterministic calculations in the limit of a large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with nonembedding stochastic DFT.

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

Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model

In this work, we report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗