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DOE OSTI2023

Analysis of Organic Electron Materials using Neutron Scattering (Final Report)

Neutron scattering is a powerful suite of measurement techniques that enable unique analysis of structure and dynamics of a wide variety of materials. Specifically, neutrons interact strongly with protons, which enables excellent contrast in light element organic materials that cannot be obtained with any other measurements. This series of three proposals focused on using inelastic neutron scattering (INS) to study the vibrations (dynamics) of the organic molecules involved in organic electronic devices. Our main goals were to demonstrate that INS is capable of elucidating new, useful, and unique knowledge about organic electronic samples that could be used to improve the function of devices or to solve outstanding problems that could not be solved using other measurement techniques. Since all of the goal involved using INS or other neutron techniques to do something “new” a large part of the effort was focused on complex data interpretation and development of modeling workflows that could be used by other members of the organic electronics community to study their materials. To facilitate the goal of making INS measurements more accessible to a broader community and for a wider range of materials, we optimized and engineered the computational workflows to be well documented, publicly available, and user friendly. The individual titles of the three sequential DOE-BES awards are: (1) Engineering doping profiles in organic semiconducting materials, (2) Measurement and modeling of molecular dopant structure and dynamics, and (3) Quantification of Dynamic Disorder in Electronic and Excitonic Organic Materials. For readability, this report is organized to highlight the progress of the research thematically. Many of the ideas started in one grant period and then spilled over into later awards and collaborative research.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Fracture Network Influence on Rock Damage and Gas Transport following an Underground Explosion

Simulations of rock damage and gas transport following underground explosions that omit preexisting fracture networks in the subsurface cannot fully characterize the influence of geo-structural variability on gas transport. Previous studies do not consider the impact that fracture network structure and variability have on gas seepage. In this study, we develop a sequentially coupled, axi-symmetric model to look at the damage pattern and resulting gas breakthrough curves following an underground explosion given different fracture network realizations. We simulate 0.327 and 0.164 kT chemical explosives with burial depths of 100 m for 90 stochastically generated fracture networks. Gases quickly reach the surface in 30% of the higher yield simulations and 5% of the lower yield simulations. The fast breakthrough can be attributed to the formation of connected pathways between fractures to the surface. The formation of a connected damage pathway to the surface is not clearly correlated with the fracture intensity (P32) in our simulations. Breakthrough curves with slower transport are highly variable depending on the fracture network sample. The variability in the breakthrough behavior indicates that ignoring the influence of fracture networks on rock damage, which strongly influences the hydraulic properties following an underground explosion, will likely lead to a large underestimation of the uncertainty in the gas transport to the surface. This work highlights the need for incorporation of fracture networks into models for accurately predicting gas seepage following underground explosions.

58 GEOSCIENCES↗

DOE OSTI2018

Stochastic Generation Capacity Expansion Planning with Approximate Dynamic Programming

Failing to consider the many long-term uncertainties that affect the performance of a power generation portfolio can result in suboptimal generation expansion plans. Further, traditional deterministic approaches can omit flexible plans that are able to adapt to future events. In this paper, we explore the use of approximate dynamic programming (ADP) to create forward-looking generation expansion plans. A case study is included with three sequential decision periods; three generation technologies; and four uncertainties: demand growth, natural gas prices, renewable portfolio standards, and the adoption of customer-driven solar generation. The flexible plans found through ADP show a 3 % reduction in total expected cost when compared to myopic planning heuristics while circumventing the computational burdens that accompany high-dimensional dynamic programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Measurement of the Drell-Yan forward-backward asymmetry at high dilepton masses in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the forward-backward asymmetry of pairs of oppositely charged leptons (dimuons and dielectrons) produced by the Drell-Yan process in proton-proton collisions is presented. The data sample corresponds to an integrated luminosity of 138 fb -1 collected with the CMS detector at the LHC at a center-of-mass energy of 13 TeV. The asymmetry is measured as a function of lepton pair mass for masses larger than 170 GeV and compared with standard model predictions. An inclusive measurement across both channels and the full mass range yields an asymmetry of 0.612 ± 0.005 (stat) ± 0.007 (syst). As a test of lepton flavor universality, the difference between the dimuon and dielectron asymmetries is measured as well. No statistically significant deviations from standard model predictions are observed. The measurements are used to set limits on the presence of additional gauge bosons. For a Z' boson in the sequential standard model the observed (expected) 95% confidence level lower limit on the Z' mass is 4.4 TeV (3.7 TeV).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Dynamic deuterium retention properties of tungsten measured using laser-induced breakdown spectroscopy

Dynamic deuterium (D) retention properties of tungsten (W) are investigated under steady-state D plasma exposure in the PISCES-A linear plasma device. In contrast to static retention, dynamic retention is quickly released from the material at the termination of the incident plasma flux, and thus in-operando laser-induced breakdown spectroscopy (LIBS) measurements have been conducted during steady-state D plasma exposure. A procedure is, first, established to extract the dynamic retention component from the in-operando LIBS D I 656.1 nm line intensity, which can contain contributions from dynamic and static retention as well as background D/D 2 gas, excited by both steady-state and laser-induced plasmas. Using the developed procedure, the dynamic D retention in W is systematically examined while scanning the following plasma exposure parameters: incident ion energy, E i , sample temperature, T s , incident ion flux, Γ i . No clear E i dependence is seen in the range of E i ~ 45–175 eV, as expected from a small variation in the average implantation depth (~3-6 nm) of D in W. The dynamic retention is found to monotonously decrease with increasing T s from 348 to 573 K, while the total static retention is reported to peak at T s ~ 500–600 K. It is revealed that the dynamic retention linearly increases with increasing Γ i , and then saturates at Γ i ≥ 0.75 × 10 21 m –2 s –1 . Possible physical mechanisms for the observed dependence of the dynamic retention on T s and Γ i are discussed. Furthermore, sequential pure He, followed by pure D, plasma exposures show that the dynamic D retention is not strongly affected by He bubbles in the near-surface region.

super-saturated surface layer↗

DOE OSTI2017

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at $\sqrt{s}$ = 13 TeV and combination with 8 TeV data

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions at $ \sqrt{s} = $ 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb$^{-1}$ and for the dimuon sample 2.9 fb$^{-1}$. The sensitivity of the search is increased by combining these data with a previously analysed set of data obtained at $ \sqrt{s} = $ 8 TeV and corresponding to a luminosity of 20 fb$^{-1}$. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the $\mathrm{Z}'_{\text{SSM}}$ particle, which arises in the sequential standard model, and for the superstring inspired $\mathrm{Z}'_{\psi}$ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for Kaluza-Klein gravitons arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. Lastly, these results significantly extend previous limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

CONSERVB: A numerical method to compute soil water content and temperature profiles under a bare surface

A comprehensive, yet fairly simple model of water disposition in a bare soil profile under the sequential impact of rain storms and other atmospheric influences, as they occur from hour to hour is presented. This model is intended mostly to support field studies of soil moisture dynamics by our current team, to serve as a background for the microwave measurements, and, eventually, to serve as a point of departure for soil moisture predictions for estimates based in part upon airborne measurements. The main distinction of the current model is that it accounts not only for the moisture flow in the soil-atmosphere system, but also for the energy flow and, hence, calculates system temperatures. Also, the model is of a dynamic nature, capable of supporting any required degree of resolution in time and space. Much critical testing of the sample is needed before the complexities of the hydrology of a vegetated surface can be related meaningfully to microwave observations.

Vanbavel, C. H. M.↗

NASA NTRS2012

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗

DOE OSTI2024

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community

Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Sequential lateral solidification of silicon thin films on low-k dielectrics for low temperature integration

We present the excimer laser crystallization of amorphous silicon on a low dielectric constant (low-k) insulator for very large scale integration monolithic 3D integration and demonstrate that low dielectric constant materials are suitable substrates for 3D integration through laser crystallization of silicon thin films. We crystallized 100 nm amorphous silicon on top of SiO{sub 2} and SiCOH (low-k) dielectrics, at different material thicknesses (1 μm, 0.75 μm, and 0.5 μm). The amorphous silicon crystallization on low-k dielectric requires 35% less laser energy than on an SiO{sub 2} dielectric. This difference is related to the thermal conductivity of the two materials, in agreement with one dimensional simulations of the crystallization process. We analyzed the morphology of the material through defect-enhanced microscopy, Raman spectroscopy, and X-ray diffraction analysis. SEM micrographs show that polycrystalline silicon is characterized by micron-long grains with an average width of 543 nm for the SiO{sub 2} sample and 570 nm for the low-k samples. Comparison of the Raman spectra does not show any major difference in film quality for the two different dielectrics, and polycrystalline silicon peaks are closely placed around 517 cm{sup −1}. From X-ray diffraction analysis, the material crystallized on SiO{sub 2} shows a preferential (111) crystal orientation. In the SiCOH case, the 111 peak strength decreases dramatically and samples do not show preferential crystal orientation. A 1D finite element method simulation of the crystallization process on a back end of line structure shows that copper (Cu) damascene interconnects reach a temperature of 70 °C or lower with a 0.5 μm dielectric layer between the Cu and the molten Si layer, a favorable condition for monolithic 3D integration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1995

Sizing up the sub-Tommotian unconformity in Siberia

Sedimentary rocks in the western Anabar region, northwestern Siberia, preserve an exceptional record of evolution and biogeochemical events near the Proterozoic-Cambrian boundary. Carbon isotopic data on petrographically and geochemically screened samples collected at 1 to 2 m intervals support correlation of the lower Anabar succession (Staraya Reckha and lower Manykai Formations) with sub-Tommotian carbonates of the Ust'-Yu-doma Formation in southeastern Siberia. In contrast, the upper Manykai and most of the overlying Medvezhya Formation appear to preserve a sedimentary and paleontological record of an evolutionary important time interval represented in southeastern Siberia only by the sub-Tommotian unconformity. Correlation of the Anabar section with other northern Siberian successions that contain well-dated volcanic rocks permits the estimate that the sub-Tommotian unconformity in southeastern Siberia spans approximately 3 to 6 m.y. Diverse small shelly fossils (but not archaeocyathans) previously thought to mark the base of the Tommotian Stage evolved sequentially throughout this earlier interval.

NASA Discipline Exobiology↗

DOE OSTI2014

Precipitation hydrometeor type relative to the mesoscale airflow in mature oceanic deep convection of the Madden-Julian Oscillation

We present that composite analysis of mature near-equatorial oceanic mesoscale convective systems (MCSs) during the active stage of the Madden-Julian Oscillation (MJO) shows where different hydrometeor types occur relative to convective updraft and stratiform midlevel inflow layers. The National Center for Atmospheric Research (NCAR) S-PolKa radar observed these MCSs during the Dynamics of the Madden-Julian Oscillation/Atmospheric Radiation Measurement-MJO Investigation Experiment (DYNAMO/AMIE). NCAR's particle identification algorithm (PID) is applied to S-PolKa's polarimetric data to identify the dominant hydrometeor type in each radar sample volume. Combining S-PolKa's Doppler velocity data with the PID demonstrates that hydrometeors have a systematic relationship to the airflow within mature MCSs. In the convective region, moderate rain occurs within the updraft core; the heaviest rain occurs just downwind of the core; wet aggregates occur immediately below the melting layer; narrow zones containing graupel/rimed aggregates occur just downstream of the updraft core at midlevels; dry aggregates dominate above the melting level; and smaller ice particles occur along the edges of the convective zone. In the stratiform region, rain intensity decreases toward the anvil; melting aggregates occur in horizontally extensive but vertically thin regions at the melting layer; intermittent pockets of graupel/rimed aggregates occur atop the melting layer; dry aggregates and small ice particles occur sequentially above the melting level; and horizontally oriented ice crystals occur between -10°C and -20°C in turbulent air above the descending midlevel inflow, suggesting enhanced depositional growth of dendrites. Finally, the organization of hydrometeors within the midlevel inflow layer is insensitive to the presence or absence of a leading convective line.

58 GEOSCIENCES↗

NASA NTRS2003

Possible Class of Nearby Gamma-Ray Burst/Gravitational Wave Sources

A possible subclass of gamma-ray bursts - those with few, wide pulses, spectral lags of order one to several seconds, and soft spectra - has been identified. Their Log[N]-Log[Fp] distribution approximates a -3/2 power-law, suggesting homogeneity and relatively nearby sources. These mostly dim bursts account for approximately 50% of the BATSE sample of long bursts near that instrument s trigger threshold, suggesting that this subluminous class constitutes a more common variety than the more familiar burst sources which lie at truly cosmological distances. Theoretical scenarios predicted such a class, motivated by their exemplar GRB 980425 (SN 1998bw) lying at a distance of approximately 38 Mpc. The observations are explained by invoking off-axis viewing of the GRB jet and/or bulk Lorentz factors of order a few. Long-lag bursts show a tendency to concentrate near the Supergalactic Plane with a quadrupole moment of -0.10 plus or minus 0.04, similar to that for SNe type Ib/c within the same volume. The rate of the observed subluminous bursts is of order 1/4 that of SNe Ib/c. Evidence for a sequential relationship between SNe Ib/c and GRBs is critiqued for two cases, as simultaneity of the SN and GRB events may be important for detection of the expected gravitational wave signal; at most, SN to GRB delays appear to be a few days. SN asymmetries and ultrarelativistic GRB jets suggest the possibility of rapid rotation in the pre-collapse objects, a primary condition required for highly nonaxisymmetric SN collapse to produce strong gravitational waves.

Norris, Jay P.↗

DOE OSTI2021

Z-Sequence: photometric redshift predictions for galaxy clusters with sequential random k-nearest neighbours

ABSTRACT We introduce Z-Sequence, a novel empirical model that utilizes photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimize photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study, we train, fine-tune, and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of |Δ$z$|/(1 + $z$) (across a photometric redshift range of 0.05 ≤ $z$ ≤ 0.6) to be ∼0.01 when applying a small search radius. The photometric redshift prediction error for test samples increases by 30–50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.

Chan, Matthew C.↗

DOE OSTI2022

High manganese redox variability and manganate predominance in temperate soil profiles as determined by X-ray absorption spectroscopy

Manganese speciation is a key to understanding the fate of contaminants, nutrients, and organic matter in soils. To date, quantification of Mn species in bulk soils has been performed mainly by sequential extraction methods and rarely supported by spectroscopic analysis. In order to obtain quantitative information on the Mn species inventory of soils, we investigated 46 soil horizons (<2-mm fraction, 45.1–2,280 mg/kg Mn) of nine typical Central European soils (Cambisols, Chernozems, Luvisols, Podzol, Stagnosol) by chemical Mn analyses and Mn K-edge X-ray absorption spectroscopy, and related speciation results to major soil properties. Amounts of Mn 2+ , Mn 3+ , and Mn 4+ and the average oxidation state of Mn were evaluated by linear combination fitting (LCF) of X-ray absorption near edge structure (XANES) spectra. Additionally, we used extended X-ray absorption fine structure (EXAFS) spectroscopy to identify and quantify major Mn species. For this, EXAFS spectra of 20 organic and mineral soil samples from five soils (Cambisols, Chernozem, Luvisol) were analyzed by LCF and shell fitting. XANES analyses revealed a high Mn redox variability in organic surface layers, with Mn 2+ being most abundant (≤100%, $\overline{x}$ = 54%), followed by Mn 3+ (≤80%, $\overline{x}$ = 32%) and Mn 4+ (≤55%, $\overline{x}$ = 14%). Mineral soil horizons contained significantly less Mn 2+ (≤56%, $\overline{x}$ = 23%), about equal quantities of Mn 3+ (≤68%, $\overline{x}$ = 31%), and were enriched in Mn 4+ (≤89%, $\overline{x}$ = 46%). EXAFS analyses implied the presence of six major Mn species groups: manganates, organically complexed Mn, Mn(III) oxyhydroxides, silicate-bound Mn, Mn oxides without tunnel- or layer structure, and physisorbed Mn. In litter horizons, Mn was mainly present in organic complexes (58–91%, $\overline{x}$ = 78%) and as physisorbed Mn (≤15%), but individual horizons also comprised manganates, Mn(III) oxyhydroxides, and silicate-bound Mn. Manganates, likely mixtures of phyllomanganates with hexagonal layer symmetry and tectomanganates, dominated in all mineral soil horizons (37–94%, $\overline{x}$ = 67%). Correlation analysis showed that manganates dissolve completely during dithionite-citrate and acid ammonium oxalate extractions, and suggested that Mn 4+ -rich manganates preferentially form under less acidic soil conditions, partly by oxidation of organically complexed Mn(II), and that they are enriched in the soil clay fraction. Mineral soil horizons also contained minor quantities of organically complexed Mn (≤39%, $\overline{x}$ = 11%), silicate-bound Mn (≤30%, $\overline{x}$ = 8%), Mn(III) oxyhydroxides (≤37%, $\overline{x}$ = 7%), Mn oxides without tunnel- or layer structure (≤18%, $\overline{x}$ = 5%), and physisorbed Mn (≤14%, $\overline{x}$ <1%). The detection of Mn(III) oxyhydroxides such as feitknechtite (β-MnOOH) or groutite (α-MnOOH) as well as the spinel hausmannite (Mn 3 O 4 ) in acidic soils is remarkable, since their formation is normally linked to neutral or alkaline pH conditions. Minor contributions of silicate-bound Mn indicate the release of Mn from primary minerals already at early stages of soil formation, and low concentrations of physisorbed Mn suggest that exchangeable Mn is rapidly converted into manganates in oxic soils. In conclusion, the predominance of manganates in mineral soils has far-reaching implications for the functioning of soils and biogeochemical element cycles, as these minerals play an important role in metal binding, plant nutrition, and redox-related processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Low-temperature sequential pulsed chemical vapor deposition of ternary B{sub x}Ga{sub 1-x}N and B{sub x}In{sub 1-x}N thin film alloys

In this work, the authors have performed sequential pulsed chemical vapor deposition of ternary B{sub x}Ga{sub 1-x}N and B{sub x}In{sub 1-x}N alloys at a growth temperature of 450 °C. Triethylboron, triethylgallium, trimethylindium, and N{sub 2} or N{sub 2}/H{sub 2} plasma have been utilized as boron, gallium, indium, and nitrogen precursors, respectively. The authors have studied the compositional dependence of structural, optical, and morphological properties of B{sub x}Ga{sub 1-x}N and B{sub x}In{sub 1-x}N ternary thin film alloys. Grazing incidence X-ray diffraction measurements showed that boron incorporation in wurtzite lattice of GaN and InN diminishes the crystallinity of B{sub x}Ga{sub 1-x}N and B{sub x}In{sub 1-x}N sample. Refractive index decreased from 2.24 to 1.65 as the B concentration of B{sub x}Ga{sub 1-x}N increased from 35% to 88%. Similarly, refractive index of B{sub x}In{sub 1-x}N changed from 1.98 to 1.74 for increase in B concentration value from 32% to 87%, respectively. Optical transmission band edge values of the B{sub x}Ga{sub 1-x}N and B{sub x}In{sub 1-x}N films shifted to lower wavelengths with increasing boron content, indicating the tunability of energy band gap with alloy composition. Atomic force microscopy measurements revealed an increase in surface roughness with boron concentration of B{sub x}Ga{sub 1-x}N, while an opposite trend was observed for B{sub x}In{sub 1-x}N thin films.

36 MATERIALS SCIENCE↗