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At least 559 records · Page 31

Spatially resolved X-ray imaging and molecular characterisation of sulfur and iron in organic- and sulfur-rich hydrocarbon source mudstones

Sulfurisation of organic matter (OM) is a prominent preservation mechanism, however iron sulfide precipitation, particularly pyrite (FeS2), can counteract this mechanism. There is a dearth of high-resolution, spatially-resolved spectroscopic (redox) information on sulfur and iron inventories within organic-rich rocks that would improve our understanding of prevailing environmental conditions during deposition. Here, state-of-the-art synchrotron-based X-ray absorption and fluorescence analyses of key organic- and sulfur-rich mudstones demonstrate the potential of these techniques to non-destructively map and produce detailed spectroscopic information. Detailed high-resolution analyses (μm- to mm-scale) reveal the presence of widespread sulfurised OM in the Blackstone Band of the Kimmeridge Clay Formation, in line with a persistence of euxinia over a long temporal span and low reactive iron input, facilitating the preservation of OM through sulfurisation. In contrast, the presence of sulfurised OM was transitional in the Monterey Formation, consistent with fluctuating water column redox conditions, and is less significant in the Whitby Mudstone Formation, likely due to the high reactive iron concentrations outcompeting sulfurised OM formation. Analyses of sulfur species using model compounds further indicate that the Whitby Formation is strongly enriched in inorganic reduced sulfur minerals, while both the Kimmeridge Clay and Monterey Formations are dominated by organic sulfur species. These synchrotron-based observations improve our understanding of environmental conditions during the time of deposition of these mudstones and thus show great promise in the study of organic-rich sediments, especially in allowing their depositional settings to be more accurately reconstructed.

Kimmeridge Clay Formation↗

Optimization of battery swapping infrastructure for e-commerce drone delivery

Drone delivery is widely-researched to alter the current e-commerce delivery convention for providing short delivery lead times. Yet, flight range of drones, constrained by the available battery technology, sets a milestone toward realizing the sole-drone delivery. To tackle with the flight range limitation, locating automated battery swapping machines (ABSM) have been proposed and a few studies modeled the problem. Using the ABSMs, drones can be loaded with fully-charged batteries along the route to a demand location. Here, we introduce a mixed-integer nonlinear program to model the problem. The objective of the program is to optimally select ABSM locations, determine the delivery-mode choices (drone-only, truck-only, and mixed delivery) of demand locations, find drone delivery routes, and approximate the baseline requirements for the number of drones and batteries needed. The program minimizes the overall delivery system costs including: ABSM, delivery, drone ownership, battery inventory, and service congestion. A cutting-plane method is developed to find exact solutions in finite iterations. Computational experiments showed that the method quickly yields the optimal solution to instances with less than 60 ABSM candidates and 20 demand locations. A case study shows that the optimal drone delivery infrastructure can save almost 20% cost compared to the conventional truck-only delivery. Sensitivity analyses were conducted to reveal the impact of key parameters in the decision-making and found that a decrease in the ABSM and drone costs highly affect the system cost.

25 ENERGY STORAGE↗

Using hydrogen and ammonia for renewable energy storage: A geographically comprehensive techno-economic study

Hydrogen and, more recently, ammonia have received worldwide attention as energy storage media. In this work we investigate the economics of using each of these chemicals as well as the two in combination for islanded renewable energy supply systems in 15 American cities representing different climate regions throughout the country. We use an optimal combined capacity planning and scheduling model which minimizes the levelized cost of energy (LCOE) by determining optimal unit selection and size along with unit commitments, production rates, and storage inventories for each period of system operation. These periods are aggregated from full year hourly resolution data via a consecutive temporal clustering algorithm. Ammonia is generally more economical than hydrogen as a single method of energy storage. Additionally, systems which use both hydrogen and ammonia outperform those which use only one storage option and have LCOE between $\$ 0.17$/kWh and $\$ 0.28$/kWh, including full investment in renewable generation infrastructure.

25 ENERGY STORAGE↗

Computational materials assessment of the D/Li-stripping neutron source as a prototypical facility for fusion materials testing

As the US fusion materials community awaits the selection and design of a fusion prototypical neutron source (FPNS), a risk reduction exercise has been conducted to (i) provide an updated materials performance evaluation using state-of-the-art computational materials modeling, (ii) expand on legacy analysis based on pure Fe to other relevant fusion structural materials types, and (iii) ensure that materials response under FPNS operational conditions is consistent with referential fusion reactor conditions. The current paper describes the efforts undertaken to assemble a comprehensive computational methodology that includes neutronics, primary damage calculations, atomistic simulations of displacement cascades, chemical inventory evolution calculations, and a computational thermodynamic analysis of emerging phases during irradiation. Our work extends existing studies in pure Fe to reduced-activation ferritic/martensitic steels, tungsten, silicon carbide, and vanadium alloys. We focus on the single-beam deuteron/lithium-stripping neutron source behind the IFMIF-DONES concept, which we assess against ITER, two DEMO designs, and an ideal pure 14-MeV flux. Our analysis indicates that, within standard uncertainties inherent to the models employed, the DONES concept adequately captures fusion conditions in the four materials analyzed. Our work is intended as a comprehensive irradiation damage analysis of fusion-representative neutron sources, to be used for further neutron source evaluation and fusion facility operation.

Marian, Jaime [Univ. of California, Los Angeles, C↗

Democratizing life cycle assessment by developing a streamlined model of greenhouse gas emissions from US natural gas supply chains

Natural gas (NG) supply chains contribute substantially to the global energy supply and anthropogenic methane emissions, making them frequent subjects of life cycle assessments (LCAs). To better characterize central tendencies and variability, we systematically reviewed and harmonized published estimates of life cycle greenhouse gas (GHG) emissions from United States NG supply chains. Results informed a streamlined LCA model (SLiNG-GHG: streamlined LCAs of NG-GHGs) that quantifies carbon dioxide and methane from three gates: transmission, distribution, and shipping. Median estimates employing harmonized emission inputs, are 10, 11, and 21 g CO2e/MJ gas (100-year global warming potentials [GWPs]), and 20, 22, and 33 g CO2e/MJ gas (20-year GWPs), delivered to each gate, respectively. Alternatively, inputting available, independent methane measurements, SLiNG-GHG estimates varied from -23% to +316% relative to baseline. Bottom-up inventories used in LCAs tend to underestimate methane compared with measurements. Results underscore the need for open-source, streamlined LCA models that can easily incorporate rapidly evolving measurements for non-experts like investors and regulators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗

A machine learning pipeline for identifying infiltration managed aquifer recharge locations from satellite imagery in the San Joaquin Valley, California

This study focuses on an agricultural region in California’s Central Valley, USA, where Managed Aquifer Recharge (MAR) is widely implemented to mitigate groundwater depletion under increasing water demand and climate variability. A deep learning and machine learning framework was developed to identify infiltration-MAR locations using satellite imagery and environmental data. The framework integrates surface water detection from Sentinel-2 imagery, geospatial delineation of water bodies, spatiotemporal tracking of water body dynamics, and supervised classification using meteorological, environmental, and topographic variables. The framework was applied to a 2379 km² study area southwest of Fresno, where 765 water bodies were detected, including 139 identified MAR sites based on publicly available datasets and expert knowledge. The classification model achieved an accuracy of 0.94 and an F1 score of 0.85. Feature importance analysis indicates that cropland, normalized difference vegetation index (NDVI), and evaporation are among the most influential predictors for infiltration-MAR. Notably, the framework suggests that engineered water management in infiltration-MAR systems can disrupt or even reverse the expected positive correlation between surface water extent and precipitation. These findings provide physically interpretable insights into the characteristics of existing infiltration-MAR facilities and demonstrate the potential of the proposed framework as a reproducible, interpretable, and potentially transferable tool for data-driven infiltration-MAR identification and inventory development under growing climatic and hydrological uncertainty.

Classification↗

CO 2 conversion to syngas via electrification of endothermal reactors: Process design and environmental impact analysis

CO 2 utilization via reverse water gas shift (rWGS) reaction has been proposed as a path to the sustainable utilization. Here this work presents a detailed process modelling study where steam methane reforming (SMR) generated hydrogen was combined with rWGS to produce syngas (CO + H 2 ) with various hydrogen-to-carbon oxide ratios. To further decrease CO 2 emissions that may offset the benefits of CO 2 converted in rWGS, electrification of endothermal reactors, both SMR and rWGS was considered where CO 2 emitting fuel burning in the furnace was replaced by the emerging ohmic (resistive) heating. Material and energy inventory obtained from process design calculations was used to perform Life Cycle Analysis (LCA) to calculate environmental impacts of CO 2 consumption and reactor electrification. The results showed that greenhouse gas emissions, in CO 2 kg equivalent, were the lowest when both SMR and rWGS were heated using wind-generated electricity, decreasing from 25 to 10 kg CO 2 equivalent for H 2 :CO = 2:1 while the conventional electricity mix used for furnace electrical heating across the board of scenarios generated highest environmental impacts, much higher than those that used natural gas as fuel. Process economics calculations suggested that, when both SMR and rWGS were electrically heated, the process only showed product syngas cost parity with the conventional fuel heated design when electricity cost was ~$0.008/kWh. This suggests that CO 2 utilization scenarios involving process electrification need to be carefully considered from the total design perspective so they do not produce more greenhouse gases than in conventional non-electrified scenarios.

42 ENGINEERING↗

Long-term cyclability of Li 4 Ti 5 O 12 /LiMn 2 O 4 cells using carbonate-based electrolytes for behind-the-meter storage applications

Li 4 Ti 5 O 12 /LiMn 2 O 4 (LTO/LMO) chemistry was evaluated as a potential candidate for behind-the-meter storage (BTMS) applications. Its long-term cycle performance at 45 °C was tested using ethylene carbonate (EC) and propylene carbonate (PC) solvent electrolytes. Over 1000 cycles, LTO/LMO cells exhibited ~80% capacity retention and Coulombic efficiency higher than 99.96%. Electrochemical test results showed the major degradation mode of LTO/LMO cells arises from continuous electrolyte decomposition at the LTO anode and loss of Li inventory. EC and PC electrolytes created distinct surface layers, where the EC reduction products were more effective in passivating the LTO electrode surface. Dissolution and migration of Mn from the cathode was probed as Mn 2+ species distributed throughout the surface layer at the anode. By utilizing a prelithiated LTO electrode, the LTO/LMO cell performance was significantly enhanced with EC electrolyte. On the other hand, PC electrolyte resulted in accelerated electrolyte decomposition at the lithiated LTO surface due to the lack of surface passivation. Thus, mitigating parasitic reactions at the LTO electrode is the key to developing successful LTO/LMO cells.

25 ENERGY STORAGE↗

Long-life LiNi 0.5 Mn 1.5 O 4 /graphite lithium-ion cells with an artificial graphite-electrolyte interface

The high operating voltage of a spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode leads to electrolyte decomposition and accelerated deterioration of the electrode/electrolyte interface in lithium-ion cells. Aggressive side reactions prevent long-term cycling and hinder its practical application. Advanced characterization shows that the high-voltage operation makes the graphite anode react with the electrolyte, particularly with the lithium salt in the electrolyte, resulting in massive active lithium inventory loss and capacity fade. The side reactions at the graphite are identified as the main culprit for the LNMO/graphite full cell decay. Here, we demonstrate that an artificial solid-electrolyte interface layer consisting of an ultra-thin Al 2 O 3 film, generated via atomic layer deposition (ALD) at the graphite surface, can successfully isolate the graphite from the electrolyte and inhibit the undesired reactions. Consequently, the capacity and cycling stability of the LNMO/graphite cell are drastically improved. After 300 cycles, the capacity retention of LNMO/graphite cell increases from 57.7% to 98.6% with the ALD-coated graphite. Furthermore, our findings provide valuable insights into the LNMO/graphite cell degradation and suggest a simple and robust, yet highly effective, approach for the practical viability of high-voltage lithium-ion batteries.

25 ENERGY STORAGE↗

Noble gas insights into early impact delivery and volcanic outgassing to Earth's atmosphere: A limited role for the continental crust

Earth's atmosphere, crust and mantle have evolved together through continuous geochemical exchange throughout Earth's history. Constraints on the transport of volatile elements and compounds between these reservoirs are crucial for understanding how Earth could have stayed habitable for extended periods of time. In this work, we present a new forward model of He, Ne and Ar in the mantle, crust and atmosphere. We explore concentrations of noble gases at the end of accretion, bulk silicate Earth K/U ratios, crustal growth scenarios, and upper mantle processing rates throughout Earth's history. We search for parameter combinations that simultaneously satisfy observational constraints on present-day mantle 4 He/ 3 He and 40 Ar/ 36 Ar (sensitive to mantle outgassing and continental crust growth, which depletes the mantle of U, Th and K), atmospheric 20 Ne/ 22 Ne (which tracks the mix of outgassed vs. delivered Ne in the atmosphere), and atmospheric 40 Ar/ 36 Ar in the past and today (sensitive to volatile delivery, mantle outgassing and crustal growth). Leveraging this intertwined set of noble gas abundances and isotopic compositions yields new constraints on initial noble gas abundances in the mantle and on the proportions of atmospheric volatiles originating from delivery by impact degassing, mantle outgassing, and degassing of the continental crust. We find that atmospheric Ar isotopic evolution is primarily sensitive to the mantle processing rate history; the atmospheric Ar isotopic record should therefore not be used to reconstruct continental crust growth, but instead provides valuable insights into mantle processing rates. Our model predicts a measurably low 20 Ne/ 22 Ne ratio of ~9.7 in Archean atmospheric samples. Most of atmospheric primordial 36 Ar was directly delivered by chondritic bodies and not transferred to the atmosphere during an intense early episode of mantle outgassing. Nitrogen delivered by impact degassing could account for the present-day atmospheric nitrogen inventory.

58 GEOSCIENCES↗

Economic dispatch for electricity merchant with energy storage and wind plant: State of charge based decision making considering market impact and uncertainties

Here this paper investigates how the market impact of electricity merchants and uncertainty of wind generation affect their co-optimized scheduling policy, specifically for merchants who have both energy storage and wind plants. In the existing literature, merchants' trading actions are usually assumed not to affect market prices; however, a large-scale energy storage merchant's actions can affect market prices. To this end, we approximate the electricity price by a linear function of the quantity of power traded by the merchant in the reward function to achieve decision-making incorporating the market impact. This paper utilizes the dynamic programming approach to analyze merchants' optimal multi-period decision-making incorporating market impact, uncertain wind generation, and energy storage constraints. First, our results demonstrate that for a merchant with co-located energy storage facilities and wind power plants, the energy storage's feasible state of charge (SOC) range can be segmented into four possible sub-ranges by three analytically developed SOC reference points. The unique optimal trading decision can be achieved by comparing the current energy inventory and the SOC references of the next period. Second, our results show that market impact and uncertainties substantially change the optimal storage scheduling policy by impacting the values of the reference points. To mitigate the negative effect of the merchant's market impact on buying and selling actions, the merchant may reduce the amount of generating or pumping electricity each period to maximize profit. Moreover, we identify and investigate the trade-off between market price and transaction quantity. Our findings provide co-optimized scheduling guidance for electricity merchants with co-located energy storage and renewable power plants systems.

17 WIND ENERGY↗

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗

A simulation-based parametric study of CLOU chemical looping reactor performance

Chemical looping with oxygen uncoupling (CLOU) is a variant on chemical looping combustion in which the oxygen carrier releases gaseous O 2 in the fuel reactor, making it well-suited for solid fuels, since the released gaseous O 2 readily reacts with solid char. This work presents several computational fluid dynamic (CFD) simulations of copper-based CLOU in a dual fluidized bed system, each with different operating conditions. The modeling predicted that coal particle sizes as large as 1000 μm did not significantly affect performance. Increased oxygen carrier copper loading resulted in an excess of gaseous oxygen in the product gas stream. Decreasing the oxygen carrier bed mass as well as reducing the air reactor fluidizing velocity did not supply enough oxygen to the fuel reactor to complete combustion of the coal. This generated a failure state in which the temperature continued to decrease in the fuel reactor from the lack of combustion, which in turn reduced the O 2 equilibrium partial pressure, further lowering the amount of combustion possible. Sufficient O 2 can be maintained in the fuel reactor by ensuring a high enough air reactor velocity and a large enough supply of oxygen carrier inventory to handle the chosen coal feed rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Implementation and verification of PyNE R2S with DAG-OpenMC

The mesh-based Rigorous-Two-Step (R2S) method has been widely used in the accurate estimation of the shutdown dose rate (SDR) of fusion systems. Several mesh-based R2S code has been implemented based on Monte Carlo particle transport code MCNP5 or DAG-MCNP5 and inventory calculation code such as FISPACT-II, ALARA or ACAB. Recently, the OpenMC, a community-developed Monte Carlo particle transport code, implemented the photon particle transport capability, which enables OpenMC to be used in R2S. In this paper, PyNE R2S is extended with the support of DAG-OpenMC, i.e., OpenMC with DAGMC. Modifications that allow PyNE to read the flux result in the state point file of OpenMC has been implemented to PyNE R2S workflow. A custom source routine of OpenMC that reads the photon source file from PyNE R2S and sampling photon particle in OpenMC photon transport has been implemented in OpenMC. With these modifications, PyNE R2S is now capable of performing R2S calculations with both DAG-MCNP5 and DAG-OpenMC. The ITER FNG dose rate benchmark problem has been used to validate the code. The FNG neutron source has been modified for neutron transport with DAG-OpenMC. The shutdown dose rate of 19 cooling times has been calculated and compared with the experimental data and the computational results of other R2S codes. The results of PyNE R2S with DAG-OpenMC show satisfactory agreement with the experimental data and other computational results. Therefore, we consider PyNE R2S with DAG-OpenMC is a reliable code to calculate the SDR of fusion systems.

fusion↗

Toward a high-fidelity tritium transport modeling for retention and permeation experiments

We report Tritium Migration Analysis Program version 8 (TMAP8), the latest version of TMAP, was developed within the framework of the Multiphysics Object-Oriented Simulation Environment (MOOSE). Created at Idaho National Laboratory (INL), MOOSE is an open-source, dimension-agnostic, fully coupled, and fully implicit multiphysics platform featuring massively parallel computation capabilities. Using TMAP8, tritium transport in a divertor monoblock was analyzed to elucidate the effects of pulsed operation (up to fifty 1,600 s plasma discharge and cool-down cycles) on the tritium in-vessel inventory source term and ex-vessel release term (i.e., tritium retention and permeation) for safety analysis. With its built-in Message Passing Interface capability, TMAP8 can, in under 2 h, simulate tritium transport in three different layered materials (i.e., tungsten, copper, and copper-chromium-zirconium alloy) in 2D geometry, using a single device/computer with 10 cores. The MOOSE-based TMAP8 code can leverage other MOOSE tools developed under the Nuclear Energy Advanced Modeling and Simulation program to perform tritium and thermal transport in complex geometries and multiphysics environments. And via its massively parallel computation, MOOSE will enable the fusion pilot plant designers to conduct high-fidelity multiphysics modeling for the design of the divertor and blanket systems as well as for the safety analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Direct internal recycling fractions approaching unity

Direct internal recycling (DIR) refers to the process of recovering pure hydrogen isotopes (D/T) from helium and other impurities in the fusion plasma exhaust and directing them back to the fuel injection system. Increasing the exhaust fraction purified through DIR significantly reduces the size and cost of the tritium plant and provides additional benefits including reduced requirements for both the tritium startup inventory and tritium breeding ratio. Metal foil pumps (MFPs) are the dominant technology for this separation, relying on the concept of superpermeation. We recently demonstrated that PdCu foils operated at low temperature provide both exceptional flux and resilience to helium absorption as the DIR fraction is increased. Herein we design and demonstrate continuous and semi-batch DIR processes using PdCu MFPs. Under continuous processing, stable performance was observed for DIR fractions up to 92 %. In addition, we demonstrate a semi-batch process capable of extending the DIR fraction to unity (> 99.8 %). Under the experimental conditions described within a PdCu MFP area of ~22 m 2 would be sufficient to process the fusion exhaust with 92 % DIR fraction at expected flowrates of 100 Pa·m 3 ·s -1 for a future fusion power plant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗