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DOE OSTI2024

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Energetic considerations for engineering novel biochemistries in photosynthetic organisms

Humans have been harnessing biology to make valuable compounds for generations. From beer and biofuels to pharmaceuticals, biology provides an efficient alternative to industrial processes. With the continuing advancement of molecular tools to genetically modify organisms, biotechnology is poised to solve urgent global problems related to environment, increasing population, and public health. However, the light dependent reactions of photosynthesis are constrained to produce a fixed stoichiometry of ATP and reducing equivalents that may not match the newly introduced synthetic metabolism, leading to inefficiency or damage. While photosynthetic organisms have evolved several ways to modify the ATP/NADPH output from their thylakoid electron transport chain, it is unknown if the native energy balancing mechanisms grant enough flexibility to match the demands of the synthetic metabolism. In this review we discuss the role of photosynthesis in the biotech industry, and the energetic considerations of using photosynthesis to power synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Saprotrophic Fungus Induces Microscale Mineral Weathering to Source Potassium in a Carbon-Limited Environment

Plants rely on potassium for many critical biological processes, but most soils are potassium limited. Moving potassium from the inaccessible, mineral-bound pool to a more bioavailable form is crucial for sustainably increasing local potassium concentrations for plant growth and health. Here, we use a synthetic soil habitat (mineral doped micromodels) to study and directly visualize how the saprotrophic fungus, Fusarium sp. DS 682, weathers K-rich soil minerals. After 30 days of fungal growth, both montmorillonite and illite (secondary clays) had formed as surface coatings on primary K-feldspar, biotite, and kaolinite grains. The distribution of montmorillonite differed depending on the proximity to a carbon source, where montmorillonite was found to be associated with K-feldspar closer to the carbon (C) source, which the fungus was inoculated on, but associated with biotite at greater distances from the C source. The distribution of secondary clays is likely due to a change in the type of fungal exuded organic acids; from citric to tartaric acid dominated production with increasing distance from the C source. Thus, the main control on the ability of Fusarium sp. DS 682 to weather K-feldspar is proximity to a C source to produce citric acid via the TCA cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Non-additive microbial community responses to environmental complexity

Environmental composition is a major, though poorly understood, determinant of microbiome dynamics. Here we ask whether general principles govern how microbial community growth yield and diversity scale with an increasing number of environmental molecules. By assembling hundreds of synthetic consortia in vitro, we find that growth yield can remain constant or increase in a non-additive manner with environmental complexity. Conversely, taxonomic diversity is often much lower than expected. To better understand these deviations, we formulate metrics for epistatic interactions between environments and use them to compare our results to communities simulated with experimentally-parametrized consumer resource models. We find that key metabolic and ecological factors, including species similarity, degree of specialization, and metabolic interactions, modulate the observed non-additivity and govern the response of communities to combinations of resource pools. Our results demonstrate that environmental complexity alone is not sufficient for maintaining community diversity, and provide practical guidance for designing and controlling microbial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Design and Implementation of Full-Scale Industrial Control System Test Bed for Assessing Cyber-Security Defenses

In response to the increasing awareness of the Ethernet-based threat surface of industrial control systems (ICS), both the research and commercial communities are responding with ICS-specific security solutions. Unfortunately, many of the properties of ICS environments that contribute to the extent of this threat surface (e.g. age of devices, inability or unwillingness to patch, criticality of the system) similarly prevent the proper testing and evaluation of these security solutions. Production environments are often too fragile to introduce unvetted technology and most organizations lack test environments that are sufficiently consistent with production to yield actionable results. Cost and space requirements prevent the creation of mirrored physical environments leading many to look towards simulation or virtualization. Examples in literature provide various approaches to building ICS test beds, though most of these suffer from a lack of realism due to contrived scenarios, synthetic data and other compromises. In this paper, we provide a design methodology for building highly realistic ICS test beds for validating cybersecurity defenses. We then apply that methodology to the design and building of a specific test bed and describe the results and experimental use cases.

Gillen, Rob↗
DOE OSTI2020

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Non-Fermi Liquids from Kinetic Constraints in Tilted Optical Lattices

Here we study Fermi-Hubbard models with kinetically constrained dynamics that conserves both total particle number and total center of mass, a situation that arises when interacting fermions are placed in strongly tilted optical lattices. Through a combination of analytics and numerics, we show how the kinetic constraints stabilize an exotic non-Fermi liquid phase described by fermions coupled to a gapless bosonic field, which in several respects mimics a dynamical gauge field. This offers a novel route towards the study of non-Fermi liquid phases in the precision environments afforded by ultracold atom platforms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Biotechnological advances in algae-based foods: applications in nutrition and microbiome health

Algae are a sustainable, nutrient-rich resource with growing potential in food biotechnology. Their ability to thrive in diverse environments makes them a promising alternative to conventional crops. Rich in proteins, essential fatty acids, and bioactive compounds, algae support the development of functional foods, including plant-based meat and seafood alternatives. Advances in synthetic biology and fermentation have enhanced algal nutrient profiles and enabled novel applications. Algae-derived polysaccharides, such as alginate, fucoidan, laminarin, and porphyran, exhibit prebiotic effects by modulating the gut microbiota and promoting SCFA production. Enzymatic hydrolysis efficiently produces bioactive oligosaccharides, while engineered microbial systems support scalable production. Algae also enable synbiotic food development by serving as both prebiotic substrates and probiotic carriers.

Yu, Sora↗
DOE OSTI2022

Effect of network connectivity on behavior of synthetic Broborg hillfort glasses

There is wide industrial interest in developing robust models of long-term (>100 years) glass durability. Archeological glass analogs, glasses of similar composition, and alteration conditions to those being tested for durability can be used to evaluate and inform such models. Two such analog glasses from a 1500-year-old vitrified hillfort near Uppsala, Sweden have previously been identified as potential analogs for low concentration Fe-bearing aluminosilicate nuclear waste glasses. However, open questions remain regarding the melting environment from which these historic glasses were formed and the effect of these conditions on their chemical durability. A key factor to answering the previous melting and durability questions is the redox state of Fe in the starting and final materials. Past work has shown that the melting conditions of a glass-forming melt may influence the redox ratio value (Fe +3 /ΣFe), a measure of a glass's redox state, and both melting conditions and the redox ratio may influence the glass alteration behavior. Synthetic analogs of the hillfort glasses have been produced using either fully oxidized or reduced Fe precursors to address this question. In this study, the melting behavior, glass transition temperature, oxidation state, network structure, and chemical durability of these synthesized glass analogs is presented. Resulting data suggests that the degree of network connectivity as impacted by the oxidation state of iron impacted the behavior of the glass-forming melt but in this case does not affect the chemical durability of the final glass. Glasses with a lower degree of melt connectivity were found to have a lower viscosity, resulting in a lower glass transition temperature and softening temperature, as well as in a lower temperature of foam onset and temperature of foam maximum. This lower degree of network connectivity most likely played a more significant role in accelerating the conversion of batch chemicals into glass than the presence of water vapor in the furnace's atmosphere. Future work will focus on using the results from this work with outcomes from other aspects of this project to evaluate long-term glass alteration models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enhanced Iodine Capture Using a Postsynthetically Modified Thione–Silver Zeolitic Imidazole Framework

Efficient management of radionuclides that are released from various processes in the nuclear fuel cycle is of significant importance. Among these nuclides, radioactive iodine (mainly 129 I and 131 I) is a major concern due to the risk it poses to the environment and to human health; thus, the development of materials that can capture and safely store radioactive iodine is crucial. Herein, a novel silver-thione-functionalized zeolitic imidazole framework (ZIF) was synthesized via post-synthetic modification and assessed for its iodine uptake capabilities alongside the parent ZIF-8 and intermediate materials. A solvent-assisted ligand exchange procedure was used to replace the 2-methylimidazole linkers in ZIF-8 with 2-mercaptoimidazole, forming the intermediate compound ZIF-8=S, which was reacted with AgNO 3 to yield the ZIF-8=S-Ag + composite for iodine uptake. Despite possessing the lowest BET surface area of the derivatives, the Ag-functionalized material demonstrated superior I 2 adsorption in terms of both maximum capacity (550 g I 2 /mol) and rapid kinetics (50% loading achieved in 5 hrs, saturation in 50 hrs) compared to our pristine ZIF-8, which reached 450 g I 2 /mol after 150 hours and 50% loading in 25 hours. This improvement is attributed to the presence of the Ag + ions, which provide a strong chemical driving force to form stable Ag-I species. In conclusion, the results of this study contribute to a broader understanding of the strategies that can be employed to engineer adsorbents with robust iodine uptake behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Molecular speciation controls arsenic and lead bioaccessibility in fugitive dusts from sulfidic mine tailings

Communities nearby mine wastes in arid and semi-arid regions are potentially exposed to high concentrations of toxic metal(loid)s from fugitive dusts deriving from impoundments. To assess the relation between potentially lofted particles and human health risk, we studied the relationship between pharmacokinetic bioaccessibility and metal(loid) molecular speciation for mine tailings dust particulate matter (PM), with elevated levels of arsenic and lead (up to 59 and 34 mmol kg -1 , respectively), by coupling in vitro bioassay (IVBA) with X-ray absorption spectroscopy (XAS). Mine tailing efflorescent salts (PM ES ) and PM from the surface crust (0–1 cm, PM SC ) and near surface (0–25 cm) were isolated to <10 μm and <150 μm effective spherical diameter (PM 10 and PM 150 ) and reacted with synthetic gastric and lung fluid for 30 s to 100 h to investigate toxic metal(loid) release kinetics. Bioaccessible (BAc) fractions of arsenic and lead were about 10 and 100 times greater in gastric than in lung fluid simulant, respectively, and 10–100% of the maximum gastric BAc from PM 10 and PM 150 occurred within 30 s, with parabolic dissolution of fine, highly-reactive particles followed by slower release from less soluble sources. Evaporite salts were almost completely solubilized in gastric-fluid simulants. Arsenate within jarosite and sorbed to ferrihydrite, and lead from anglesite, were identified by XAS as the principal contaminant sources in the near surface tailings. In the synthetic lung fluid, arsenic was released continuously to 100 h, suggesting that residence time in vivo must be considered for risk determination. Analysis of pre- and post-IVBA PM indicated the release of arsenic in lung fluid was principally from arsenic-substituted jarosite, whereas in synthetic gastric fluid arsenic complexed on ferrihydrite surfaces was preferentially released and subsequently repartitioned to jarosite-like coordination at extended exposures. Lead dissolved at 30 s was subsequently repartitioned back to the solid phase as pyromorphite in phosphate rich lung fluid. The bioaccessibility of lead in surface tailings PM was limited due to robust sequestration in plumbojarosite. Kinetic release of toxic elements in both synthetic biofluids indicated that a single IVBA interval may not adequately describe release dynamics.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Impact of secondary salts, temperature, and pH on the colloidal stability of graphene oxide in water

The stability of graphene oxide (GO) in water is extremely relevant because of its application as an adsorbent material, as well as for its fate and behavior in the environment. Zeta potential was used to study the effect of secondary salts (carbonate, sulfate, and phosphate), temperature (20 to 60 °C), and pH (5 to 9) on the stability of six different GOs produced from natural, synthetic, and amorphous graphite—with and without the use of attrition milling. Generally, GOs produced with attrition-milled graphites had lower ζ-potentials than their unmilled counterparts because of their smaller particle sizes and higher concentration of oxygen-containing functional groups. It was observed that GO produced from graphite and synthetic graphite had ζ-potential values lower than –30 mV, even at 30 °C. However, it was observed that all the GOs studied were unstable in the presence of carbonate and sulfate salts at concentrations between 170 and 1695 mg L –1 , as they reached a ζ-potential of –4.1 mV. Density-functional theory electronic structure calculations suggested that the instability of GO in the presence of carbonate and sulfate was caused by the abstraction of a proton resulting in interaction energies E int of 28.3 and 168.9 kJ mol –1 , respectively. Our results suggest that temperatures above 30 °C, as well as carbonate and sulfate salts at concentrations relevant to arid and semi-arid regions, could promote the formation of agglomerates of GO, thus limiting its use and mobility in water.

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

Evidence that Criegee intermediates drive autoxidation in unsaturated lipids

Significance Autoxidation leads to the slow persistent destruction of organic molecules causing oxidative stress and associated disease. The prevailing autoxidation mechanism of unsaturated lipids involves chain reactions initiated and propagated by H-atom abstraction, mediated by peroxy radicals and other reactive oxygen species. Here we report experimental evidence for an autoxidation mechanism initiated by OH, which is unanticipated and proceeds by OH addition followed by pathways involving Criegee intermediates (CIs). Although CIs are routinely encountered in atmospheric and synthetic organic chemistry, their role in autoxidation is unexpected. Our results suggest that in all likelihood these exotic species play a much more prominent and general role in the chemistry of cells, food, petrochemicals, and the environment beyond what is currently believed.

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

Lipid sponge droplets as programmable synthetic organelles

Living cells segregate molecules and reactions in various subcellular compartments known as organelles. Spatial organization is likely essential for expanding the biochemical functions of synthetic reaction systems, including artificial cells. Many studies have attempted to mimic organelle functions using lamellar membrane-bound vesicles. However, vesicles typically suffer from highly limited transport across the membranes and an inability to mimic the dense membrane networks typically found in organelles such as the endoplasmic reticulum. Here, we describe programmable synthetic organelles based on highly stable nonlamellar sponge phase droplets that spontaneously assemble from a single-chain galactolipid and nonionic detergents. Due to their nanoporous structure, lipid sponge droplets readily exchange materials with the surrounding environment. In addition, the sponge phase contains a dense network of lipid bilayers and nanometric aqueous channels, which allows different classes of molecules to partition based on their size, polarity, and specific binding motifs. The sequestration of biologically relevant macromolecules can be programmed by the addition of suitably functionalized amphiphiles to the droplets. We demonstrate that droplets can harbor functional soluble and transmembrane proteins, allowing for the colocalization and concentration of enzymes and substrates to enhance reaction rates. Droplets protect bound proteins from proteases, and these interactions can be engineered to be reversible and optically controlled. Our results show that lipid sponge droplets permit the facile integration of membrane-rich environments and self-assembling spatial organization with biochemical reaction systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Adaptive Anomaly Detection for Dynamic Clinical Event Sequences

Over the past decade, health information technology (IT) has enabled the amount of digital information stored in electronic health records (EHRs) to expand greatly. However, according to some studies, hazards in health IT can lead to changes in clinical decisions, care processes, and care outcomes, as well as other issues. Thus, the effects of health IT hazards on patient safety have been at the forefront of recent patient safety research. Nonetheless, hazard detection in health IT remains a challenge. In this paper, the authors assume that safety-related issues in health IT would exhibit anomalous characteristics in EHR data. Although all hazards will exhibit some anomalous characteristics, not all anomalies can be regarded as hazards. The authors hypothesize that errors in health IT could lead to interruptions in the sequence of clinical actions. To this end, the problem of detecting anomalous sequences in big EHR data is considered. This paper focuses on dynamic event sequences, which are a series of clinical actions in motion. The authors propose an adaptive anomaly detection approach that uses higher-order network representation to detect anomalous sequences. Furthermore, the authors propose a contiguous subsequence anomaly detection approach that identifies abnormal subsequences in the detected anomalous sequences. The proposed approaches are tested by using synthetic and real-world EHR data. The proposed methods outperform existing state of the art anomaly detection techniques. To reduce the computational complexity associated with the operational implementation of the proposed approaches, the Apache Spark environment was leveraged, and a much shorter run time together with improved performance were achieved, especially for data with more than 60,000 sequences.

Niu, Haoran↗
DOE OSTI2022

Role of carboxysomes in cyanobacterial CO 2 assimilation: CO 2 concentrating mechanisms and metabolon implications

Many carbon-fixing organisms have evolved CO 2 concentrating mechanisms (CCMs) to enhance the delivery of CO 2 to RuBisCO, while minimizing reactions with the competitive inhibitor, molecular O 2 . These distinct types of CCMs have been extensively studied using genetics, biochemistry, cell imaging, mass spectrometry, and metabolic flux analysis. Highlighted in this paper, the cyanobacterial CCM features a bacterial microcompartment (BMC) called ‘carboxysome’ in which RuBisCO is co-encapsulated with the enzyme carbonic anhydrase (CA) within a semi-permeable protein shell. Further, the cyanobacterial CCM is capable of increasing CO 2 around RuBisCO, leading to one of the most efficient processes known for fixing ambient CO 2 . The carboxysome life cycle is dynamic and creates a unique subcellular environment that promotes activity of the Calvin–Benson (CB) cycle. The carboxysome may function within a larger cellular metabolon, physical association of functionally coupled proteins, to enhance metabolite channelling and carbon flux. In light of CCMs, synthetic biology approaches have been used to improve enzyme complex for CO 2 fixations. Research on CCM-associated metabolons has also inspired biologists to engineer multi-step pathways by providing anchoring points for enzyme cascades to channel intermediate metabolites towards valuable products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

X-ray absorption spectroscopy study of Mn reference compounds for Mn speciation in terrestrial surface environments

Abstract X-ray absorption spectroscopy (XAS) offers great potential to identify and quantify Mn species in surface environments by means of linear combination fit (LCF), fingerprint, and shell-fit analyses of bulk Mn XAS spectra. However, these approaches are complicated by the lack of a comprehensive and accessible spectrum library. Additionally, molecular-level information on Mn coordination in some potentially important Mn species occurring in soils and sediments is missing. Therefore, we investigated a suite of 32 natural and synthetic Mn reference compounds, including Mn oxide, oxyhydroxide, carbonate, phosphate, and silicate minerals, as well as organic and adsorbed Mn species, by Mn K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopy. The ability of XAS to infer the average oxidation state (AOS) of Mn was assessed by comparing XANES-derived AOS with the AOS obtained from redox titrations. All reference compounds were studied for their local (<5 Å) Mn coordination environment using EXAFS shell-fit analysis. Statistical analyses were employed to clarify how well and to what extent individual Mn species (groups) can be distinguished by XAS based on spectral uniqueness. Our results show that LCF analysis of normalized XANES spectra can reliably quantify the Mn AOS within ~0.1 v.u. in the range +2 to +4. These spectra are diagnostic for most Mn species investigated, but unsuitable to identify and quantify members of the manganate and Mn(III)-oxyhydroxide groups. First-derivative XANES fingerprinting allows the unique identification of pyrolusite, ramsdellite, and potentially lithiophorite within the manganate group. However, XANES spectra of individual Mn compounds can vary significantly depending on chemical composition and/or crystallinity, which limits the accuracy of XANES-based speciation analyses. In contrast, EXAFS spectra provide a much better discriminatory power to identify and quantify Mn species. Principal component and cluster analyses of k2-weighted EXAFS spectra of Mn reference compounds implied that EXAFS LCF analysis of environmental samples can identify and quantify at least the following primary Mn species groups: (1) Phyllo- and tectomanganates with large tunnel sizes (2 × 2 and larger; hollandite sensu stricto, romanèchite, todorokite); (2) tectomanganates with small tunnel sizes (2 × 2 and smaller; cryptomelane, pyrolusite, ramsdellite); (3) Mn(III)-dominated species (nesosilicates, oxyhydroxides, organic compounds, spinels); (4) Mn(II) species (carbonate, phosphate, and phyllosilicate minerals, adsorbed and organic species); and (5) manganosite. All Mn compounds, except for members of the manganate group (excluding pyrolusite) and adsorbed Mn(II) species, exhibit unique EXAFS spectra that would allow their identification and quantification in mixtures. Therefore, our results highlight the potential of Mn K-edge EXAFS spectroscopy to assess bulk Mn speciation in soils and sediments. A complete XAS-based speciation analysis of bulk Mn in environmental samples should preferably include the determination of Mn valences following the “Combo” method of Manceau et al. (2012), EXAFS LCF analyses based on principal component and target transformation results, as well as EXAFS shell-fit analyses for the validation of LCF results. For this purpose, all 32 XAS reference spectra are provided in the Online Materials1 for further use by the scientific community.

Geochemistry & Geophysics↗