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DOE OSTI2024

Analytical Tools to Assess Polymer Biodegradation: A Critical Review and Recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer’s properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Colachis, Matthew↗

DOE OSTI2021

Transverse mode analysis for free-space laser beams using Bayesian analysis

Reliable and rapid assessment of the transverse mode quality of a free-space laser beam has a wide range of applications in laser development, research, and utilization. It has become even more important with recent advances in developing orbital angular momentum photon beams across a broad spectral region. In this work, a general modal analysis method for a free-space multimode laser beam has been developed based on Bayesian analysis. After transforming mode decomposition into a linear system problem, a Gaussian probabilistic model is used to find a closed-form solution. The method is found to be robust with the presence of Gaussian noise. Prior knowledge about the mode content can be incorporated into the method to improve the solution for situations when coherent disturbances or contamination are present in the laser beam. This method can be used to analyze the mode content for laser beams in different bases, such as Hermite–Gaussian (HG) modes and Laguerre–Gaussian (LG) modes. Three applications of this method are presented: a detailed modal analysis of the beam image from the incoherent intensity addition of HG modes and two examples of mode decomposition using the complex wavefront from the coherent superposition of HG and LG modes. The feasibility of this method is demonstrated using various simulation results. Based on digital images of a laser beam recorded without complex wavelength-limiting optics, in principle, this method can be used in a wide wavelength range from infrared to ultraviolet, and possibly x ray.

Liu, Peifan (ORCID:0000000273816153)↗

DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗

DOE OSTI2025

SigTime: Learning and Visually Explaining Time Series Signatures

Understanding and distinguishing temporal patterns in time series data is essential for scientific discovery and decision-making. For example, in biomedical research, uncovering meaningful patterns in physiological signals can improve diagnosis, risk assessment, and patient outcomes. However, existing methods for time series pattern discovery face major challenges, including high computational complexity, limited interpretability, and difficulty in capturing meaningful temporal structures. Here, to address these gaps, we introduce a novel learning framework that jointly trains two Transformer models using complementary time series representations: shapelet-based representations to capture localized temporal structures and traditional feature engineering to encode statistical properties. The learned shapelets serve as interpretable signatures that differentiate time series across classification labels. Additionally, we develop a visual analytics system—SigTime—with coordinated views to facilitate exploration of time series signatures from multiple perspectives, aiding in useful insights generation. We quantitatively evaluate our learning framework on eight publicly available datasets and one proprietary clinical dataset. Additionally, we demonstrate the effectiveness of our system through two usage scenarios along with the domain experts: one involving public ECG data and the other focused on preterm labor analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Assessment of frequency and amplitude dependence on the cyclic degradation of polyurethane foams

Many energy absorption applications utilize flexible polymeric foams for their viscoelastic properties. It is desired that the material will perform consistently across repeated compression cycles. This study examines the effect of fatigue at low strain rates on the viscoelasticity of open-cell polyurethane foam. Six polyurethanes of the same base composition with two porosities (70% and 80%) and three chemical indexes (79i, 100i, and 121i) are tested. Large deformation cyclic compression of the foams is conducted on a universal testing system (UTS). These data are then post-processed leveraging dynamic mechanical analysis Fourier transform rheology to characterize changes in the viscoelasticity of the materials over fatigue cycles. Results show that foams can increase or decrease in stiffness up to 10% over 10 4 cycles. Specifically, higher chemical index, higher excitation frequency, and larger excitation amplitude correlate with a more pronounced decrease in stiffness. Damping can also change by 15% and correlates with chemical index and excitation frequency. Consequently, the findings suggest that internal foam structure and bulk material properties as well as applied loading parameters affect the viscoelastic fatigue response of flexible polymeric foams.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Microstructure and properties of a high temperature Al–Ce–Mn alloy produced by additive manufacturing

An Al–10Ce-8Mn (wt%) alloy was designed and fabricated by laser powder bed fusion additive manufacturing (AM). The rapid cooling rates of the AM process produced a refined microstructure with a large fraction of reinforcing intermetallic phases. The tensile properties of the alloy were characterized in the as-fabricated state and following thermal exposure. The properties of the as-fabricated microstructure showed exceptional high-temperature performance and strength retention at elevated temperatures up to 400 °C relative to benchmark wrought Al and AM Al alloy properties. Characterization of the microstructure and thermodynamic modeling of the ternary Al–Ce–Mn system rationalized the solidification and solid-state phase transformations. Finally, analysis of the relevant strengthening mechanisms for both the as-fabricated and thermally exposed conditions was performed.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Covalent Functionalization of Nickel Phosphide Nanocrystals with Aryl-Diazonium Salts

Covalent functionalization of Ni 2 P nanocrystals was demonstrated using aryl-diazonium salts. Spontaneous adsorption of aryl functional groups was observed, with surface coverages ranging from 20 to 96% depending on the native reactivity of the salt as determined by the aryl substitution pattern. Increased coverage was possible for low reactivity species using a sacrificial reductant. Functionalization was confirmed using thermogravimetric analysis, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy. The structure and energetics of this nanocrystal electrocatalyst system, as a function of ligand coverage, were explored with density functional theory calculations. The Hammett parameter of the surface functional group was found to linearly correlate with the change in Ni and P core-electron binding energies and the nanocrystal's experimentally and computationally determined work function. The electrocatalytic activity and stability of the functionalized nanocrystals for hydrogen evolution were also improved when compared to the unfunctionalized material, but a simple trend based on electrostatics was not evident. Density functional theory was used to understand this discrepancy, revealing that H adsorption energies on the covalently functionalized Ni 2 P also do not follow the electrostatic trend and are predictive descriptors of the experimental results.

14 SOLAR ENERGY↗

DOE OSTI2023

Comparison of the Chemical Composition of Liquids from the Pyrolysis and Hydrothermal Liquefaction of Lignocellulosic Materials

Major differences in thermal stability and hydrotreatment behavior of HTL and pyrolysis oils have been reported in the literature. However, little is known about the variations in the chemical composition of these oils that could explain such differences. Two commercial wood pyrolysis oils (Pyrovac and BTG), and their water-soluble (WS) and water-insoluble fractions (WIS) were analyzed and compared with the aqueous (WS WD-57 ) and oily (WIS WS-57 ) fractions obtained from hydrothermal liquefaction (HTL) of Douglas-fir. The samples were characterized by GC/MS, Karl Fischer titration, carbonyl content, total acid number, elemental composition, calorific value, proximate analysis, Fourier Transform Infrared Spectroscopy (FTIR), Folin-Ciocalteu (FC), and UV fluorescence. All the fractions were also analyzed by Fourier Transform Ion Cyclotron Resonance Mass Spectroscopy (FT-ICR-MS) and by Electrospray Ionization (EI). The most prevalent class of compounds in the water insoluble phases were phenols derived from lignin. Water-soluble phases contain mostly the oxygenated compounds derived from cellulose and hemicellulose and were richer in carbonyl functional groups. The water content of the resulting aqueous phases were between: 65 (WS BTG ) and 96 (WS Pyrovac ) wt. %. The bio-oil from BTG has higher water content and lower HHV, compared to Pyrovac oil. The GC/MS results of BTG oil show the presence of a more prominent acetic acid peak and higher TAN number than the Pyrovac oil. The GC/MS of Pyrovac oil showed more obvious mono-phenol peaks. The quantification of this family by Folin-Ciocalteu method confirmed higher content of monophenolic compounds compared with the BTG oil. The lower thermal stability of pyrolysis oils compared with HTL biocrudes can be partially explained by the fact that pyrolysis oils (BTG and Pyrovac) contain carbohydrates while HTL biocrude (WIS WD-57 ) doesn’t. Thus, we decided to further investigate the chemical differences between the phenolic rich fractions insoluble in water and the holocellulose derived compounds soluble in water. Even after water extraction, the acid content of the water insoluble fraction from BTG (WISBTG) was higher than the acid content of the water insoluble fraction obtained by HTL (WISWSD-57). Likewise, the acid content of the aqueous phases derived from pyrolysis oils (WS Pyrovac , WS BTG ) was also higher than for the aqueous phase obtained by HTL (WSWSD-57). This result is in part due to the use of bases in the HTL process that neutralizes the acid formed in that process. Moreover, the starting feedstock may also influence the differences between the oils. Although, the UV-Fluorescence spectra, ICR-MS and the EI analyses showed some minor differences in the molecular weight and chemical make-up of the oligomers soluble and insoluble in water from pyrolysis and HTL; the differences observed were not large enough to justify the differences in behavior between these oils reported in the literature. Our results suggest that the differences observed between HTL biocrudes and pyrolysis oils are likely partially due to the presence of holocellulose derived products in the pyrolysis oils and higher acid contents.

09 BIOMASS FUELS↗

DOE OSTI2020

Effect of the Ionic Liquid Structure on the Melt Processability of Polyacrylonitrile Fibers

The production of high-strength carbon fibers is an energy-intensive process, where a significant cost involves the wet or dry-spinning of polyacrylonitrile (PAN) fiber precursors. Melt-spinning PAN fibers would allow for significant reduction in the production cost and production hazards. Ionic liquids (ILs) are an attractive fiber-processing medium because of their negligible vapor pressure and low toxicity. In addition, they are carbon-forming precursors; upon carbonization, residual ILs can enhance the carbon yield, although primarily useful for plasticized melt-spinning of PAN precursor fibers. Here, we investigated the influence of the molecular structure of ILs and the control of plasticizing interactions with PAN during melt-spinning. The structural, thermal, and mechanical properties of the melt-spun PAN fibers were obtained by a combination of various characterization methods, such as differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, and mechanical testing. These results demonstrated that the IL structure and counteranions influence the PAN fiber formation. More specifically, ILs containing bromide counteranions produced PAN precursor fibers with increased mechanical properties compared to ILs containing chloride anions. Our research can provide a foundation to understand the influence of ILs on melt-spinning of PAN fibers and provides us the guidelines for a higher cost-/energy-efficient production of PAN-based carbon fibers.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Promoting Atomically Dispersed MnN 4 Sites via Sulfur Doping for Oxygen Reduction: Unveiling Intrinsic Activity and Degradation in Fuel Cells

Carbon supported and nitrogen coordinated single Mn site catalysts (Mn-N-C) catalysts are the most desirable platinum group metal (PGM)-free cathode catalysts for proton exchange membrane fuel cells (PEMFCs) due to their insignificant Fenton reactions (vs. Fe), earth abundances (vs. Co) and encouraging activity and stability. However, current Mn-N-C catalysts suffer from high over-potential due to low intrinsic activity and less dense MnN 4 sites. Herein, we present sulfur-doped Mn-N-C catalyst (Mn-N-C-S) synthesized through an effective adsorption-pyrolysis process. Using electron microscopy and X-ray absorption spectroscopy (XAS) techniques, we verify the uniform dispersion of MnN 4 sites and confirm the effect of S doping on the Mn-N coordination. The Mn-N-C-S catalyst exhibits a favorable oxygen reduction reaction (ORR) activity in acidic media relative to the S-free Mn-N-C catalyst. The corresponding membrane electrode assembly (MEA) generated a remarkable performance with a peak power density of 500 mW cm -2 under a realistic H 2 /air environment. The constant voltage tests of fuel cells confirm the much-enhanced stability of the Mn-N-C-S catalyst compared to the Fe-N-C and Fe-N-C-S catalysts. The electron microscopy and Fourier transform XAS analysis provide insights into catalyst degradation associated with Mn oxidation and agglomeration. The theoretical calculation elucidates that the promoted ORR activity is mainly attributed to the spatial effect stemmed from the repulsive interaction between the ORR intermediates and adjacent S do-pants.

25 ENERGY STORAGE↗

DOE OSTI2023

Revisiting Interior Water Mass Responses to Surface Forcing Changes and the Subsequent Effects on Overturning in the Southern Ocean

Abstract Two coupled climate models, differing primarily in horizontal resolution and treatment of mesoscale eddies, were used to assess the impact of perturbations in wind stress and Antarctic ice sheet (AIS) melting on the Southern Ocean meridional overturning circulation (SO MOC), which plays an important role in global climate regulation. The largest impact is found in the SO MOC lower limb, associated with the formation of Antarctic Bottom Water (AABW), which in both models is enhanced by wind and weakened by AIS meltwater perturbations. Even though both models under the AIS melting perturbation show similar AABW transport reductions of 4–5 Sv (50%–60%), the volume deflation of AABW south of 30°S is four times greater in the higher resolution simulation (−20 vs. −5 Sv). Water mass transformation (WMT) analysis reveals that surface‐forced dense water formation on the Antarctic shelf is absent in the higher resolution and reduced by half in the lower resolution model in response to the increased AIS melting. However, the decline of the AABW volume (and its inter‐model difference) far exceeds the surface‐forced WMT changes alone, which indicates that the divergent model responses arise from interactions between changes in surface forcing and interior mixing processes. This model divergence demonstrates an important source of uncertainty in climate modeling, and indicates that accurate shelf processes together with scenarios accounting for AIS melting are necessary for robust projections of the deep ocean's response to anthropogenic forcing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Experimental and theoretical evidence for hydrogen doping in polymer solution-processed indium gallium oxide

The field-effect electron mobility of aqueous solution-processed indium gallium oxide (IGO) thin-film transistors (TFTs) is significantly enhanced by polyvinyl alcohol (PVA) addition to the precursor solution, a >70-fold increase to 7.9 cm 2 /Vs. To understand the origin of this remarkable phenomenon, microstructure, electronic structure, and charge transport of IGO:PVA film are investigated by a battery of experimental and theoretical techniques, including In K-edge and Ga K-edge extended X-ray absorption fine structure (EXAFS); resonant soft X-ray scattering (R-SoXS); ultraviolet photoelectron spectroscopy (UPS); Fourier transform-infrared (FT-IR) spectroscopy; time-of-flight secondary-ion mass spectrometry (ToF-SIMS); composition-/processing-dependent TFT properties; high-resolution solid-state 1 H, 71 Ga, and 115 In NMR spectroscopy; and discrete Fourier transform (DFT) analysis with ab initio molecular dynamics (MD) liquid-quench simulations. The 71 Ga{ 1 H} rotational-echo double-resonance (REDOR) NMR and other data indicate that PVA achieves optimal H doping with a Ga···H distance of ~3.4 Å and conversion from six- to four-coordinate Ga, which together suppress deep trap defect localization. This reduces metal-oxide polyhedral distortion, thereby increasing the electron mobility. Finally, hydroxyl polymer doping thus offers a pathway for efficient H doping in green solvent-processed metal oxide films and the promise of high-performance, ultra-stable metal oxide semiconductor electronics with simple binary compositions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Field-Aged Glass/Backsheet and Glass/Glass PV Modules: Encapsulant Degradation Comparison

Ethylene vinyl acetate (EVA) is the predominant encapsulant in crystalline-silicon photovoltaic (PV) modules; however, its degradation is a subject of major concern, which causes significant power loss under field conditions. This article presents a comparison of EVA degradation in field-aged PV modules with glass/backsheet (G/B) and glass/glass (G/G) architectures. Modulelevel characterization included UV fluorescence imaging and I-V measurements. Material analytical techniques, including colorimetry, differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, and Raman spectroscopy, were performed to correlate the module performance parameters with EVA material properties. An intense EVA discoloration in G/G modules was observed, which was corroborated by higher module Isc and Pmax degradation rates compared with its counterpart G/B modules. Higher power degradation was accompanied by a significant increase in EVA crosslinking, vinyl acetate content, yellowness index, and presence of functional groups containing unsaturated moieties that are linked to degradation products of photothermal reaction, and a higher decrease in the degree of crystallinity. The absence of a polymeric backsheet in hermetically sealed G/G modules, which restricts photobleaching and enhances the entrapment of volatile acetic acid and other degradation by-products, plays a major role in causing higher EVA degradation in G/G modules. This article concludes that EVA might have been a good choice of an encapsulant for the G/B modules over the decades, but it may prove to be an inappropriate choice for the G/G modules because of potential degassing, corrosion, and/or discoloration issues. Ionomers or polyester-based encapsulants like polyolefins could be best suited for G/G modules as it appears to be a current trend in the industry.

14 SOLAR ENERGY↗

DOE OSTI2022

Capability to Process and Characterize Uranium-Zirconium (U-Zr) and Uranium-Zirconium-Plutonium (U-Zr-Pu) Alloys

This work investigated co-reduction of anhydrous compounds of uranium, zirconium, and plutonium to produce uranium rich ternary nuclear fuel alloys. Metallothermic co-reduction is a novel method to produce all-metal nuclear fuels. Metal fuels offer thermal, fissility, compatibility, and security benefits over oxide fuels. Alloys of uranium–10% zirconium with plutonium contents of 0%, 2.5%, 5%, and 10% were produced, with yields of 60–85% of theoretical values in a traditional calciothermic bomb reduction apparatus. Microstructural analysis indicated transformation of uranium phase from gamma to beta and then alpha, in alternating lamellar plates typical of alpha phase uranium and delta phase uranium-zirconium, with zirconium and carbides at prior grain boundaries. Some of the analyses were inconclusive in their results and therefore require additional testing. Successful ternary co-reduction would simplify production of homogeneous feedstock and thereby streamline manufacture of homogeneous ternary metallic fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Digital Twin and Cybersecurity Requirements for Beartooth

This report summarizes the requirements for the Cybersecurity and the Digital Twin for Beartooth. The Beartooth digital twin will ultimately allow for both comprehensive offline data analysis and transformational autonomy. This document places limits on the IPL-funded work scope to end at a predictive digital twin stage but allow for future expansion to support full autonomy. It is expected that this work will support both currently funded LDRD and future direct-funded digital twin research.

42 ENGINEERING↗

DOE OSTI2024

Mathematical methods for optimal polynomial recovery of high-dimensional systems from noisy data

The goal of our Early Career Research Project (ECRP) is to establish a modern mathematical foundation that will enable next-generation computational methods for polynomial approximation of high-dimensional systems, having a certain set of constraints, from a limited amount of noisy data. Such a foundation is critical to realizing the future potential of the DOE user facilities, and will ultimately empower scientists to address a fundamental question, namely, “how many realizations of a nonlinear manifold are required to recover the entire high-dimensional solution map, with optimal approximation guarantees and minimal computational cost?” The central theme of this effort aims to conquer this challenge by pioneering the development of extraordinarily innovative theoretical analysis and transformational non-intrusive computational methodologies. Such approaches will enable the reconstruction of the entire high-dimensional solution map, with accuracy comparable to the best approximation, while utilizing an optimal number of samples. During this reporting period we have made significant progress on four thrusts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Riverine organic matter functional diversity increases with catchment size

A large amount of dissolved organic matter (DOM) is transported to the ocean from terrestrial inputs each year (~0.95 Pg C per year) and undergoes a series of abiotic and biotic reactions, causing a significant release of CO 2 . Combined, these reactions result in variable DOM characteristics (e.g., nominal oxidation state of carbon, double-bond equivalents, chemodiversity) which have demonstrated impacts on biogeochemistry and ecosystem function. Despite this importance, however, comparatively few studies focus on the drivers for DOM chemodiversity along a riverine continuum. Here, we characterized DOM within samples collected from a stream network in the Yakima River Basin using ultrahigh-resolution mass spectrometry (i.e., FTICR-MS). To link DOM chemistry to potential function, we identified putative biochemical transformations within each sample. We also used various molecular characteristics (e.g., thermodynamic favorability, degradability) to calculate a series of functional diversity metrics. We observed that the diversity of biochemical transformations increased with increasing upstream catchment area and landcover. This increase was also connected to expanding functional diversity of the molecular formula. This pattern suggests that as molecular formulas become more diverse in thermodynamics or degradability, there is increased opportunity for biochemical transformations, potentially creating a self-reinforcing cycle where transformations in turn increase diversity and diversity increase transformations. We also observed that these patterns are, in part, connected to landcover whereby the occurrence of many landcover types (e.g., agriculture, urban, forest, shrub) could expand DOM functional diversity. For example, we observed that a novel functional diversity metric measuring similarity to common freshwater molecular formulas (i.e., carboxyl-rich alicyclic molecules) was significantly related to urban coverage. These results show that DOM diversity does not decrease along stream networks, as predicted by a common conceptual model known as the River Continuum Concept, but rather are influenced by the thermodynamic and degradation potential of molecular formula within the DOM, as well as landcover patterns.

54 ENVIRONMENTAL SCIENCES↗