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At least 577 records · Page 32

Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs

Accurate prediction of geothermal reservoir responses to alternative energy production scenarios is critical for optimizing the development of the underlying resources. While the conventional physics-based models offer a comprehensive prediction tool, data-driven models provide an efficient alternative to build fit-for-purpose predictive models by extracting and using the statistical patterns in the collected data to make predictions. The recurrent neural network (RNN) is a data-driven model that is commonly applied to predict time series sequences. This paper presents a variant of RNN that also utilizes the efficiency of convolutional neural networks (CNN) for the prediction of energy production from geothermal reservoirs. Specifically, a CNN–RNN architecture is developed that takes historical well controls as input (features) and their corresponding production response data as output (labels) to learn an input-output mapping that can predict the future well production responses/performance for any given future well control inputs. The model is paired with a labeling scheme to handle real field disturbances that create data gaps. In addition to the model structure, we introduce a thorough workflow for applying the model, which includes data pre-processing, feature selection, as well as different training strategies for short-term and long-term prediction. Finally, the performance and accuracy of the model are evaluated by applying it to multiple datasets, including a field reservoir model.

15 GEOTHERMAL ENERGY↗

A comparative study of multimodal data fusion strategies for planetary spectroscopy

Integrating heterogeneous data sources can improve scientific inference when different modalities capture complementary information, but doing so is challenging in high-dimensional, small-sample settings. In spectroscopy for planetary exploration, Laser-Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (Raman), Visible Infrared Spectroscopy (VISIR), and Mid-Infrared Spectroscopy (MIR) each examine different aspects of composition and mineralogy, raising fundamental questions about when and how data fusion improves predictive performance. Using a Mars-relevant set of geologic standards with measurements from all four modalities, we present a rigorous systematic evaluation of four data fusion strategies: low-level (data) fusion, mid-level (feature) fusion, high-level (decision) fusion, and residual-boosting (sequential) fusion. We assess performance in predicting oxide composition via nested cross-validation and corrected significance testing to evaluate whether data fusion improves upon single-modality baselines. We show that data fusion does not uniformly improve accuracy, and that observed gains are modest, oxide-dependent, and sensitive to modality and model structure. To move beyond aggregate accuracy metrics, we use model coefficients, permutation importance, and residual gain analysis to examine how the fusion models weight individual modalities and to identify patterns of apparent complementarity or redundancy. Though focused on spectroscopy for planetary exploration, our framework for data fusion evaluation and interpretation extends to other scientific domains with heterogeneous and scarce data and provides a principled approach evaluating data fusion strategies, interpreting modality contributions, and understanding tradeoffs among data fusion strategies.

97 MATHEMATICS AND COMPUTING↗

A Theory-Guided X-ray Absorption Spectroscopy Approach for Identifying Active Sites in Atomically Dispersed Transition-Metal Catalysts

Atomically dispersed supported metal catalysts offer new properties and the benefits of maximized metal accessibility and utilization. The characterization of these materials, however, remains challenging. Using atomically dispersed platinum supported on crystalline MgO (chosen for its well-defined bonding sites) as a prototypical example, we demonstrate in this work how systematic density functional theory calculations for assessing all the potentially stable platinum sites, combined with automated analysis of extended X-ray absorption fine structure (EXAFS) spectra, leads to unbiased identification of isolated, surface-enveloped platinum cations as the catalytic species for CO oxidation. The catalyst has been characterized by atomic-resolution imaging and EXAFS and high-energy resolution fluorescence detection X-ray absorption near edge spectroscopy. The proposed platinum sites are in agreement with experiment. This theory-guided workflow leads to rigorously determined structural models and provides a more detailed picture of the structure of the catalytically active site than what is currently possible with conventional EXAFS analyses. As this approach is efficient and agnostic to the metal, support, and catalytic reaction, we posit that it will be of broad interest to the materials characterization and catalysis communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploiting SMILEs and the CMIP5 Archive to Understand Arctic Climate Change Seasonality and Uncertainty

Arctic Amplification (AA) exhibits a distinct seasonal dependence; it is weakest in boreal summer and strongest in winter. Here, we analyze simulations from single-model initial-condition large ensembles and Coupled Model Intercomparison Project Phase 5 to decipher the seasonal evolution of Arctic climate change. Models agree that the annual maximum AA shifts from autumn into winter over the 21st century, accompanied by similar shifts in sea-ice loss and surface turbulent heat fluxes, whereas the maximum precipitation shifts only into late autumn. However, the exact seasonal timing and magnitude of these shifts are highly uncertain. Decomposing the uncertainty into model structural differences, emission scenarios, and internal variability reveals that model differences dominate the total uncertainty, which also undergo autumn-to-winter shifts. We also find that the scenario uncertainty is unimportant for projections of AA. These results highlight that understanding model differences is critical to reducing uncertainty in projected Arctic climate change.

54 ENVIRONMENTAL SCIENCES↗

Investigating the Global Biogeophysical Impact of Area and Mass Based Wood Harvest in a Vegetation Demography Model

Wood harvesting alters land surface properties and energy redistribution, but there is a lack of studies estimating these changes on a global scale. We coupled a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator, with the E3SM land model to perform offline model simulation to investigate the land biogeophysical responses, including canopy coverage, leaf area index, albedo, surface roughness length, and energy fluxes, to historical wood harvest on the global scale. In this study, we found 50% less harvested carbon (C) when choosing the area-based harvest rate as driving data that has not been spatially harmonized, compared to reharmonized mass-based harvesting. By considering the uncertainty from reconstruction of historical wood harvest time series and the choice of wood harvest approach in the model, continuous wood harvest (1850–2015) results in 5%–10% of canopy coverage loss, contributing 0.5%–1% increase of albedo over disturbed land, which is much stronger than a non-demographic land surface model. Changes in energy flux from the wood harvest are negligible (<1%), but the responses of land surface properties vary (up to 30%) due to differences in model structure between the single canopy, sun-shade leaf model and vegetation demographic model.

Shu, Shijie [Lawrence Berkeley National Laboratory↗

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes

Abstract The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

59 BASIC BIOLOGICAL SCIENCES↗

Instability of the topological surface state in Bi 2 Se 3 upon deposition of gold

Momentum-resolved photoemission spectroscopy indicates the instability of the Dirac surface state upon deposition of gold on the (0001) surface of the topological insulator Bi 2 Se 3 . Based on the structure model derived from extended x-ray absorption fine structure experiments showing that gold atoms substitute bismuth atoms, first-principles calculations provide evidence that a gap appears due to hybridization of the surface state with gold d states near the Fermi level. Here, our findings provide insights into the mechanisms affecting the stability of the surface state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of a Thin Film Primary Surface Heat Exchanger for Advanced Power Cycles

This project objective is to develop a high-temperature design upgrade for an existing primary surface heat exchanger so that the redesigned hardware is capable of operation in CO 2 at temperatures up to 1,510°F (821°C) and pressure differentials up to 130 psi (9 bar). The heat exchanger is proposed for use as a recuperator in an advanced low-pressure oxy-fuel Brayton cycle that is predicted to achieve over 50% thermodynamic efficiency, although the heat exchanger could also be used in other high-temperature, low-differential pressure cycles. This report describes the progress to date, which includes continuing work performed to select and test new candidate materials for the recuperator redesign, final mechanical and thermal performance analysis results of various redesign concepts, and the preliminary design of a test loop for the redesigned recuperator including a budgetary estimate for detailed test loop design, procurement, and test operation. A materials search was performed in order to investigate high-temperature properties of many candidate materials, including high-temperature strength and nickel content. These properties were used to rank the candidate materials, resulting in a reduced list of nine materials for corrosion testing. Multiple test rigs were considered and analyzed for short-term corrosion testing and Thermal Gravimetric Analysis (TGA) was selected as the most cost-effective option for evaluating corrosion resistance of the candidate materials. In addition, tantalum, niobium, and chromium coatings were identified as potential options for increased corrosion resistance. The test results show that many materials exhibit relatively low weight gain rates, and that niobium and tantalum coatings may improve corrosion resistance for many materials, while chromium coatings appear to oxidize and debond quickly. Metallurgical analysis of alloys was also performed, showing evidence of intergranular attack in 282 that may cause long-term reliability problems in CO 2 service at these temperatures. However, long-term testing in a flowing environment is recommended in order to understand accurately the severity of the attack. Detailed economic modeling of the existing air cycle recuperator and CO 2 cycle recuperator options was also completed, including costs for material, fabrication, fuel, maintenance, and operation. The analysis results show that the increased capital cost for high-temperature materials may be offset by higher cycle efficiencies, decreasing the overall lifetime cost of the system. The economic analysis also examines costs associated with increased pressure drop and material changes for two redesign options. These results show that, even with slightly reduced performance and/or higher material costs, the lifetime cost per energy production may still be reduced by over 12%. The existing recuperator design information was provided by Solar Turbines, Inc. via several models, drawings, and design handoff meetings. Multiple fluid/thermal and structural models were created in order to analyze critical recuperator performance and mechanical strength in critical areas throughout the redesign process. These models were analyzed for a baseline condition (consistent with current Mercury 50 operation) for validation purposes. Results are presented for heat transfer coefficients and pressure drops, matching well with the existing operational data. Simulation of higher-temperature CO 2 conditions was also performed, showing a slight expected increase in both heat transfer and pressure drop. Mechanical analysis results for critical areas on the cross-flow and counter-flow sheets have also been obtained for air and CO 2 cases. These results show similar stresses in both cases but significantly reduced safety factors for the CO 2 case due to reduced yield and creep rupture strengths of alloy 625 at the higher temperatures. A concept brainstorm session and initial down-selection were completed in order to identify promising redesign options for further analysis. Detailed analysis of all promising redesign options was performed via finite element and computational fluid dynamic simulations in order to characterize mechanical and thermal-fluid performance of each option. These options included material change, various sheet thickness configurations, pitch and phasing of cross-flow and counter-flow sheets, and separator sheets. The analysis results have identified two viable redesign options that maintain existing safety margins optimally through a material change to Haynes 282 and (A) sheet thickness increases of 40% on the counter-flow sheet and 75% on the hot side cross-flow corrugation sheet or (B) addition of a separator sheet in the counter-flow section while maintaining the original counter-flow sheet thickness and increasing the cross-flow corrugation sheet thickness by 90% to account for the increase in cell height. While both options satisfy mechanical stress constraints, the separator sheet design has a higher part count, slightly reduced heat transfer, and slightly higher pressure drop than the first option and is not preferred. Finally, several test loop concepts have been developed for different full-scale and reduced-scale recuperator testing options. For each option, various loop components, such as heat exchangers, valves, heaters, and compressors, were evaluated in an effort to maximize utilization of existing resources. All concepts utilize an existing 3-MW CO 2 compressor, heater, and loop coolers, but the concepts vary by incorporating different amounts of new equipment for achieving various flow rates (all concepts operate at design pressure and temperature). The third concept achieves a 1 kg/s test without purchasing any costly equipment (coolers, heaters, blowers, etc.). Since the stacked cell design of the recuperator results in the same flow conditions at each core cell (even for a reduced-scale test). Thus, test loop Concept #3 was selected for the preliminary design. This loop design is detailed within the report, culminating in a budgetary estimate of $1,013,000.00 for the detailed design, construction, commissioning, and operation of a high-temperature recuperator test loop.

03 NATURAL GAS↗

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

54 ENVIRONMENTAL SCIENCES↗

Focus: Two-dimensional electron-electron double resonance and molecular motions: The challenge of higher frequencies

The development, applications, and current challenges of the pulsed ESR technique of two-dimensional Electron-Electron Double Resonance (2D ELDOR) are described. This is a three-pulse technique akin to 2D Exchange Nuclear Magnetic Resonance, but involving electron spins, usually in the form of spin-probes or spin-labels. As a result, it required the extension to much higher frequencies, i.e., microwaves, and much faster time scales, with π/2 pulses in the 2-3 ns range. It has proven very useful for studying molecular dynamics in complex fluids, and spectral results can be explained by fitting theoretical models (also described) that provide a detailed analysis of the molecular dynamics and structure. We discuss concepts that also appear in other forms of 2D spectroscopy but emphasize the unique advantages and difficulties that are intrinsic to ESR. Advantages include the ability to tune the resonance frequency, in order to probe different motional ranges, while challenges include the high ratio of the detection dead time vs. the relaxation times. We review several important 2D ELDOR studies of molecular dynamics. (1) The results from a spin probe dissolved in a liquid crystal are followed throughout the isotropic → nematic → liquid-like smectic → solid-like smectic → crystalline phases as the temperature is reduced and are interpreted in terms of the slowly relaxing local structure model. Here, the labeled molecule is undergoing overall motion in the macroscopically aligned sample, as well as responding to local site fluctuations. (2) Several examples involving model phospholipid membranes are provided, including the dynamic structural characterization of the boundary lipid that coats a transmembrane peptide dimer. Additionally, subtle differences can be elicited for the phospholipid membrane phases: liquid disordered, liquid ordered, and gel, and the subtle effects upon the membrane, of antigen cross-linking of receptors on the surface of plasma membrane, vesicles can be observed. These 2D ELDOR experiments are performed as a function of mixing time, T{sub m}, i.e., the time between the second and third π/2 pulses, which provides a third dimension. In fact, a fourth dimension may be added by varying the ESR frequency/magnetic field combination. Therefore, (3) it is shown how continuous-wave multifrequency ESR studies enable the decomposition of complex dynamics of, e.g., proteins by virtue of their respective time scales. These studies motivate our current efforts that are directed to extend 2D ELDOR to higher frequencies, 95 GHz in particular (from 9 and 17 GHz), in order to enable multi-frequency 2D ELDOR. This required the development of quasi-optical methods for performing the mm-wave experiments, which are summarized. We demonstrate state-of-the-art 95 GHz 2D ELDOR spectroscopy through its ability to resolve the two signals from a spin probe dissolved in both the lipid phase and the coexisting aqueous phase. As current 95 GHz experiments are restricted by limited spectral coverage of the π/2 pulse, as well as the very short T{sub 2} relaxation times of the electron spins, we discuss how these limitations are being addressed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disordered crystal structure of 20H-AlON, Al{sub 10}O{sub 3}N{sub 8}

The disordered crystal structure of 20H-AlON (Al{sub 10}O{sub 3}N{sub 8}) was determined by combined use of X-ray powder diffraction and transmission electron microscopy. The title compound is hexagonal with space group P6{sub 3}/mmc (Z=2) and the unit-cell dimensions are a=0.307082(5) nm, c=5.29447(8) nm and V=0.432376(12) nm{sup 3}. The structural model showed the positional disordering of three of the six Al sites in the unit cell. The reliability indices calculated from the Rietveld method were R{sub wp}=6.97%, S (=R{sub wp}/R{sub e})=1.68, R{sub p}=5.45%, R{sub B}=5.13% and R{sub F}=4.56%. We interpreted the disordered structure of 20H-AlON as a statistical average of six different types of ordered structural configurations, which are composed of an octahedral [Al(O, N){sub 6}] layer and tetrahedral [Al(O, N){sub 4}] layers. We demonstrated the high correlations between the hexagonal unit-cell dimensions and the octahedral layer concentrations for AlON and SiAlON polytypoids. - Graphical abstract: Variations of a and c/(n{sub O}+n{sub T}) with n{sub O}/(n{sub O}+n{sub T}). The a and c are the hexagonal unit-cell dimensions of AlON, SiAlON and AlN. The n{sub O} and n{sub T} are, respectively, the numbers of octahedral and tetrahedral layers in the unit cells. The unit-cell dimensions in literature are plotted in black plus for AlON and black cross for SiAlON. The unit-cell dimensions of AlN are a=0.3110 nm and c=0.4980 nm. - Highlights: • Crystal structure of Al10O3N8 is determined by laboratory X-ray powder diffraction. • The atom arrangements are represented by the split-atom model. • Six types of ordered atom arrangements are derived from the disordered structure. • Hexagonal unit-cell dimensions changed systematically for AlON and SiAlON compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Domain Structures of Ni and NiFe (Oxy)Hydroxide Oxygen-Evolution Catalysts from X-ray Pair Distribution Function Analysis

Ni-Fe (oxy)hydroxides, Ni( i-z )Fe z O x H y , are among the fastest-known water oxidation catalysts in alkaline media on a per-cation basis. At current densities relevant for electrolysis (e.g., >0.5 A/cm( -2 )), mass and electron transport through catalyst films with high mass loading are critical and depend substantially on the extended and intermediate catalyst architecture. We use X-ray pair distribution function (PDF) analysis to determine the intermediate nanostructures of electrodeposited Ni( i-z )Fe z O x H y films. We report the effects of electrodeposition technique (pulsed versus continuous), electrochemical cycling, and Fe content on the structure of the catalyst film. The PDF patterns for Ni( i-z )Fe z O x H y films are best simulated by model structures consisting of brucite-like β-Ni(OH) 2 fragments 1 to 3 layers in thickness. Only the oxidation state of the film significantly affects the intralayer scattering behavior (i.e., metal-oxygen bond distance). The interlayer interactions, however, are affected by Fe content and deposition conditions. The domain size of many of the systems are similar, extending to similar to ~5 nm, which are best modeled by sheets containing upward of similar to ~250 metal cations. Smaller domains were found for films deposited through a larger number of electrochemical cathodic current pulses. Films can be cycled between as-deposited, oxidized, and reduced states, with minimal loss of intrasheet coherence, indicating a degree of structural stability. We estimate heterogeneity in the domain structures by modeling the PDF data to linear combinations of oxyhydroxide fragments with different sizes and numbers of layers.

36 MATERIALS SCIENCE↗

A first-principles based description of the Hf-Ni system supported by high-temperature synchrotron experiments

Hf-Ni is an important binary system for high temperature alloys and shape memory alloys which has been investigated several times in the literature but often using samples of Hf contaminated by Zr. The thermodynamics of this system are remodeled in this work based on first-principles calculations and additional experiments using Hf with relatively low Zr contamination (0.25 wt. %). Diffusion couples in the Ni-rich portion of the Hf-Ni system heat treated at 1173, 1273 and 1373 K are used to measure phase stability and Hf solubility in the fcc phase. The solubility observed in fcc Ni from Ni/Ni 50 Hf 50 (at.%) diffusion couples is larger than that observed in previous experiments. These results are the only source fit to during modeling of the fcc solubility to mitigate effects from Zr contamination. Data in the literature suggests that the high temperature crystal structure of the B33 NiHf phase is, in fact, the B2 structure. High temperature synchrotron measurements provide confirmation of this crystal structure. Modeling of the B2 phase was aided by first-principles calculations using special quasi-random structures (SQS). Finally, the present CALPHAD model will prove useful when designing shape memory alloys containing Hf and when modeling the Hf activity in Ni-base high temperature alloys.

36 MATERIALS SCIENCE↗

Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units

Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.

Wang, Hong↗

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by the observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.

54 ENVIRONMENTAL SCIENCES↗

In situ characterization of cofacial Co(IV) centers in Co 4 O 4 cubane: Modeling the high-valent active site in oxygen-evolving catalysts

The Co 4 O 4 cubane is a representative structural model of oxidic cobalt oxygen evolving catalysts (Co-OECs). The Co-OECs are active when residing at two oxidation levels above an all Co(III) resting state. This doubly oxidized Co(IV) 2 state may be captured in a Co(III) 2 (IV) 2 cubane. We demonstrate that the Co(III) 2 (IV) 2 cubane may be electrochemically generated and the electronic properties of this unique high-valent state may be probed by in situ spectroscopy. Intervalence charge transfer (IVCT) bands in the near-IR are observed for the Co(III) 2 (IV) 2 cubane, and spectroscopic analysis together with electrochemical kinetics measurements reveal a larger reorganization energy and a smaller electron transfer rate constant for the doubly versus singly oxidized cubane. Spectroelectrochemical X-ray absorption data further reveal systematic spectral changes with successive oxidations from the cubane resting state. Electronic structure calculations correlated to experimental data suggest that this state is best represented as a localized, antiferromagnetically coupled Co(IV) 2 dimer. The exchange coupling in the cofacial Co(IV) 2 site allows for parallels to be drawn between the electronic structure of the Co 4 O 4 cubane model system and the high valent active site of the Co-OEC, with specific emphasis on the manifestation of a doubly oxidized Co(IV) 2 center on O–O bond formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗