HelioCon: A roadmap for advanced heliostat technologies for concentrating solar power
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Zhu, Guangdong↗
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Hydrogen Infrastructure Analysis for the Port Applications [Slides]
The International Maritime Organization has committed to 50% reduction in GHG emissions by 2050 worldwide as of 2023. This analysis includes performing an inventory and modeling efforts to understand the energy, equipment and cost requirements to support decarbonization of cargo handling and shore power at U.S. Ports, along with assessment of zero- and near- zero emission fuel supplies at or near U.S. ports focused upon Hydrogen technologies. Initial market assessment for ocean going vessels for harbor support and ocean-going vessels is explored. An energy analysis is performed on the port system using a holistic approach and considering the port as an entire ecosystem that functions as a transportation and energy node. Presently, a comprehensive view is lacking for future analysis efforts, this analysis seeks to address this gap in data by evaluating four representative port types and the potential for utilizing hydrogen for the maritime industry. Every port is different, but broadly they could be bracketed into reference cases with scaling factors for the relative size of the port operations. These reference ports are for future use, potentially as baselines for analysis and development of demonstration programs. An equipment inventory for each reference port type (container, bulk, breakbulk, and inland waterway) is presented. A comparative analysis of fuel cell electric and battery electric equipment is conducted based on the following criteria: technology readiness level, refueling/charging time, operational range, energy consumption, and fuel cost savings compared to baseline internal combustion engine equipment. The tradeoffs and synergies between two alternative powertrains is highlighted. Based on energy and infrastructure analysis, average and high equipment utilization profiles across different port types is identified and quantified baseline fuel and electricity demand for various decarbonization scenarios. Based on the portfolio of equipment converted to fuel cell electric, the estimates of initial capital investment are provided for hydrogen refueling stations across ports. An energy demand model is developed that predicts well the all-electric cargo handling equipment annual energy consumption for ports with annual tonnage under 2 million twenty-foot equivalent units (TEUs). The model is a good rubric to follow for further energy demand models that can create a scalable solution to understand the energy needs of cargo handling equipment, whether they are all-electric, hydrogen fuel cell, or powered by another fuel-type. Zero and near-zero emission fuel supply at ports is evaluated looking into the characteristics of hydrogen, ammonia, and methanol as an alternative fuel, as well as the bunkering status. The readiness of reference ports to produce ammonia or methanol and bunker the fuel is examined based on the framework developed by the Global Maritime Forum and Rocky Mountain Institute.
08 HYDROGEN↗
Electronic Structure of Molecular Cobalt Catalysts for H 2 Production Revealed by Multifrequency EPR
Improving the design of hydrogen evolution reaction (HER) catalysts requires a detailed understanding of the catalyst's structure and environment. Here wwe have used multifrequency electron paramagnetic resonance (EPR) spectroscopy (X-band, Q-band, and D-band) in combination with density functional theory (DFT) modeling to elucidate the electronic structure of three Co(II) molecular catalysts for H 2 evolution to determine correlations of electronic structure parameters with catalytic activity and stability. The Co(II) coordination complexes investigated here are representative of two types of H 2 -evolving molecular catalysts: cobaloximes, formed from cobalt coordination to two glyoxime ligands, and cobalt poly(pyridyl) complexes, which commonly have either four or five pyridyl ligands coordinating a single Co(II) ion. These Co(II) complexes were studied in a variety of solvents with a range of polarities and stoichiometric amounts of potential ligands to the cobalt ion to assess the strength and nature of ligand- cobalt interactions. Using magnetic resonance parameters obtained by EPR spectroscopy as reference data, we reconstructed the electronic structure of the Co(II) complexes with the help of DFT modeling. For all three catalysts, we uncovered a linear correlation between the Co(II) A z value and the g x value that is dependent on the strength of the axial ligands. The correlations that we have established between the electronic structure and metal coordination environment provide insight into the structural and electronic factors underpinning the observed trends in HER catalysis activity.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Hydrogen interaction kinetics of Ge dangling bonds at the Si{sub 0.25}Ge{sub 0.75}/SiO{sub 2} interface
The hydrogen interaction kinetics of the GeP{sub b1} defect, previously identified by electron spin resonance (ESR) as an interfacial Ge dangling bond (DB) defect occurring in densities ∼7 × 10{sup 12} cm{sup −2} at the SiGe/SiO{sub 2} interfaces of condensation grown (100)Si/a-SiO{sub 2}/Ge{sub 0.75}Si{sub 0.25}/a-SiO{sub 2} structures, has been studied as function of temperature. This has been carried out, both in the isothermal and isochronal mode, through defect monitoring by capacitance-voltage measurements in conjunction with ESR probing, where it has previously been demonstrated the defects to operate as negative charge traps. The work entails a full interaction cycle study, comprised of analysis of both defect passivation (pictured as GeP{sub b1}-H formation) in molecular hydrogen (∼1 atm) and reactivation (GeP{sub b1}-H dissociation) in vacuum. It is found that both processes can be suitably described separately by the generalized simple thermal (GST) model, embodying a first order interaction kinetics description based on the basic chemical reactions GeP{sub b1} + H{sub 2} → GeP{sub b1}H + H and GeP{sub b1}H → GeP{sub b1} + H, which are found to be characterized by the average activation energies E{sub f} = 1.44 ± 0.04 eV and E{sub d} = 2.23 ± 0.04 eV, and attendant, assumedly Gaussian, spreads σE{sub f} = 0.20 ± 0.02 eV and σE{sub d} = 0.15 ± 0.02 eV, respectively. The substantial spreads refer to enhanced interfacial disorder. Combination of the separately inferred kinetic parameters for passivation and dissociation results in the unified realistic GST description that incorporates the simultaneous competing action of passivation and dissociation, and which is found to excellently account for the full cycle data. For process times t{sub a} ∼ 35 min, it is found that even for the optimum treatment temperature ∼380 °C, only ∼60% of the GeP{sub b1} system can be electrically silenced, still far remote from device grade level. This ineffectiveness is concluded, for the major part, to be a direct consequence of the excessive spreads in the activation energies, ∼2–3 times larger than for the Si DB P{sub b} defects at the standard thermal (111)Si/SiO{sub 2} interface which may be easily passivated to device grade levels, strengthened by the reduced difference between the average E{sub f} and E{sub d} values. Exploring the guidelines of the GST model indicates that passivation can be improved by decreasing T{sub an} and attendant enlarging of t{sub a}, however, at best still leaving ∼2% defects unpassivated even for unrealistically extended anneal times. The average dissociation energy E{sub d} ∼ 2.23 eV, concluded as representing the GeP{sub b1}-H bond strength, is found to be smaller than the SiP{sub b}-H one, characterized by E{sub d} ∼ 2.83 eV. An energy deficiency is encountered regarding the energy sum rule inherent to the GST-model, the origin of which is substantiated to lie with a more complex nature of the forward passivation process than basically depicted in the GST model. The results are discussed within the context of theoretical considerations on the passivation of interfacial Ge DBs by hydrogen.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
ORNL_AISD_NiNb
This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.
36 MATERIALS SCIENCE↗
Multidimensional dosimetry of {sup 106}Ru eye plaques using EBT3 films and its impact on treatment planning
Purpose: The purpose of this study was to establish a method to perform multidimensional radiochromic film measurements of {sup 106}Ru plaques and to benchmark the resulting dose distributions against Monte Carlo simulations (MC), microdiamond, and diode measurements. Methods: Absolute dose rates and relative dose distributions in multiple planes were determined for three different plaque models (CCB, CCA, and COB), and three different plaques per model, using EBT3 films in an in-house developed polystyrene phantom and the MCNP6 MC code. Dose difference maps were generated to analyze interplaque variations for a specific type, and for comparing measurements against MC simulations. Furthermore, dose distributions were validated against values specified by the manufacturer (BEBIG) and microdiamond and diode measurements in a water scanning phantom. Radial profiles were assessed and used to estimate dosimetric margins for a given combination of representative tumor geometry and plaque size. Results: Absolute dose rates at a reference depth of 2 mm on the central axis of the plaque show an agreement better than 5% (10%) when comparing film measurements (MCNP6) to the manufacturer’s data. The reproducibility of depth-dose profile measurements was <7% (2 SD) for all investigated detectors and plaque types. Dose difference maps revealed minor interplaque deviations for a specific plaque type due to inhomogeneities of the active layer. The evaluation of dosimetric margins showed that for a majority of the investigated cases, the tumor was not completely covered by the 100% isodose prescribed to the tumor apex if the difference between geometrical plaque size and tumor base ≤4 mm. Conclusions: EBT3 film dosimetry in an in-house developed phantom was successfully used to characterize the dosimetric properties of different {sup 106}Ru plaque models. The film measurements were validated against MC calculations and other experimental methods and showed a good agreement with data from BEBIG well within published tolerances. The dosimetric information as well as interplaque comparison can be used for comprehensive quality assurance and for considerations in the treatment planning of ophthalmic brachytherapy.
60 APPLIED LIFE SCIENCES↗
Search for electroweak production of vector-like leptons in $\tau$-lepton and b-jet final states in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector
A search for pair-production of vector-like leptons is presented, considering their decays into a third-generation Standard Model (SM) quark and a vector leptoquark ( U 1 ) as predicted by an ultraviolet-complete extension of the SM, referred to as the ‘4321’ model. Given the assumed decay of U 1 into third-generation SM fermions, the final state can contain multiple τ-leptons and b-quarks. This search is based on a dataset of pp collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of up to $140~\textrm{fb}^{-1}$. No significant excess above the SM background prediction is observed, and 95% confidence level limits on the cross-section times branching ratio are derived as a function of the vector-like lepton mass. A lower observed (expected) limit of 910 GeV (970 GeV) is set on the vector-like lepton mass. Additionally, the results are interpreted for a supersymmetric model with an R-parity violating coupling to the third-generation quarks and leptons. Lower observed (expected) limits are obtained on the higgsino mass at 880 GeV (940 GeV) and on the wino mass at 1170 GeV (1170 GeV).
Aad, G. [CPPM, Aix-Marseille Université, CNRS/IN2P↗
SubDyn User's Guide and Theory Manual
SubDyn is a time-domain structural-dynamics module for multimember fixed-bottom substructures created by the National Renewable Energy Laboratory (NREL) through U.S. Department of Energy Wind and Water Power Program support. The module has been coupled into the FAST aero-hydro-servo-elastic computer-aided engineering (CAE) tool. Substructure types supported by SubDyn include monopiles, tripods, jackets, and other lattice-type substructures common for offshore wind installations in shallow and transitional water depths. SubDyn can also be used to model lattice support structures for land-based wind turbines. This document is organized as follows. Section 1 details how to obtain the SubDyn and FAST software archives and run both the stand-alone SubDyn or SubDyn coupled to FAST. Section 2 describes the SubDyn input files. Section 3 discusses the output files generated by SubDyn; these include echo files, a summary file, and the results file. Section 4 provides modeling guidance when using SubDyn. The SubDyn theory is covered in Section 5. Section 6 outlines future work, and Section 7 contains a list of references. Example input files are shown in Appendixes A and B. A summary of available output channels are found in Appendix C. Instructions for compiling the stand-alone SubDyn program are detailed in Appendix D. Appendix E tracks the major changes we have made to SubDyn for each public release.
17 WIND ENERGY↗
Interpreting T-History Data on Supercooling and Phase Change Enthalpy of a Salt-Hydrogel Complex for Building Thermal Management
Phase change materials (PCMs) are promising materials for storing and discharging latent heat in buildings to regulate the thermal environment. Measurement of salt hydrate PCM thermal performance is often challenging because of supercooling and phase segregation. Though differential scanning calorimetry (DSC) has been widely used to measure thermal properties of various phase change materials, DSC uses milligrams of sample and is unrealistic for predicting large-scale materials performance. The T-history method [1], in contrast, handles higher volumes but the analysis typically requires a lumped capacitance assumption. Here, we report and analyze T-History data on a novel salt-hydrogel complex with high viscosity, that renders low Biot number sample preparation extremely challenging. We re-examine the standard T-history method and compared against DSC data in this complex material. We report details of an experimental setup, built with necessary additions to a controlled environmental chamber. We carefully examine the validity of the lumped capacitance assumption and suggest a modified analysis using a computational approach for reliable data. Experimental parameters such as ramp rate and temperature range of the environmental chamber are considered via computational modeling to understand the effect of ramp rate on supercooling [2]. Finally, we report thermal cycling experiments on the salt-hydrogel complex. Our modified approach to measuring supercooling and enthalpy of fusion at large scales is important in better understanding the performance of phase-change materials at scale for building thermal storage. References: [1] Marin, Jose M, Belen Zalba, Luisa F Cabeza, and Harald Mehling. “Determination of Enthalpy Temperature Curves of Phase Change Materials with the Temperature-History Method: Improvement to Temperature Dependent Properties.” Measurement Science and Technology 14, no. 2 (February 1, 2003): 184–89. https://doi.org/10.1088/0957-0233/14/2/305. [2] Safari, A., R. Saidur, F.A. Sulaiman, Yan Xu, and Joe Dong. “A Review on Supercooling of Phase Change Materials in Thermal Energy Storage Systems.” Renewable and Sustainable Energy Reviews 70 (April 2017): 905–19. https://doi.org/10.1016/j.rser.2016.11.272
thermodynamics↗
Modeling of Mixed-Pixel Clumping Index From Remote Sensing Data and Its Evaluation
The clumping index (CI) is a canopy structure parameter that describes the dispersion or grouping of leaves. Previously, it has been estimated based on the normalized difference between hotspot and darkspot (NDHD), which is derived from multi-angle remote sensing data. However, currently it is impossible to derive CI from NDHD for a large area at a spatial resolution finer than 275 m since such fine multi-angle data are unavailable. In this study, an algorithm of the mixed-pixel clumping index (MPCI) was implemented, and an MPCI map of China's landmass at 1 km resolution was derived from the HJ-1A/1B data at 30 m resolution. The MPCI map was compared with the previous NDHD CI derived from the moderate resolution imaging spectroradiometer (MODIS). The correlation of these two datasets was greater than 0.9, and the mean bias was approximately 0.1. Indirectly, the MPCI map was applied to an effective leaf area index (LAI) product to derive true LAI. Using the MODIS LAI product as a reference, we found that the coefficient of determination was improved from 0.72 to 0.80, and the root mean squared error was reduced from 0.53 to 0.35 m 2 /m 2 after the effective LAI is corrected by this MPCI map, suggesting that this MPCI map is comparable to the NDHD CI. Although our algorithm is currently tested at 1 km resolution, potentially, it can be applied to higher spatial resolution than 275 m for mapping LAI and carbon cycle modeling before these multi-angle data at higher resolution are available.
47 OTHER INSTRUMENTATION↗
Actinium–DOTA coordination in water from hybrid ML/MM: Structure, free energies, and water-exchange pathways
Quantitative simulation of trivalent ƒ-block chelates in water remains challenging because bonded and non-bonded force-field models make different approximations for coordination structure, exchange dynamics, and ion–ligand interactions in highly charged systems. Here, we develop a hybrid machine-learning/molecular-mechanics (ML/MM) framework for Ac 3+ –DOTA in explicit solvent by training an E(3)-equivariant neural network potential (MACELES) on mechanically embedded QM/MM data for Ac aquo and Ac–DOTA species and coupling it to NAMD 2.14 with particle-mesh Ewald electrostatics. Nanosecond ML/MM trajectories remain numerically stable and preserve chelate integrity, yielding a compact DOTA inner shell with an inner-sphere water coordination number of CN Ac,O w ≈ 1.7 arising from a dynamic equilibrium between one- and two-water states (37.5% and 59.9% of frames; three waters 2.5%). A 5 ns potential of mean force shows two low-lying basins at CN Ac,O w ≈ 1 and CN Ac,O w ≈ 2. DFT end-state free energies are consistent with the ML/MM profile, and DFT minimum-energy paths provide a qualitative electronic-structure reference for the observed basin connectivity. State-resolved kinetics reveal picosecond water-exchange pathways that couple hydration changes to transient DOTA arm fluctuations, and training-set comparisons show that temperature-matched Ac–DOTA data optimize energy/force accuracy while more diverse solvated data improve charge prediction. Overall, the present hybrid ML/MM model provides a practical description of Ac 3+ –DOTA hydration thermodynamics and short-time exchange behavior in explicit water at MD-like cost.
Actinium↗
Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin
Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.
58 GEOSCIENCES↗
Minkowski conformal blocks and the Regge limit for Sachdev-Ye-Kitaev-like models
We discuss scattering in a conformal field theory (CFT) via the conformal partial-wave analysis and the Regge limit. The focus of this paper is on understanding an operator product expansion (OPE) with Minkowski conformal blocks. Starting with a t-channel OPE, it leads to an expansion for an s-channel scattering amplitude in terms of t-channel exchanges. By contrasting with Euclidean conformal blocks we see a precise relationship between conformal blocks in the two limits without preforming an explicit analytic continuation. We discuss a generic feature for a CFT correlation function having singular F (M) (u,v) ~ u –δ , δ > 0, in the limit u → 0 and v → 1. Here, δ = (ℓ eff – 1)/2, with ℓ eff serving as an effective spin and it can be determined through an OPE. In particular, it is bounded from above, ℓ eff ≤ 2, for all CFTs with a gravity dual, and it can be associated with string modes interpolating the graviton in AdS. This singularity is historically referred to as the Pomeron. This bound is nearly saturated by SYK-like effective d = 1 CFT, and its stringy and thermal corrections have piqued current interests. Our analysis has been facilitated by dealing with Wightman functions. We provide a direct treatment in diagonalizing dynamical equations via harmonic analysis over physical scattering regions. As an example these methods are applied to the SYK model.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration
Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.
25 ENERGY STORAGE↗
Confinement effects on the solvation structure of solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel: A first-principles study
Confinement plays an important role in determining ion transport in porous materials, which, in turn, may influence the performance of many energy storage and desalination devices. In this work, we combined density functional theory (DFT) with an implicit solvation model and ab initio molecular dynamics (AIMD) to investigate the effects of nanoconfinement on several solvated alkaline metal cations in a single-digit 1T-MoS 2 nanochannel. Our DFT calculations with a solvation model indicated that cations with stronger hydration energy introduce a higher number of co-intercalated water molecules into the channel, consistent with early experimental observation obtained for MXene (2D transition metal carbide) channels. The predicted optimal water numbers for the cations were then used for AIMD simulations that explicitly include the effects of the solvent. When compared with the cations in bulk solution, our simulations showed that the hydration structure and coordination number (CN) of the solvated cations confined in the MoS 2 channel can be significantly altered. Further, we found that larger cations with weaker hydration energy (K + , Rb + , and Cs + ) exhibited a distinctive CN decrease under confinement, while smaller cations (Li + and Na + ) retained a similar hydration shell as in the bulk solution. More specifically, the hydration shell of large cations (K + , Rb + , and Cs + ) in MoS 2 showed similar features of the coordination angle to the bulk, which suggests the partially broken hydration shell with no geometry change under confinement. Our simulations provided insights into the change of the hydration structure of alkaline metal cations under confinement, which may have important implications on their transport in the 1T-MoS 2 channel.
36 MATERIALS SCIENCE↗
Isomer-resolved unimolecular dynamics of the hydroperoxyalkyl intermediate (•QOOH) in cyclohexane oxidation
The oxidation of cycloalkanes is important in the combustion of transportation fuels and in atmospheric secondary organic aerosol formation. A transient carbon-centered radical intermediate (•QOOH) in the oxidation of cyclohexane is identified through its infrared fingerprint and time- and energy-resolved unimolecular dissociation dynamics to hydroxyl (OH) radical and bicyclic ether products. Although the cyclohexyl ring structure leads to three nearly degenerate •QOOH isomers (β-, γ-, and δ-QOOH), their transition state (TS) barriers to OH products are predicted to differ considerably. Selective characterization of the β-QOOH isomer is achieved at excitation energies associated with the lowest TS barrier, resulting in rapid unimolecular decay to OH products that are detected. A benchmarking approach is employed for the calculation of high-accuracy stationary point energies, in particular TS barriers, for cyclohexane oxidation (C 6 H 11 O 2 ), building on higher-level reference calculations for the smaller ethane oxidation (C 2 H 5 O 2 ) system. The isomer-specific characterization of β-QOOH is validated by comparison of experimental OH product appearance rates with computed statistical microcanonical rates, including significant heavy-atom tunneling, at energies in the vicinity of the TS barrier. Master-equation modeling is utilized to extend the results to thermal unimolecular decay rate constants at temperatures and pressures relevant to cyclohexane combustion.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Synergistic Retrieval of Temperature and Humidity Profiles from Space-Based and Ground-Based Infrared Sounders Using an Optimal Estimation Method
The atmospheric temperature and humidity profiles of the troposphere are generally measured by radiosondes and satellites, which are essential for analyzing and predicting weather. Nevertheless, the insufficient observation frequencies and low detection accuracy of the boundary layer restricts the description of atmospheric state changes by the temperature and humidity profiles. Therefore, this work focus on retrieving the temperature and humidity profiles using observations of the FengYun-4 (FY-4) Geostationary Interferometric Infrared Sounder (GIIRS) combined with ground-based infrared spectral observations from the Atmospheric Emitted Radiance Interferometer (AERI), which are more accurate than space-based individual retrieval results and have a wider effective retrieval range than ground-based individual retrieval results. Based on the synergistic observations, which are made by matching the space-based and ground-based data with those of different spatial and temporal resolutions, a synergistic retrieval process is proposed to obtain the temperature and humidity profiles at a high frequency under clear-sky conditions based on the optimal estimation method. In this research, using the line-by-line radiative transfer model (LBLRTM) as the forward model for observing simulations, a retrieval experiment was carried out in Qingdao, China, where an AERI is situated. Taking radiosonde data as a reference for comparing the retrieval results of the temperature and humidity profiles of the troposphere, the root-mean-square error (RMSE) of the synergistic retrieval algorithm below 400 hPa is within 2 K for temperature and within 12% for relative humidity. Compared with the GIIRS individual retrieval, the RMSE of temperature and relative humidity for the synergistic method is reduced by 0.13–1.5 K and 2.7–4.4% at 500 hPa, and 0.13–2.1 K and 2.5–7.2% at 900 hPa. Moreover, the forecast index (FI) calculated from the retrieval results shows reasonable consistency with the FIs calculated from the ERA5 reanalysis and from radiosonde data. The synergistic retrieval results have higher temporal resolution than space-based retrieval results and can reflect the changes in the atmospheric state more accurately. Overall, the results demonstrated the promising potential of the synergistic retrieval of temperature and humidity profiles at high accuracy and high temporal resolution under clear-sky conditions from FY-4/GIIRS and AERI.
54 ENVIRONMENTAL SCIENCES↗
Techno-Economic Implications of Electrical Machine Scaling for Wave Energy Converters: Preprint
The sizing of an electrical machine for a Wave Energy Converter (WEC) can have a substantial impact on the overall sizing, cost, and rating of the device. An electrical generator is typically part of the power take-off (PTO) system, which is the mechanism by which the energy absorbed by the prime mover is transformed into useable electrical. For practically all WECs, the rate of change of actuation is predominantly determined by the wave resource (i.e., the wave height and frequency) and devices will see a sinusoidally varying velocity according to the wave conditions. The same can then be said for both directly and indirectly coupled PTOs with electrical generators. This techno-economic study investigates electrical machine scaling and associated cost implications through core machine design theory, manufacturer data, supporting literature, and the DOE sponsored Reference Model Project (RMP). The RMP was a partnered effort to develop open-source marine energy (ME) point designs as reference models (RMs) to benchmark ME technology performance and costs, methods for design and analysis of ME technologies, estimations for capital costs, operational costs, and levelized costs of energy (LCOE). The results from this study show torque is directly related to (1) the physical size of the machine required to increase the airgap sheer stresses, (2) the amount of active material, (3) the support structure, (4) bearing size and rating, and (5) offshore cable rating, all of which have a significant effect on overall system costs in terms of both CAPEX and OPEX. This paper aims to be a critical benchmark in helping determine an “optimal” nameplate rating for wave energy devices and their associated PTO. With an optimized rating and sizing process, WEC costs can be reduced, and overall performance can be improved.
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