Efficient representation for simulating U(1) gauge theories on digital quantum computers at all values of the coupling
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting
Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.
36 MATERIALS SCIENCE↗
Enzymatic synthesis of kraft lignin-acrylate copolymers using an alkaline tolerant laccase
Abstract Softwood kraft lignin is a major bioresource relevant to the production of sustainable bio-based products. Continued challenges to lignin valorization, however, include poor solubility in organic solvents and in aqueous solutions at neutral pH. Herein, an alkaline tolerant laccase was used to graft acrylate functionalities onto softwood kraft lignin, which is expected to enhance the reactivity of lignin with isocyanate when producing bio-based polyurethanes. Proton nuclear magnetic resonance, Fourier-transform infrared spectroscopy, and high-performance liquid chromatography were used to confirm successful grafting of the acrylate monomer onto lignin and verify the importance of including tert-butyl hydroperoxide as an initiator in the grafting reaction. Laccase-mediated grafting of softwood kraft lignin under alkaline conditions produced lignin products with approximately 30% higher hydroxyl value and higher reactivity toward isocyanate. The reported enzymatic and aqueous process presents an opportunity for the sustainable valorization of softwood kraft lignin. Key points • Softwood kraft lignin displayed high phenolic hydroxyl content, polydispersity index and average molecular weight • Grafting hydroxyethyl acrylate (HEA) monomer onto kraft lignin by laccase was successful at 60 °C and alkaline conditions • Lignin-HEA grafted copolymer showed an increase in total OH value and an increase in average molecular weight
59 BASIC BIOLOGICAL SCIENCES↗
Composite coatings from polycarbosilane derived SiC and Al/SiC cermet active fillers as protective barriers against steel corrosion
Stainless steel is used throughout the world as a structural material. However, it undergoes corrosion damage when exposed to extremely corrosive media, such as the marine environment. An alternative to solve this problem lies in the development of coatings that can withstand extreme conditions but also be easily deposited with inherently corrosion-resistant materials such as silicon carbide (SiC). The present study shows a simple method to produce Al/SiC cermet powders by attrition milling. The resulting cermet powders with a metallic matrix and hemispherical morphology, were employed as fillers in polycarbosilane (PCS) solutions that were sprayed on A304 stainless steel substrates. Al/SiC composite coatings were produced after heating the sprayed suspensions at 700 °C for 1 h in Ar atmosphere. The resulting composite coatings exhibited low surface energies (< 35 mN/m), water contact angles of 53°, and adhesion strength of up to 30 MPa. Finally, corrosion tests were performed in a cyclic corrosion test chamber, showing that these coatings effectively reduced the corrosion rate of stainless steel by 87%, reaching corrosion rate values of 0.007 g/cm 2 year.
36 MATERIALS SCIENCE↗
Dynamic properties of 316l stainless steel repaired using electron beam additive manufacturing
Additive manufacturing has the potential to be used for repair of high-value parts, but the strength and integrity of such repaired parts, especially under dynamic loading, in still unknown. This work presents the results of high strain-rate dynamic testing of additively repaired stainless steel samples. The 316L samples were intentionally damaged and subsequently repaired with 308L stainless steel wire using electron beam additive manufacturing. The repaired samples were subjected to gas-gun impact testing to induce incipient damage and determine the role played by the repaired region in dictating damage and failure. The results show the following: 1) the equation of state of the repaired region is comparable to the original material as shown by the unchanged spall plane location, 2) the deformation behavior is similar to the original material as shown by the similar Hugoniot Elastic limit, 3) the spall strength of the repaired region is slightly higher than the original material due to varying grain size, and 4) the damage morphology in the repaired region is different and involves a high rate of void coalescence. In conclusion, despite these minor differences in the spall strength and the damage morphology, the overall dynamic response of the original material and repaired samples is similar suggesting that AM is a promising approach for repairing high-value components.
36 MATERIALS SCIENCE↗
Flash graphene from rubber waste
Most conventional production processes for graphene are time-consuming, solvent-intensive, and energetically demanding. To circumvent these limitations for mass production, flash Joule heating (FJH) has been shown to be an effective method to synthesize graphene. Here, methods for optimizing production of graphene from rubber waste feedstocks are shown. Through careful control of system parameters, such as pulse voltage and pulse time, turbostratic flash graphene (tFG) can be produced from rubber waste. It is characterized by Raman spectroscopy, X-ray diffraction and thermogravimetric analysis. Here, the resulting tFG can be easily exfoliated and dispersed into various solvents because of its turbostratic arrangement. Addition of tFG into Portland cement results in a significant increase in the compressive strength of the composite. From a materials perspective, FJH offers a facile and inexpensive method for producing high quality tFG from rubber waste materials, which would otherwise be disposed of in landfills or burned for fuel. FJH allows for upcycling of low-value rubber waste into high-value carbon nanomaterials for use as reinforcing additives.
54 ENVIRONMENTAL SCIENCES↗
Quantifying cover crop effects on soil health and productivity
The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.
54 ENVIRONMENTAL SCIENCES↗
Adsorption and activation of CO 2 on Pt/CeOx/TiO 2 (110): Role of the Pt-CeO x interface
The adsorption and dissociation of CO 2 on TiO 2 (110), CeO x /TiO 2 (110) and Pt/CeO x /TiO 2 (110) surfaces has been examined using Ambient Pressure X-ray Photoelectron Spectroscopy (AP-XPS). The substrates under study exhibited different degrees of complexity which were tested for the binding of the adsorbate and the cleavage of C-O bonds. The surfaces were prepared by depositing CeO x (0.1 ML) onto TiO 2 (110) to form a mixed oxide support, onto which Pt nanoparticles (0.2 ML) were deposited. This configuration yields a complex set of interfaces between metal and oxides and we have systematically titrated the active role of each component (Pt 4f, Ce 3d and Ti 2p regions) and the arising surface intermediates (C 1s and O 1s regions). CO 2 barely bonds to stoichiometric TiO 2 (110). It heals oxygen vacancies of this oxide surface (CO 2,gas → CO gas + O a ) and does not form stable carbonates. A stable carbonate was seen upon adsorption of CO 2 on CeO x /TiO 2 (110) and on this type of substrate the adsorbate also removed O vacancies leading to the oxidation of Ti 3+ and Ce 3+ sites. Pt nanoparticles dispersed on CeO x /TiO 2 (110) were highly effective for the binding and dissociation of CO 2 , with the formation of CO 3 , CO, C and CH x species on the Pt/CeO x /TiO 2 (110) system. The results of theoretical calculations based on density-functional theory (DFT) show that Pt/CeOx/TiO2(110) binds CO2 much stronger than surfaces of bulk platinum {(111), (100), (110)} or other late transition metals. On a Pt-CeO x interface, the molecule adsorbs with a bent configuration (~ 130° O-C-O bond angle) and with a substantial elongation (~ 0.1 Å) of the C-O bonds, facilitating its transformation into high value chemicals.
36 MATERIALS SCIENCE↗
Cobalt Oxide-Coated Single Crystalline Bismuth Vanadate Photoanodes for Efficient Photoelectrochemical Chlorine Generation
Bismuth vanadate (BiVO 4 ) is an outstanding photoanode material for photoelectrochemical water splitting. Here in this work, a series of single crystalline BiVO 4 photoanodes are synthesized by pulsed laser deposition (PLD). Once coated with a thin layer of cobalt oxide (CoO x ) cocatalyst, also by PLD, the photoanodes support efficient photoelectrochemical generation of chlorine (Cl 2 ) from brine under simulated solar light. The activity of the chlorine generation reaction (ClER) is optimized when the thickness of CoO x is about 3 nm, with the faradic efficiency of ClER exceeding 60%. Detailed studies show that the CoO x cocatalyst layer is amorphous, uniform in thickness, and chemically robust. As such, the cocatalyst also effectively protects the underlying BiVO 4 photoanodes against chlorine corrosion. This work provides insights into using artificial photosynthesis for byproducts that carry significant economic value while avoiding the energetically expensive oxygen evolution reactions.
36 MATERIALS SCIENCE↗
Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions
Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.
54 ENVIRONMENTAL SCIENCES↗
Creating large Fock states and massively squeezed states in optics using systems with nonlinear bound states in the continuum
The quantization of the electromagnetic field leads directly to the existence of quantum mechanical states, called Fock states, with an exact integer number of photons. Despite these fundamental states being long-understood, and despite their many potential applications, generating them is largely an open problem. For example, at optical frequencies, it is challenging to deterministically generate Fock states of order two and beyond. Here, we predict the existence of an effect in nonlinear optics, which enables the deterministic generation of large Fock states at arbitrary frequencies. The effect, which we call an n-photon bound state in the continuum, is one in which a photonic resonance (such as a cavity mode) becomes lossless when a precise number of photons n is inside the resonance. Based on analytical theory and numerical simulations, we show that these bound states enable a remarkable phenomenon in which a coherent state of light, when injected into a system supporting this bound state, can spontaneously evolve into a Fock state of a controllable photon number. This effect is also directly applicable for creating (highly) squeezed states of light, whose photon number fluctuations are (far) below the value expected from classical physics (i.e., shot noise). In conclusion, we suggest several examples of systems to experimentally realize the effects predicted here in nonlinear nanophotonic systems, showing examples of generating both optical Fock states with large n (n > 10), as well as more macroscopic photonic states with very large squeezing, with over 90% less noise (10 dB) than the classical value associated with shot noise.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Non-parametric projections of national income distribution consistent with the Shared Socioeconomic Pathways
Understanding and projecting income distributions within countries and regions is important to understanding consumption trends and the distributional consequences of climate impacts and responses. Several global, country-level projections of income distribution are available but most project only the Gini coefficient (a summary statistic of the distribution) or utilize the Gini along with the assumption of a lognormal distribution. We test the lognormal assumption and find that it typically underestimates income in the highest deciles and over-estimates it in others. We find that a new model based on two principal components of national time series data for income distribution provides a better fit to the data for all deciles, especially for the highest and lowest. We also construct a projection model in which the first principal component is driven by the Gini coefficient and the second captures deviations from this relationship. We use the model to project income distribution by decile for all countries for the five shared socioeconomic pathways. We find that inequality is consistently higher than projections based on the Gini and the lognormal functional form, with some countries reaching ratios of the highest to lowest income deciles that are almost three times their value using the lognormal assumption.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Printing of electromagnetic interference shielding materials
Here, the proliferation of electronic devices has made electromagnetic interference (EMI) shielding an exponentially growing business. Regulatory requirements change constantly as new technologies continue to emerge. Innovations in materials and new advances in shielding implementation techniques are needed to pass regulatory compliance tests at an affordable cost. Here, we print various EMI shielding materials such as copper, silver and a composite of copper with Fe 3 O 4 using plasma jet printing. Printing enables shields only a few microns thick capable of high shielding effectiveness. Copper's EMI shielding performance is primarily contributed by reflection mechanism, as expected and this is known to cause secondary pollution. A Green Index for EMI shielding, given by the ratio of absorption and reflection contributions to shielding, indicates values lower than 0.1 for printed copper films.
36 MATERIALS SCIENCE↗
Quaternary MgSiN 2 -GaN alloy semiconductors for deep UV applications
Ultrawide direct band gap semiconductors hold great promise for deep ultraviolet optoelectronic applications. Here we evaluate the potential of MgSiN 2 -GaN alloys for this purpose. Although MgSiN 2 itself has an indirect gap ~0.4 eV below its direct gap of ~6.5 eV, its different sign lattice mismatch from GaN in two different basal plane directions could avoid the tensile strain which limits Al x Ga 1–x N on GaN for high x. Two octet-rule-preserving structures (with space groups Pmn2 1 and P1n1) of a 50% alloy of MgSiN 2 and GaN are investigated and are both found to have gaps larger than 4.75 eV using quasiparticle self-consistent GW calculations. Both are nearly direct gap in the sense that the indirect gap is less than 0.1 eV lower than the direct gap. Furthermore, their mixing energies are positive yet small, with values of 8 (31) meV/atom for Pmn2 1 (P1n1), indicating only a small driving force toward phase separation.
36 MATERIALS SCIENCE↗
Increased bundle‐sheath leakiness of CO 2 during photosynthetic induction shows a lack of coordination between the C 4 and C 3 cycles
Summary Use of a complete dynamic model of NADP‐malic enzyme C 4 photosynthesis indicated that, during transitions from dark or shade to high light, induction of the C 4 pathway was more rapid than that of C 3 , resulting in a predicted transient increase in bundle‐sheath CO 2 leakiness ( ϕ ). Previously, ϕ has been measured at steady state; here we developed a new method, coupling a tunable diode laser absorption spectroscope with a gas‐exchange system to track ϕ in sorghum and maize through the nonsteady‐state condition of photosynthetic induction. In both species, ϕ showed a transient increase to > 0.35 before declining to a steady state of 0.2 by 1500 s after illumination. Average ϕ was 60% higher than at steady state over the first 600 s of induction and 30% higher over the first 1500 s. The transient increase in ϕ , which was consistent with model prediction, indicated that capacity to assimilate CO 2 into the C 3 cycle in the bundle sheath failed to keep pace with the rate of dicarboxylate delivery by the C 4 cycle. Because nonsteady‐state light conditions are the norm in field canopies, the results suggest that ϕ in these major crops in the field is significantly higher and energy conversion efficiency lower than previous measured values under steady‐state conditions.
59 BASIC BIOLOGICAL SCIENCES↗
(Invited) Utilization of Bio-CO 2 and Bio-Methane for Fuel Production: Integration Solid Oxide Electrolyzer, Low Energy Plasma Reformer with Fischer-Tropsch Synthesis
Transition to renewable energy is essential to achieve climate protection objectives. Besides storing electricity for later use, fuel production using renewable energy is an essential part of reducing fossil dependance. The highest value application in current markets is the production of liquid transportation fuels such as sustainable aviation fuels (SAF) from sustainable, ideally biogenic carbon resources. A system is presented for processing anaerobic digester gas for liquid hydrocarbon production. Bio-CO 2 is processed through a solid oxide electrolysis cell and bio-CH 4 through a low energy plasma reformer. The combined synthesis gas is supplied to a Fischer-Tropsch reactor for the production of liquid hydrocarbons. The combination of technologies nearly doubles the yield of biofuel by utilizing the bio-CO 2 in addition to the bio-CH 4 . Here, the product fuel is all bio-carbon but it also embodies renewable electric energy in a high-value, storable and transportable liquid hydrocarbon.
09 BIOMASS FUELS↗
Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing
This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.
54 ENVIRONMENTAL SCIENCES↗
Electroplating Titanium from Ionic Mixtures
Titanium & Zirconium metal films have been electroplated by a near-ambient scalable process for high value-add/lower volume applications. The films have been commercially tested as bonding layers
36 MATERIALS SCIENCE↗