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At least 289 records · Page 16

Overview of the SPARC tokamak

The SPARC tokamak is a critical next step towards commercial fusion energy. SPARC is designed as a high-field ( $B_0 = 12.2$ T), compact ( $R_0 = 1.85$ m, $a = 0.57$ m), superconducting, D-T tokamak with the goal of producing fusion gain $Q>2$ from a magnetically confined fusion plasma for the first time. Currently under design, SPARC will continue the high-field path of the Alcator series of tokamaks, utilizing new magnets based on rare earth barium copper oxide high-temperature superconductors to achieve high performance in a compact device. The goal of $Q>2$ is achievable with conservative physics assumptions ( $H_{98,y2} = 0.7$ ) and, with the nominal assumption of $H_{98,y2} = 1$ , SPARC is projected to attain $Q \approx 11$ and $P_{\textrm {fusion}} \approx 140$ MW. SPARC will therefore constitute a unique platform for burning plasma physics research with high density ( $\langle n_{e} \rangle \approx 3 \times 10^{20}\ \textrm {m}^{-3}$ ), high temperature ( $\langle T_e \rangle \approx 7$ keV) and high power density ( $P_{\textrm {fusion}}/V_{\textrm {plasma}} \approx 7\ \textrm {MW}\,\textrm {m}^{-3}$ ) relevant to fusion power plants. SPARC's place in the path to commercial fusion energy, its parameters and the current status of SPARC design work are presented. This work also describes the basis for global performance projections and summarizes some of the physics analysis that is presented in greater detail in the companion articles of this collection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ionic Liquid-Enhanced Interfaces to Boost Reactive C O2 Capture

The addition of ionic liquids (ILs) to a mixture containing a molecular solvent and other ionic species can induce the heterogeneous redistribution of cations and anions at the gas–liquid interface. This nonuniform redistribution of cations and anions driven by the differences in the solvophilicity of ions can improve the thermophysical and interfacial properties of such mixtures, creating a local chemical environment that is conducive to some reactions. In this work, ILs are added to a mixture of potassium hydroxide (KOH) and ethylene glycol (EG), used as a reactive absorbent and electrolyte in the migration-assisted moisture-gradient (MAMG) process for CO 2 capture. Molecular dynamics (MD) simulations are employed to probe into the effects of complex ion–ion and ion–solvent interactions and to examine the chemical composition at the gas–liquid interface. A total of 12 systems are investigated using molecular simulations to identify trends in the performance of IL additives based on the choice of cation, anion, and IL concentration. The cation effects are studied using IL additives based on 1-ethyl-3-methylimidazolium ([EMIM] + ) and 1-butyl-3-methylimidazolium ([BMIM] + ), while the impact of anions is examined using additives based on dicyanamide [DCA] − , triflate [TfO] − , bistriflimide [NTf 2 ] − , and hexafluorophosphate [PF 6 ] − anions, respectively. The influence of the IL concentration is also evaluated at molar concentrations between 1% and 4%. The simulation results indicate that the use of IL additives can affect the physical CO 2 solubility, surface tension, and the localization of CO 2 around the [OH] − ions at the gas–liquid interface. It is also evident that the choice of cations, anions, and IL concentration determines the extent to which the IL additives impact the local physicochemical properties. Physical dissolution, diffusive transport, and interaction with [OH] − are critical intermediate steps toward reactive CO 2 capture using a liquid absorbent. Hence, the improvement in one or more of these properties, aided by IL additives, is expected to improve the overall CO 2 capture performance. Experiments reaffirmed the impact of IL additives on CO 2 capture performance and the sensitivity to the choice of the cation, anion, and concentration of the IL additive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning-Accelerated First-Principles Molecular Dynamics Reveals C–C Coupling Mechanisms toward Ethylene on Cu(100)

Here, the Cu(100) termination has been identified as the most effective facet for converting CO and CO 2 into ethylene. To enhance both the activity and selectivity of ethylene production, we perform machine-learning-accelerated, first-principles molecular dynamics simulations at 298 K in an explicit solvent at pH 7 to elucidate the C–C coupling mechanism─the critical reaction step in forming C 2+ products. Among the six potential C–C coupling pathways, the most feasible are CO* dimerization and CO – CHO* and CHO* – CHO* couplings. Using the computational hydrogen electrode method, we demonstrate that all three pathways are equally accessible at −0.6 V vs RHE. At a potential below −1.0 V vs RHE, the thermodynamic barriers for the CO – CHO* and CHO* – CHO* pathways become negligible. Our computational findings explain the experimental observations, particularly the absence of C 2+ products above −0.4 V vs RHE and the peaks in ethylene production near −0.6 and −1.0 V vs RHE. Since CHO* acts as a key intermediate common to both C–C coupling and CH 4 formation, we propose that suppressing CHO* hydrogenation would inhibit CH 4 pathways, thereby maximizing ethylene selectivity.

CO2 reduction↗

Isotopic Substitution Reveals the Importance of Aluminate Diffusion Dynamics in Gibbsite (Al(OH) 3 ) Crystallization from Alkaline Aqueous Solution

Understanding molecular-scale factors governing the precipitation of aluminum hydroxides, such as gibbsite, under alkaline conditions is important for the formation of laterite deposits, as well as aluminum processing. However, mechanisms enabling tetrahedral aluminate ions to assemble into octahedral sites of the gibbsite lattice remain unclear. Formation of oligomeric complexes has been hypothesized as a critical intermediate step. Here, we report a study of gibbsite solubility in highly alkaline solutions using deuterium substitution to probe equilibrium and kinetic factors that could affect oligomeric intermediate formation, including the reactivity and the diffusivity of aluminate ions. When substituting sodium hydroxide with sodium deuteroxide, solution analysis shows a nearly 40% and 50% increase in gibbsite solubility in 2.4 and 3.3 mol·kg –1 total sodium solutions, respectively. Raman spectroscopy indicated that monomeric aluminate ions are the predominant species in solution irrespective of deuteration. However, both 27 Al and 23 Na nuclear magnetic resonance (NMR) spectroscopy revealed significant differences in chemical shifts in deuterated solutions, and analysis of 1 H, 23 Na, and 27 Al diffusion coefficients with pulsed-field gradient, stimulated echo NMR spectroscopy shows a decrease in ion diffusivity with increasing total deuterium in solution, consistent with the notion of increasing strength in the hydrogen/deuterium bonding network. In conclusion, because the relative change in 1 H diffusion coefficients are commensurate with the difference in apparent solubility constants, there is evidence for an oligomeric intermediate whose steady-state concentration is maintained by the collision frequency of aluminate ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gerischer Electrochemistry Today

Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward More Actionable Flood‐Risk Information

Abstract The increasingly urgent need to develop knowledge and practices to manage flood risks drives innovative information design. However, experts often disagree about design practices. As a result, flood‐risk estimates can diverge, leading to different conclusions for decision‐making. Using examples of household‐scale fluvial (riverine) flood‐risk information in the United States, we assess design features and risk communication approaches that may lead to more actionable information for decision‐making. We argue that increased attention to uncertainty characterization and model diagnostics is a critical intermediate step for developing simpler approaches for designing flood‐risk information. Simpler frameworks are desirable because flood risks change over time, and simpler frameworks are less costly to update. Developing frameworks for large spatial domains require collaboration grounded in principles of open science. Finally, systematically evaluating how decision‐makers access and use information can provide new insights to guide risk communication and information design.

54 ENVIRONMENTAL SCIENCES↗

Trends in oxygenate/hydrocarbon selectivity for electrochemical CO (2) reduction to C 2 products

The electrochemical conversion of carbon di-/monoxide into commodity chemicals paves a way towards a sustainable society but it also presents one of the great challenges in catalysis. Herein, we present the trends in selectivity towards specific dicarbon oxygenate/hydrocarbon products from carbon monoxide reduction on transition metal catalysts, with special focus on copper. We unveil the distinctive role of electrolyte pH in tuning the dicarbon oxygenate/hydrocarbon selectivity. The understanding is based on density functional theory calculated energetics and microkinetic modeling. We identify the critical reaction steps determining selectivity and relate their transition state energies to two simple descriptors, the carbon and hydroxide binding strengths. The atomistic insight gained enables us to rationalize a number of experimental observations and provides avenues towards the design of selective electrocatalysts for liquid fuel production from carbon di-/monoxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large-scale integration of artificial atoms in hybrid photonic circuits

A central challenge in developing quantum computers and long-range quantum networks is the distribution of entanglement across many individually controllable qubits. Colour centres in diamond have emerged as leading solid-state ‘artificial atom’ qubits because they enable on-demand remote entanglement, coherent control of over ten ancillae qubits with minute-long coherence times and memory-enhanced quantum communication. A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. So far, these efforts have been stymied by qubit inhomogeneities, low device yield and complex device requirements. Here we introduce a process for the high-yield heterogeneous integration of ‘quantum microchiplets’—diamond waveguide arrays containing highly coherent colour centres—on a photonic integrated circuit (PIC). We use this process to realize a 128-channel, defect-free array of germanium-vacancy and silicon-vacancy colour centres in an aluminium nitride PIC. Photoluminescence spectroscopy reveals long-term, stable and narrow average optical linewidths of 54 megahertz (146 megahertz) for germanium-vacancy (silicon-vacancy) emitters, close to the lifetime-limited linewidth of 32 megahertz (93 megahertz). We show that inhomogeneities of individual colour centre optical transitions can be compensated in situ by integrated tuning over 50 gigahertz without linewidth degradation. The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters and general-purpose quantum processors

36 MATERIALS SCIENCE↗

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗

Quantum computing and preconditioners for hydrological linear systems

Modeling hydrological fracture networks is a hallmark challenge in computational earth sciences. Accurately predicting critical features of fracture systems, e.g. percolation, can require solving large linear systems far beyond current or future high performance capabilities. Quantum computers can theoretically bypass the memory and speed constraints faced by classical approaches, however several technical issues must first be addressed. Chief amongst these difficulties is that such systems are often ill-conditioned, i.e. small changes in the system can produce large changes in the solution, which can slow down the performance of linear solving algorithms. We test several existing quantum techniques to improve the condition number, but find they are insufficient. We then introduce the inverse Laplacian preconditioner, which improves the scaling of the condition number of the system from O(N) to O($\sqrt{N}$) and admits a quantum implementation. These results are a critical first step in developing a quantum solver for fracture systems, both advancing the state of hydrological modeling and providing a novel real-world application for quantum linear systems algorithms.

97 MATHEMATICS AND COMPUTING↗

Critical Enzyme Reactions in Aromatic Catabolism for Microbial Lignin Conversion

The application of microbes to valorize aromatic compounds derived from the abundant plant biopolymer lignin is a rapidly developing area of research that may ultimately enable viable conversion of this recalcitrant and heterogeneous resource to valuable bio-based chemical products. Starting from the three canonical lignin building blocks, which differ in the extent of aromatic ring methoxylation, several common classes of enzymatic reaction occur in the upper pathways of aromatic catabolism to prepare aromatic compounds for assimilation into central carbon metabolism, including aromatic O-demethylation, hydroxylation and decarboxylation. These critical enzymatic steps can often be rate-limiting for efficient biological funnelling of aromatic compounds. Here we review the known enzymatic mechanisms for these reactions that are relevant for aerobic aromatic catabolism of lignin-related monomers, highlighting opportunities at the intersection of biochemistry, enzyme engineering and metabolic engineering for applications in the expanding field of microbial lignin valorization.

aromatic catabolism↗

Using anion photoelectron spectroscopy of cluster models to gain insights into mechanisms of catalyst-mediated H 2 production from water

We report that metal oxide cluster models of catalyst materials offer a powerful platform for probing the molecular-scale features and interactions that govern catalysis. This perspective gives an overview of studies implementing the combination of anion photoelectron (PE) spectroscopy and density functional theory calculations toward exploring cluster models of metal oxides and metal-oxide supported Pt that catalytically drive the hydrogen evolution reaction (HER) or the water–gas shift reaction. The utility in the combination of these experimental and computational techniques lies in our ability to unambiguously determine electronic and molecular structures, which can then connect to results of reactivity studies. In particular, we focus on the activity of oxygen vacancies modeled by suboxide clusters, the critical mechanistic step of forming proximal metal hydride and hydroxide groups as a prerequisite for H2 production, and the structural features that lead to trapped dihydroxide groups. The pronounced asymmetric oxidation found in heterometallic group 6 oxides and near-neighbor group 5/group 6 results in higher activity toward water, while group 7/group 6 oxides form very specific stoichiometries that suggest facile regeneration. Studies on the trans-periodic combination of cerium oxide and platinum as a model for ceria supported Pt atoms and nanoparticles reveal striking negative charge accumulation by Pt, which, combined with the ionic conductivity of ceria, suggests a mechanism for the exceptionally high activity of this system towards the water–gas shift reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Appendix Q: Recommendations for Developing Molecular Assays for Microbial Pathogen Detection Using Modern In Silico Approaches

We describe the use of in silico approaches to improve the process of molecular assay development and reduce time and cost by utilizing available databases of whole genome pathogen sequences combined with modern bioinformatics and physical modeling tools. Well-characterized assays are needed for accurately detecting pathogens in environmental and patient samples and also for evaluation of the efficacy of a medical countermeasure that may be administered to patients. The polymerase chain reaction (PCR) remains the gold standard for pathogen detection due to the simplicity of its instrumentation, low cost of reagents, and outstanding limit of detection (LOD), sensitivity, and specificity. However, creation of such PCR assays often involves iterations of design, preliminary testing, and thorough validation with clinical isolates and testing in relevant matrices, which can be time consuming, costly, and result in suboptimal assays. Since formal validation (e.g., for Emergency Use Authorization [EUA] or Food and Drug Administration [FDA] licensure) of an infectious disease assay can be very expensive and can require extensive time of development, having a well-designed assay up front is a critical first step. Yet, many assays described in the literature utilized limited design capabilities and many initially promising assays fail the validation process, resulting in increased costs and timelines for successful product development. While the computational approaches outlined in this document by no means obviate the need for wet lab testing, they can reduce the amount of effort wasted on empirical optimization and iterative redesigns and also guide validation studies. The proposed computational approaches also result in higher performing assays with better sensitivity, specificity, and lower LOD and reduce the possibility of assay failure due to signature erosion. To provide clarity, an extensive glossary of defined terms is provided.

59 BASIC BIOLOGICAL SCIENCES↗

Stringent σ8 constraints from small-scale galaxy clustering using a hybrid MCMC + emulator framework

ABSTRACT We present a novel simulation-based hybrid emulator approach that maximally derives cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy clustering, with sufficient precision for DESI Year 1 (Y1) analysis. Our hybrid approach first samples the HOD space on a fixed cosmological simulation grid to constrain the high-likelihood region of cosmology + HOD parameter space, and then constructs the emulator within this constrained region. This approach significantly reduces the parameter volume emulated over, thus achieving much smaller emulator errors with fixed number of training points. We demonstrate that this combined with state-of-the-art simulations result in tight emulator errors comparable to expected DESI Y1 LRG sample variance. We leverage the new abacussummit simulations and apply our hybrid approach to CMASS non-linear galaxy clustering data. We infer constraints on σ8 = 0.762 ± 0.024 and fσ8(zeff = 0.52) = 0.444 ± 0.016, the tightest among contemporary galaxy clustering studies. We also demonstrate that our fσ8 constraint is robust against secondary biases and other HOD model choices, a critical first step towards showcasing the robust cosmology information accessible in non-linear scales. We speculate that the additional statistical power of DESI Y1 should tighten the growth rate constraints by at least another 50–60 ${{\ \rm per\ cent}}$, significantly elucidating any potential tension with Planck. We also address the ‘lensing is low’ tension, which we find to be in the same direction as a potential tension in fσ8. We show that the combined effect of a lower fσ8 and environment-based bias accounts for approximately $50{{\ \rm per\ cent}}$ of the discrepancy.

79 ASTRONOMY AND ASTROPHYSICS↗

Impact of the Annealing Temperature on the Local Se Distribution and Optical Properties in CdSexTe1-x Solar Cells by Multimodal X-ray Microscopy

The introduction of Se in CdTe solar-cell absorbers has led to multiple beneficial effects in the devices, including an increased short-circuit current and an extended charge-carrier lifetime. A critical manufacturing step of CdSexTe1-x solar cells is CdCl2 annealing at high temperatures, during which Se diffuses through the absorber layer. Understanding the local Se distribution in the absorber and its impact on optical properties of the material is key for the further development of this thin-film solar cell technology. In a multimodal x-ray scanning microscopy approach, we investigated the impact of the annealing temperature of CdSexTe1-x solar cells on the Se distribution and on optical characteristics of the material. For this purpose, we exploited an upgraded x-ray excited optical luminescence (XEOL) detection unit that enables simultaneous spectrally and temporally resolved XEOL mapping at synchrotron facilities that are ideal for studying thin-film solar-cell materials with hard x-rays featuring high penetration depth and lateral resolution.

14 SOLAR ENERGY↗

Measurements of attenuation and scattering properties of water-based liquid scintillator

Water-based liquid scintillator (WbLS) is a hybrid detector medium which has been proposed as a fill material for future large-volume rare event searches, including ν − detectors. This family of scintillating suspensions promises waterlike attenuation and scattering behavior, while offering scintillation light yield for sub-Cherenkov-threshold events. These features may allow for improved vertex and energy resolution, and concomitant improvements in background rejection and particle identification. While subscale measurements of light yield, timing and pulse-shape have been performed in several WbLS formulations, detailed measurements of the attenuation and scattering properties of WbLS remain a critical, unresolved step along the pathway to deployment. In pursuit of a better understanding of these parameters, a “long-arm” attenuation and scattering instrument has been developed at Lawrence Livermore National Laboratory, dubbed LASE (Livermore Attenuation and Scattering Experiment). Optical property measurements have been performed using LASE in DI water, Gd-water, WbLS and Gd-WbLS. Measurements of the optical properties of WbLS (1% LAB-PPO scintillator) provided by Brookhaven National Laboratory demonstrate an attenuation minimum of 4.87 × 10 − 4 ± 1.42 × 10 − 4 cm − 1 at 450 nm, while Gd-loaded WbLS (1% LAB-PPO scintillator, 0.1% Gd) demonstrated a minimum attenuation coefficient of 4.77 × 10 − 4 ± 1.27 × 10 − 4 cm − 1 at the same wavelength. Measurements of scattering in WbLS show a scattering coefficient of 3.39 × 10 − 4 ± 1.98 × 10 − 5 cm − 1 at the 450 nm attenuation minimum, while Gd-WbLS has a scattering coefficient of 2.8 × 10 − 4 ± 1.63 × 10 − 5 cm − 1 at that wavelength. These scattering and attenuation coefficients are significantly larger than measured for DI water at similar wavelengths ( 8.8 × 10 − 5 cm − 1 ± 3.8 × 10 − 5 attenuation at 430 nm, 2.2 × 10 − 5 ± 1.28 × 10 − 6 cm − 1 scattering). Though the WbLS attenuation and scattering coefficients measured are lower than the corresponding values published for ultrapure oils and LAB-PPO liquid scintillator, the material tested attenuates significantly more than water across the blue and green portions of the visible spectrum. This attenuation is markedly stronger at wavelengths under 430 nm. Published by the American Physical Society 2025

47 OTHER INSTRUMENTATION↗

Integrating plant physiology into simulation of fire behavior and effects

Summary Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine‐scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine‐scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process‐based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future.

54 ENVIRONMENTAL SCIENCES↗

Atomic-scale polarization switching in wurtzite ferroelectrics

Ferroelectric wurtzites have the potential to revolutionize modern microelectronics because they are easily integrated with multiple mainstream semiconductor platforms. However, the electric fields required to reverse their polarization direction and unlock electronic and optical functions need substantial reduction for operational compatibility with complementary metal-oxide semiconductor (CMOS) electronics. To understand this process, we observed and quantified real-time polarization switching of a representative ferroelectric wurtzite (Al 0.94 B 0.06 N) at the atomic scale with scanning transmission electron microscopy. The analysis revealed a polarization reversal model in which puckered aluminum/boron nitride rings in the wurtzite basal planes gradually flatten and adopt a transient nonpolar geometry. Independent first-principles simulations reveal the details and energetics of the reversal process through an antipolar phase. Furthermore, this model and local mechanistic understanding are a critical initial step for property engineering efforts in this emerging material class.

36 MATERIALS SCIENCE↗