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At least 73 records · Page 4

Fine-Tuning Microporosity of Crystalline Vanadomolybdate Frameworks for Selective Adsorptive Separation of Kr from Xe

Selective adsorptive capture and separation of chemically inert krypton (Kr) and xenon (Xe) noble gases with very low ppmv concentrations in air and industrial off-gases constitute an important technological challenge. Here, using a synergistic combination of experiment and theory, the microporous crystalline vanadomolybdates (MoVO x ) as highly selective Kr sorbents are studied in detail. By varying the Mo/V ratios, we show for the first time that their one-dimensional (1D) pores can be fine-tuned for the size-selective adsorption of Kr over the larger Xe with selectivities reaching >100. Using extensive electronic structure calculations and grand canonical Monte Carlo simulations, the competition between Kr uptake with CO 2 and N 2 was also investigated. As most materials reported so far are selective toward the larger, more polarizable Xe than Kr, this work constitutes an important step toward robust Kr-selective sorbent materials. Furthermore this work highlights the potential use of porous crystalline transition metal oxides as energy-efficient and selective noble gas capture sorbents for industrial applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Unlocking enhanced gas capture via core scrambling of porous-organic cages

The demand for low-cost, low-energy, and highly selective gas capture and separations is an ongoing driver of porous material development. Porous liquids have been identified as a promising gas separation material by creating permanent porosity in inorganic solvents through inclusion of nanoporous materials that sterically exclude solvent from their internal porosity. Among the nanoporous materials that can be used to form porous liquids, porous-organic cages (POCs) have been one of the most popular due to the inherent tunability of POCs. “Scrambled” POCs with varying functionalities on the POC vertices have been developed and incorporated into porous liquid compositions, increasing their gas adsorption capacity. An unexplored avenue to tailor the properties of porous liquids is through scrambling the functionality of the core of the POC. Here, therefore, we have synthesized a new POC, a CC3-OH derivative with scrambled hydroxides on the core and evaluated the impact on the CO 2 uptake capacity in silicon oil-based porous liquids. Core scrambling of the POC resulted in a twofold increase CO 2 adsorption capacity in the porous liquid, an emergent property that is a dramatic increase beyond a linear combination of the gas adsorption capacity of the neat solvent and the POC. Density functional theory modeling of the CC3 POC and its hydroxide-based derivatives identified that free rotation of the linker hydroxide allowed for forced interaction between the CO 2 molecule and the hydroxide in the pore window. Solvation of the POC may release scrambled core hydroxides from intramolecular bonding with a neighboring imine, allowing for increased gas uptake in the porous liquid over the neat POC. These results identify a key structural relationship of POCs that enables emergent properties in porous liquids and can guide future development of liquid phase gas capture and separation materials for environmental and industrial applications.

Gas capture↗

Metal-organic frameworks as effective sensors and scavengers for toxic environmental pollutants

Abstract Metal-organic frameworks (MOFs) constructed from a rich library of organic struts and metal ions/clusters represent promising candidates for a wide range of applications. The unique structure, porous nature, easy tunability and processability of these materials make them an outstanding class of materials for tackling serious global problems relating to energy and environment. Among them, environmental pollution is one aspect that has increased at an alarming rate in the past decade or so. With rapid urbanization and industrialization, toxic environmental pollutants are constantly released and accumulated leading to serious contamination in water bodies and thereby having adverse effects on human health. Recent studies have shown that many toxic pollutants, as listed by the World Health Organization and the US Environmental Protection Agency, can be selectively detected, captured, sequestered and removed by MOFs from air and aquatic systems. Most of these sensing/capture processes in MOFs are quantifiable and effective for even a trace amount of the targeted chemical species. The functional sites (ligands and metals) play a critical role in such recognition processes and offer an extensive scope of structural tunability for guest (pollutants, toxic entities) recognition. Whereas on the one hand, the underlying mechanisms governing such sensing and capture are important, it is also crucial to identify MOFs that are best suited for commercial applications for the future. In this review article, we provide an overview of the most recent progress in the sensing, capture and removal of various common toxic pollutants, including neutral and ionic, inorganic and organic species, with brief discussions on the mechanism and efficacy of selected MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Capture Cavities for the CW Polarized Positron Source Ce+BAF

The initial design of the capture cavities for a continuous wave (CW) polarized positron beam for the Continuous Electron Beam Accelerator Facility (CEBAF) up-grade at Jefferson Lab is presented. A chain of standing wave multi-cell copper cavities inside a solenoid channel are selected to capture positrons in CW mode. The cavity shunt impedance is surveyed by tuning the cavity geometry while considering accommodating large phase space distribution positron beams with large beam pipe radius while ensuring a large enough passband mode separation. The RF field wall loss power and maximum wall loss power density are considered in cavity and waveguide design. A range of design parameters are given for larger system optimization when the capture cavities are considered together with thermal calculation and beam dynamics in next phase of work.

Wang, S.↗

A customized MOF-polymer composite for rapid gold extraction from water matrices

With the fast-growing accumulation of electronic waste and rising demand for rare metals, it is compelling to develop technologies that can promotionally recover targeted metals, like gold, from waste, a process referred to as urban mining. Thus, there is increasing interest in the design of materials to achieve rapid, selective gold capture while maintaining high adsorption capacity, especially in complex aqueous-based matrices. Here, a highly porous metal-organic framework (MOF)–polymer composite, BUT-33–poly(para-phenylenediamine) (PpPD), is assessed for gold extraction from several matrices including river water, seawater, and leaching solutions from CPUs. BUT-33–PpPD exhibits a record-breaking extraction rate, with high Au3+ removal efficiency (>99%) within seconds (less than 45 s), a competitive capacity (1600 mg/g), high selectivity, long-term stability, and recycling ability. Furthermore, the high porosity and redox adsorption mechanism were shown to be underlying reasons for the material’s excellent performance. Given the accumulation of recovered metallic gold nanoparticles inside, the material was also efficiently applied as a catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Octane Gasoline from Lignocellulosic Biomass via Syngas and Methanol/Dimethyl Ether Intermediates (2021 State of Technology)

The 2021 state of technology (SOT) assessment for the indirect liquefaction (IDL) of lignocellulosic biomass to high-octane gasoline (HOG) via methanol and dimethyl ether (DME) intermediates details the techno-economic analysis (TEA) results and technical progress of the pathway since the 2020 SOT report. A detailed process description and collection of underlying assumptions is given the 2015 design report. In 2021, research efforts rigorously quantified the selectivity of DME to aromatic compounds. As a result, the overall carbon selectivity to hydrocarbon products was updated based upon new findings. Additionally, research conducted over the past few years resulted in successful lower temperature regeneration of NREL's Cu/BEA catalyst with favorable implications on catalyst longevity. Discussions with an engineering firm resulted in an update to the excess air requirement for process combustors (including the char combustor, tar reformer combustor, and catalyst regenerator) in which excess air was reduced from 20% excess to 10%. The cumulative effect of the above efforts was used to calculate a minimum fuel selling price for the modeled pathway. Sensitivity cases examining federal carbon tax credits from CO 2 capture, product selectivity and yield, catalyst lifetime, and other key financial and process parameters were also considered in this assessment.

09 BIOMASS FUELS↗

Solution and Active Site Speciation Drive Selectivity for Electrocatalytic Reactive Carbon Capture in Diethanolamine over Ni–N–C Catalysts

Direct conversion of captured forms of carbon, or reactive carbon capture (RCC), presents an opportunity to reduce the energy intensity and cost of direct CO 2 utilization from dilute sources. While amine-based sorbents effectively capture CO 2 , their use for RCC presents numerous challenges with typical pure metal catalysts used for electrochemical CO 2 reduction (CO 2 R). Here, using both theory and experiments, we find that Ni–N–C single atom catalysts are effective for RCC conversion to CO using a diethanolamine sorbent, in contrast to pure metal catalysts. Computational analysis reveals that RCC can proceed directly through direct reduction of the sorbent-CO 2 adduct or indirectly by C–N bond breaking facilitating CO 2 adsorption and subsequent reduction. We find that the latter mechanism is most prevalent at low overpotentials where we experimentally observe RCC selectivity. We also find experimentally that the rate of CO production for RCC with Ni–N–C catalysts can exceed pure bicarbonate solutions at intermediate sorbent concentration (0.1–0.5 M DEA) under dilute (10–25%) streams of CO 2 at low overpotentials. The coordination environment of Ni sites and the solution speciation influence their RCC activity, with changes in protonation to coordinating N/C atoms resulting in changing the RCC mechanism and consequent activity. In situ X-ray absorption spectroscopy and computational analysis reveal restructuring under RCC conditions due to hydrogen coadsorption with DEA that limits the stability of Ni–N–C catalysts. This work highlights the importance of carefully controlling the catalyst and solution environment to achieve active and stable RCC electrocatalysis.

Chemistry↗

Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0

Abstract. Fire is a fundamental part of the Earth system, with impacts on vegetation structure, biomass, and community composition, the latter mediated in part via key fire-tolerance traits, such as bark thickness. Due to anthropogenic climate change and land use pressure, fire regimes are changing across the world, and fire risk has already increased across much of the tropics. Projecting the impacts of these changes at global scales requires that we capture the selective force of fire on vegetation distribution through vegetation functional traits and size structure. We have adapted the fire behavior and effects module, SPITFIRE (SPread and InTensity of FIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime, and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf, and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown, and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown, and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees, and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire-burned area and its effects, which could feed back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m−1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m−1. The results support a positive grass–fire feedback across the region and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗

What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create

A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics.

97 MATHEMATICS AND COMPUTING↗

Disentangling interlayer confinement and pore surface adsorption in functionalized smectites for tunable ethylene gas capture

Smectite-based adsorbents are increasingly being studied as sustainable packaging materials for scavenging ethylene, a plant hormone that accelerates fruit ripening. However, the mechanisms governing their uptake and retention remain poorly understood. Here, to tackle this question we systematically investigate ethylene gas-solid interactions in pristine, acid-activated, and choline-functionalized montmorillonites using a complementary combination of structural, gravimetric, and spectroscopic techniques, including inelastic neutron scattering. We experimentally distinguish ethylene populations associated with interlayer confinement, mesopore, and external surface adsorption. We show that chemical functionalization distinctly controls adsorption pathways: acid activation enhances total uptake by generating mesoporous adsorption sites and promoting partial interlayer intercalation, yielding capacities comparable to those of leading smectite-based adsorbents, while choline functionalization promotes preferential confinement and stabilization of guest molecules within the interlayer galleries. Advanced spectroscopic analysis provides molecular-level insight into confinement environments and interaction strengths. We also establish clear structure-property relationships by correlating uptake values derived from independent techniques, linking chemical modification, accessible adsorption domains, and retention behavior. These findings provide general design principles for tuning gas-solid interactions in functionalized layered silicates and highlight their potential as adaptable platforms for sustainable ethylene gas capture and selective adsorption technologies.

Ethylene adsorption mechanism↗

An electrochemical mesoscale tool for modeling the corrosion of structural alloys by molten salt

Understanding the impact of microstructure on corrosion rates can aid the development of corrosion-resistant alloys for molten salt reactors. Here in this work, we develop an electrochemical phase-field model for capturing the microstructure-dependent corrosion of structural alloys by molten salts. As a demonstration problem, we apply this model to capture the selective depletion of Cr from Ni-Cr grain boundaries during corrosion in molten FLiBe salt. We perform sensitivity analysis and model verification on 1D simulations to confirm that the model predicts diffusion-limited kinetics. The model is validated using 1D, 2D, and 3D simulations against experimental data for Ni-5Cr and Ni-20Cr corrosion in molten FLiBe. The 1D simulations predict the corrosion behavior with reasonable accuracy when using an effective diffusion coefficient that accurately represents the grain boundary diffusion. 2D simulations that represent the grain structure underpredict the corrosion. 3D simulations that represent the grain structure predict the corrosion with reasonable accuracy. The corrosion rate predicted by the 3D simulations is proportional to the average grain size at the alloy/salt interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Functional stimuli-responsive polymers on micro- and nano-patterned interfaces

Micro- and nano-patterned surfaces offer precise control over morphology and chemical composition, enhancing the stability, durability, and functionality of coating materials. When combined with stimuli-responsive polymers, these surfaces gain dynamic adaptability, enabling reversible binding, reusable sensing, and selective molecular capture. Furthermore, while recent review articles have explored various aspects of stimuli-responsive materials, from hydrogel patterns for bioanalytical applications to shape-morphing hydrogels for soft robotics and sensors, a comprehensive review focused on the integration of smart polymers with micro- or nano-patterned interfaces remains absent. This review addresses key surface patterning techniques, including soft lithography, colloidal lithography, and polymer brush photolithography, as well as advances in surface-initiated polymerization methods, such as surface-initiated controlled radical polymerization (SI-CRP). In addition, we discuss recent progress in integrating stimuli-responsive polymers with patterned surfaces to create advanced, functional materials.

Colloidal lithography↗

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CH 3 Radical Generation in Microplasmas for Up-Conversion of Methane

The conversion of methane, CH 4 , into higher value chemicals using low temperature plasmas is challenged by both improving efficiency and selectivity. One path towards selectivity is capturing plasma produced methyl radicals, CH 3 , in a solvent for aqueous processing. Due to the rapid reactions of methyl radicals in the gas phase, the transport distance from production of the CH 3 to its solvation should be short, which then motivates the use of microplasmas. The generation of CH 3 in Ar/CH 4 /H 2 O plasmas produced in nanosecond pulsed dielectric barrier discharge microplasmas is discussed using results from a computational investigation. The microplasma is sustained in the channel of a microfluidic chip in which the solvent flows along one wall or in droplets. CH 3 is primarily produced by electron-impact of and dissociative excitation transfer to CH 4 , as well as CH 2 reacting with CH 4 . CH 3 is rapidly consumed to form C 2 H 6 which, in spite of being subject to these same dissociative processes, accumulates over time, as do other stable products including C 3 H 8 and CH 3 OH. The gas mixture and electrical properties were varied to assess their effects on CH 3 production. CH 3 production is largest with 5% CH 4 in the Ar/CH 4 /H 2 O mixture due to an optimal balance of electron-impact dissociation, which increases with CH 4 percentage, and dissociative excitation transfer and CH 2 reacting with CH 4 , which decrease with CH 4 percentage. Design parameters of the microchannels were also investigated. Increasing the permittivity of the dielectrics in contact with the plasma increased the ionization wave intensity which increased CH 3 production. Increased energy deposition per pulse generally increased CH 3 production as does lengthening pulse length up to a certain point. The arrangement of the solvent flow in the microchannel can also affect the CH 3 density and fluence to the solvent. The fluence of CH 3 to the liquid solvent is increased if the liquid is immersed in the plasma as a droplet or is a layer on the wall where the ionization wave terminates. The solvation dynamics of CH 3 with varying numbers of droplets was also examined. Here, the maximum density of solvated methyl radicals CH 3aq occurs with a large number of droplets in the plasma. However, the solvated CH 3aq density can rapidly decrease due to desolvation, emphasizing the need to quickly react the solvated species in the solvent.

03 NATURAL GAS↗

Reversible parts-per-trillion-level detection of perfluorooctane sulfonic acid in tap water using field-effect transistor sensors

Widespread, persistent and toxic per- and polyfluoroalkyl substances (PFAS) pose a major threat to water systems and human health. Current detection methods are relatively expensive, slow and complex, underscoring the need for more accessible alternatives to meet increasingly stringent PFAS regulations. Here, in this study, we present an ultrasensitive sensing platform for perfluorooctane sulfonic acid detection in tap water with a reporting limit ( ~ 250 parts per quadrillion) lower than the US Environmental Protection Agency’s regulatory standard (4 parts per trillion), using a remote gate field-effect transistor featuring β-cyclodextrin (β-CD)-modified reduced graphene oxide as the sensing membrane. The sensor exhibits excellent selectivity against common inorganic ions, natural organic matter and select organic pollutants in tap water. The reversible and rapid response ( < 2 min) indicates the potential of remote gate field-effect transistor for continuous in-line monitoring. Mechanistic studies using quartz crystal microbalance and molecular dynamics simulations reveal key roles of analyte adsorption and charge properties in sensing performance and offer insights for designing more selective PFAS capture probes.

Wang, Yuqin [University of Chicago, IL (United Sta↗

New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research

In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal–organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding in situ and operando electrochemical stability. Lastly, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. The data support the analyses presented in the article: “Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.” We collected 105 ground-truth biomass samples from four mature commercial fields (>4 years old) covering 92.81 ha. Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS. Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated. This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here. The dataset consists of three comma-separated value (CSV) files: 1. Combine_Groundtruth_Yield_VI_22_23.csv This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons. Rows: 105 observations Columns: Year — Year of observation (2022 or 2023) Field — Field location identifier Sample_number — Unique sample identifier GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare) 2. trainData_GNDVI.csv This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield. Rows: 76 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹) 3. testData_GNDVI.csv This file contains the test dataset used to evaluate model performance. Rows: 29 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹) Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)

Potential yield, yield gap, in-field management, y↗

Simulations of positron injector for Ce+BAF

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. This concept is based on the generation of CW longitudinally polarized positrons by a high-current, polarized electron beam (1 mA, 130‑370 MeV, and 90% longitudinal polarization) that passes through a rotating, water-cooled, tungsten target. The simulation results for the Ce+BAF injector at the Low Energy Recirculator Facility (LERF) are presented, including positron beam generation, capture, energy selection, and acceleration to 123 MeV. The positron yield (or positron current) and longitudinal polarization are calculated considering the longitudinal and transverse CEBAF acceptances (<1% energy spread, <1 mm bunch length and normalized emittance of <100 mm mrad). The impact of target thickness, drive electron beam energy, and transverse size on positron yield within the required emittance limit is evaluated.

Accelerator Physics↗