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At least 325 records · Page 18

Graphene as reusable substrate for bialkali photocathodes

Bialkali photocathodes, such as cesium potassium antimonide (CsK 2 Sb), can generate a high-brightness electron beam using a high-power green laser. These photocathode materials have potential applications in advanced accelerators and electron microscopes. It is known that the quantum efficiency (QE) of these photocathodes is affected severely by their substrates; however, reusability of the substrates is not well known. Here, we use graphene, silicon (Si), and molybdenum (Mo) substrates to evaluate the effects of substrates on the QE of redeposited CsK 2 Sb photocathodes after thermal cleanings. We found the QE of CsK 2 Sb photocathodes redeposited on a graphene substrate after a thermal cleaning at 500 °C remained largely unchanged. On the other hand, the QE of redeposited photocathodes on Si and Mo substrates after thermal cleaning at the same temperature decreased drastically. We used X-ray photoelectron spectroscopy (XPS) to quantitatively evaluate the residues of photocathodes after thermal cleaning at 400 °C and 500 °C. We found that the Sb, K, and Cs are removed by thermal cleaning at 500 °C for the graphene substrate, but all or the majority of these elements remained on the Si and Mo substrates. The results were consistent with our density functional theory (DFT) calculations for the case of Si, which we investigated. Furthermore, our angle-resolved photoemission spectroscopy (ARPES) on graphene indicated that its intrinsic electronic structure is preserved after photocathode deposition and thermal cleaning at 500 °C. Hence, we attributed the difference in amount of photocathode residue to the unique dangling-bond- free surface of inert graphene. Our results provide a foundation for graphene-based reusable substrates for high-QE semiconductor photocathodes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Complementary effects of supplemental feeding and straw retention on winter biodiversity in rice agroecosystems

Rice paddies are both major food-production systems and critical winter habitats for wildlife. In the Civilian Control Zone (CCZ) adjoining the Korean Demilitarized Zone (DMZ), post-harvest interventions such as supplementary grain feeding and straw retention are promoted through agronomic and conservation incentives. These measures differ in ecological scope: feeding provides direct, concentrated energetic subsidies, whereas straw management alters habitat structure and resource bases. We clarified whether these pathways function in complementary or substitutive ways to support resilient, long-term conservation strategies in rice agroecosystems. Using camera traps, we evaluated the effects of three straw treatments (chopped-straw, whole-straw, straw-removed) and supplemental feeding on winter bird and mammal communities across 48 rice fields in the CCZ. Our results demonstrate that feeding produced strong, localized increases in bird abundance and richness, driven mainly by cranes (Grus japonensis and Antigone vipio) and geese (Anser spp.), with limited effects on Shannon diversity or functional structure. Among non-feeding fields, chopped-straw paddies consistently supported higher richness and Shannon diversity than whole-straw or straw-removed fields, while centroid shifts in taxonomic and functional space were modest. Mammal abundance and diversity were largely insensitive to feeding or straw regimes, varying instead with road and forest distance and regional context. Supplemental feeding and straw retention are therefore not interchangeable tools: feeding concentrates a few avian guilds, whereas chopped-straw retention enhances baseline diversity across farmland. Collectively, our findings suggest integrating low-input straw retention with targeted feeding offers a more robust pathway for sustaining winter biodiversity in rice agroecosystems.

60 APPLIED LIFE SCIENCES↗

Control of airborne infectious disease in buildings: Evidence and research priorities

The evolution of SARS-CoV-2 virus has resulted in variants likely to be more readily transmitted through respiratory aerosols, underscoring the increased potential for indoor environmental controls to mitigate risk. Use of tight-fitting face masks to trap infectious aerosol in exhaled breath and reduce inhalation exposure to contaminated air is of critical importance for disease control. Administrative controls including the regulation of occupancy and interpersonal spacing are also important, while presenting social and economic challenges. Indoor engineering controls including ventilation, exhaust, air flow control, filtration, and disinfection by germicidal ultraviolet irradiation can reduce reliance on stringent occupancy restrictions. However, the effects of controls-individually and in combination-on reducing infectious aerosol transfer indoors remain to be clearly characterized to the extent needed to support widespread implementation by building operators. We review aerobiologic and epidemiologic evidence of indoor environmental controls against transmission and present a quantitative aerosol transfer scenario illustrating relative differences in exposure at close-interactive, room, and building scales. We identify an overarching need for investment to implement building controls and evaluate their effectiveness on infection in well-characterized and real-world settings, supported by specific, methodological advances. Finally, improved understanding of engineering control effectiveness guides implementation at scale while considering occupant comfort, operational challenges, and energy costs.

60 APPLIED LIFE SCIENCES↗

Considering computational speed vs. accuracy: Choosing appropriate mesoscale RVE boundary conditions

Modeling a material’s microstructure using continuum theories allows for inspection of the relationship between coarse scale and fine scale behaviors. Computational limits generally require selection of a sub-volume from a bulk sample in order to directly model the microstructure. Boundary conditions are applied to the sub-volume to mimic the excluded bulk material. Appropriate selection of boundary conditions helps effectively determine the appropriate spatial scale required of the sub-volume. Applicable boundary conditions include direct displacement, periodic, and uniform traction. While direct displacement and periodic boundary conditions are commonly used, uniform traction boundary conditions have seen limited use due to rigid body stability issues in simulations of compression or shear deformation. A new application of uniform traction boundary conditions was developed through linear constraint equations, similar to approaches employed by direct displacement and periodic boundary conditions, to quench rigid body motions with minimal interference of the relative deformation of the model. These boundary conditions were tested by compressing several synthetically generated periodic microstructures using the finite element method. Evaluating the effective stiffness along the compression axis, the direct displacement boundary condition produced the stiffest response, whereas the uniform traction boundary condition produced the most compliant. Periodic boundary conditions produced the same response for all volumes analyzed and both the direct displacement and uniform traction boundary conditions trended toward the periodic response as the domain volume increased. Computational performance was also evaluated for each boundary condition using implicit and explicit solvers. Direct displacement boundary conditions presented the lowest computational cost of all of the boundary conditions followed by periodic then uniform traction. The computational expense of periodic and uniform traction boundary conditions limited the viable spatial scale and mesh resolutions able to be simulated. Selection of appropriate boundary conditions for specific uses need to be a balance between allowable computational expense and accuracy of the method. Techniques for evaluating which boundary conditions to use are discussed.

42 ENGINEERING↗

Effect of Cultivation Conditions on the Bioconversion of 4-Hydroxybenzoic Acid in Two White-Rot Fungi

White-rot fungi (WRF) are the most efficient organisms for lignin degradation in nature. A recent study has also shown the ability of WRF in funneling lignin-derived aromatics, including 4-hydroxybenzoic acid (4HBA) and vanillic acid, to central metabolism. However, it is unknown how the cultivation conditions affect the conversion of lignin-derived aromatic compounds. To address this, we performed multi-omic analyses and tracked the conversion of 4HBA in different cultivation conditions in two white-rot fungi: Trametes versicolor and Ceriporiopsis subvermispora. Specifically, we evaluated the effect of static and agitation cultivation conditions in the absence and the presence of antioxidants on fungal performance. We found that the comparison between static and agitation has the higher number of differentially expressed genes or protein abundances at the transcriptomic and proteomic levels, respectively, compared to the presence or the absence of antioxidants. Gene mapping on the enzymatic steps of the proposed 4HBA conversion pathway revealed that agitation causes upregulation of several oxidase genes such as aldehyde dehydrogenases, aldehyde oxidases, and hydroxylases in both fungi. Time-course experiments including 4HBA and cellobiose as carbon sources showed that T. versicolor exhibited higher 4HBA conversion levels in agitation (~110% more conversion, compared to static cultivation conditions) and in the presence of antioxidants (~10% more conversion, compared to the treatments without antioxidants). Interestingly, these trends were not found in C. subvermispora, suggesting different carbon metabolism in both species. Our findings are fundamental to better understand carbon sequestration from lignin in WRF, which will be key for future applications in the lignin valorization field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Effect of heat treatment on creep behavior of 316 L stainless steel manufactured by laser powder bed fusion

The objective of this study is to understand the thermal stability of microstructure and its effect on the creep behavior of additively-manufactured 316L stainless steel (AM 316L SS). Creep specimens were fabricated from rods printed by a laser powder bed fusion process. Six different heat treatments, namely 650 °C/1 h, 700 °C/1 h, 750 °C/1 h, 800 °C/1 h, 900 °C/1 h and 1050 °C/1 h were applied to the creep specimens. The heat-treated specimens were creep-tested under the same condition, 550 °C/275 MPa to evaluate the effect of post-build heat treatment on the creep behavior of AM 316L SS. In the temperature range of 650-750 °C, dislocation density within cells, and cell size and wall thickness were affected by the heat treatment, while elemental segregation at boundaries remained unchanged and Mn-enriched Si oxide particles remained stable. In the temperature range of 750-900 °C, concurrent changes were observed in dislocation cell structures, elemental segregation and oxide particles. The 1050 °C-heat treatment removed cell structures and boundary solute segregations, leading to formation of equiaxed grains; Mn-enriched Si oxide particles in the as-built specimen were replaced by more stable Mn-enriched Cr oxides. The creep life of AM 316L SS increased after the heat treatment at 650 °C and then decreased with increasing temperature up to 900 °C where cell/subgrain structures still existed. The creep rate and creep elongation followed an opposite trend. The creep rate can be correlated with the structural parameters of cell/subgrain size and cell wall/boundary thickness and can be rationalized by different strengthening mechanisms of dislocation cells and subgrains. The heat treatment affected strongly the primary and secondary creep but had a minimal effect on the tertiary creep of AM 316L SS.

316L stainless steel↗

Operation Upshot-Knothole

A thundering boom and sheet of fire announced a dramatic, once in a lifetime event – the firing of a nuclear projectile from a 280 mm cannon. Travelling seven miles downrange, the projectile detonated 500 feet over the Nevada Test Site’s Frenchman Flat with a force of fifteen kilotons. Although the test was successful, the massive cannon, designed for tactical battlefield use, had a critical flaw. It was too large and cumbersome for mobile combat. The cannon test, codenamed Grable, was part of Operation Upshot-Knothole, the fourth test series conducted in Nevada. Beginning with the Annie test on March 17, 1953, and concluding with the Climax test on June 4th, the Operation consisted of three airdrops, seven tower detonations, and the one artillery shot. As with previous Nevada tests, the demarcation between the weapon development series, Upshot, and the DOD effects tests, Knothole, was blurred. All eleven tests generated data in support of weapon development as well as tactical battlefield applications. During Upshot-Knothole, the University of California Radiation Laboratory (UCRL), conducted its first ever tests, Ruth and Ray. Although neither test was successful, these failures, along with another a year later at Operation Castle, provided the new laboratory with design data leading to future successful tests. The Federal Civil Defense Administration (FCDA) participated in a test series with the general goal of preparing for societal recovery from a nuclear attack. Known as Operation Doorstep, the FCDA’s experiments evaluated the effects of a nuclear attack on food supplies, housing and urban structures, and even a copse of trees transplanted from nearby Mt. Charleston. A contingent of the press witnessed test Annie from an outcropping of rocks, subsequently named News Nob. The presence of the news media, along with the FCDA’s participation, marked a fundamental change in the Nevada test program - a change that that now included the general populace, whose survival was, of course, the rationale for testing. The Department of Defense continued and expanded its Desert Rock exercises of troop exercises, helicopter operations, and evaluation of blast damage to military aircraft, tanks, and guns. Annie, Nancy, Badger, Simon, Encore, and Grable involved larger numbers of personnel than the other five shots. Below is an edited and condensed account of Desert Rock activities compiled by the Defense Threat Reduction Agency.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Molecular-Scale Considerations of Enhanced Oil Recovery in Shale

With only less than 10% recovery, the primary production of hydrocarbon from shale reservoirs has redefined the energy equation in the world. Similar to conventional reservoirs, Enhanced Oil Recovery (EOR) techniques could be devised to enhance the current recovery factors. However, shale reservoirs possess unique characteristics that significantly affect the fluid properties. Therefore, we are adopting a molecular simulation approach that is well-suited to account for these effects to evaluate the performance of three different gases, methane, carbon dioxide and nitrogen, to recover the hydrocarbons from rough pore surfaces. Our hydrocarbon systems consists of either a single component (decane) or more than one component (decane and pentane). We simulated cases where concurrent and countercurrent displacement is studied. For concurrent displacement (injected fluids displace hydrocarbons towards the production region), we found that nitrogen and methane yielded similar recovery; however nitrogen exhibited a faster breakthrough. On the other hand, carbon dioxide was more effective in extracting the hydrocarbons when sufficient pressure was maintained. For countercurrent displacement (gases are injected and hydrocarbons are produced from the same direction), methane was found to be more effective, followed by carbon dioxide and nitrogen. In all cases, confinement reduced the recovery factor of all gases. This work provides insights to devise strategies to improve the current recovery factors observed in shale reservoirs.

04 OIL SHALES AND TAR SANDS↗

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets: NASA GEDI LiDAR-derived biomass and Mexico’s National Forest and Soil Inventory (INFyS). Our results showed that models trained on INFyS consistently outperformed those trained on GEDI, highlighting limitations in GEDI’s reliability in biomass estimates within this study region. Furthermore, the integration of Sentinel-2 and PALSAR-2 provided improved predictions compared to single-sensor models, particularly when combined with temporally explicit yearly statistics. The best-performing model, which was trained on INFyS data, and considered both Sentinel-2 and PALSAR-2 yearly statistics, as well as topographic variables, achieved an R2 of 0.64, RMSE of 51.10 Mg/ha, and relative RMSE (rRMSE) of 58.69%. Explainable ML analysis identified Sentinel-2 spectral indices and topographic features as key predictors, while PALSAR-2 metrics provided complementary information, partially mitigating saturation effects in high-biomass areas. Specifically, integrating both sensors substantially improved AGB estimation in high biomass forest (≥200 Mg/ha), yielding 98% gains over optical-only model, with resulting estimates exceeding GEDI L4B by 29% and ESA-CCI-BIOMASS by 174%. Terrain-stratified analysis indicated close agreement with GEDI in low-slope areas, with increasing divergence as slope steepness increased, while estimates remained consistently higher than ESA-CCI-BIOMASS across all slope classes. The proposed approach advances multi-sensor fusion and temporal feature engineering for AGB mapping using open-access satellite datasets, providing a scalable and reproducible framework for annual biomass monitoring in topographically complex mountainous forests. The resulting 25 m resolution biomass product has the potential to provide spatially detailed information for forest monitoring and may support applications in carbon accounting and forest management.

54 ENVIRONMENTAL SCIENCES↗

Unlocking hidden information in sparse small-angle neutron scattering measurements

Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.

Small angle neutron scattering↗

A Comparative Study of Direct and Indirect Additive Manufacturing Approaches for the Production of a Wind Energy Component

Additive manufacturing (AM) was developed in the 1980s to create three-dimensional prototypes through layer-wise approaches to fabrication. Since then, these approaches have seen improvements in both materials and processing technologies. To date, there are now 7 types of additive manufacturing processes and hundreds of materials, which can be directly printed – going directly from digital design to fabricated components. In this project, Oak Ridge National Laboratory (ORNL), Vestas Wind Systems, and The National Renewable Energy Laboratory (NREL) collaborated to evaluate the effectiveness of state-of-the-art large-scale AM processes in the production of a structural component for use in a wind turbine nacelle, through both direct and indirect manufacturing approaches. Here, experienced AM design engineers detail techniques for AM design, including topology optimization (TO), support minimization, reverse engineering, and techniques for mitigating poor interlaminar performance. Fabrication of the components is presented, including printing parameters and postprocessing, and followed with full-scale component testing by a 3rd party testing laboratory. To evaluate the potential of the developed approaches, a complete techno-economic analysis is provided which evaluates the cost of these techniques given current and near to long-term projections of AM system capabilities.

17 WIND ENERGY↗

Applications of fuzzy logic and best-worst method for tritium sensor selection

Accurate assessment of tritium as a fuel source is critical in fusion reactions, necessitating effective sensor evaluation methods. This study investigates a multi-criteria decision-making framework for selecting tritium sensors, integrating fuzzy logic to enhance decision quality. Initial attempts at applying fuzzy logic were found to be too elementary and failed to capture the complexity of multi-criteria selection; this prompted a refined approach that incorporated expert insights and advanced ranking techniques for sensor evaluation. The research used a two-stage methodology. In the first stage, important criteria and sub-criteria for sensor performance were identified and defined. These criteria were then weighted and scored using a fuzzy best-worst method, drawing upon expert opinions to ensure relevance and validity. The second stage involved interpreting information about varying sensors to rank them based on their overall criteria scores, encouraging the selection of the most suitable options. The result of the study is a proposed method for effective sensor selection in fusion reactors, which in turn will significantly improve the reliability of tritium monitoring in fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Revealing the complex chemistry of grain boundaries in K-doped BaFe 2 As 2 with atom probe tomography

Iron-based superconductors have attractive properties for high-field applications, but there is a lack of understanding of the effect of grain boundary chemistry on the in-field performance. The near atomic-scale resolution, ppm sensitivity and 3D analysis offered by atom probe tomography make it a powerful tool to investigate the nanoscale structure and chemistry of these defects in fine-grained K-doped BaFe 2 As 2 samples. A computational method to systematically extract and compare the Gibbsian interfacial excess of chemical species across grain boundaries has been explored in this work. The robustness of the method has been tested by evaluating the effects of selected variables on simulated APT datasets. The accuracy and precision of the calculated Gibbsian interfacial excess were found to be stable over a range of analysis conditions: varying grain boundary widths and detection efficiencies, spatial precisions below 1.5 nm, and bin widths between 1.2 and 1.6 nm. For the K-doped BaFe 2 As 2 samples studied, segregation of As, Ba, K and impurities of O, Na, and Sb were found at grain boundaries. The Gibbsian excess values were found to vary widely between different boundaries, showing the complexity of the grain boundary chemistry in this material. Possible links between the observed critical current density (Jc) of these samples and their nano- and micro-structure have also been investigated and discussed.

36 MATERIALS SCIENCE↗

Adsorptive denitrogenation of model aviation fuel using mesoporous silica in a packed bed adsorption system

This study aims to understand the effects of system process parameters such as flow rate, adsorbent particle size, and use of recycled adsorbent on denitrogenation performance of a model fuel using mesoporous silica gel. The goal is to reduce the nitrogen content of the model fuel from 1500 parts per million to single-digit ppm to meet ASTM specifications for drop-in fuels. This work was done with the intent of applying adsorptive denitrogenation to sustainable aviation fuel (SAF) product fractions produced via hydrothermal liquefaction (HTL). The adsorption performance of the silica is evaluated via packed column breakthrough data, with data generated from collecting from the column outlet and quantifying nitrogen content via gas chromatography. Select experiments use a significantly larger (2.5x column diameter and length) column to demonstrate linear scalability of the process. Thermogravimetric analysis data is collected to evaluate the effects of thermal calcination as a sorbent regeneration method. Effects of a more complex feed are also investigated using a known reference fuel with additional added nitrogen containing compounds. The results presented in this work successfully demonstrate up to 99.8 % removal of NCCs from a model fuel fraction at an original NCC concentration of approximately 1500 ppm to single-digit parts per million after treatment. We also examine calcination of sorbent materials to remove the adsorbed species to enable sorbent reuse and minimize waste generation and show that the calcined material can be reused up to 5 cycles with reduced adsorption capacity. Overall, this work indicates that adsorptive denitrogenation using silica gel is a viable solution to enable the integration of HTL-derived aviation fuels into existing fuel infrastructure.

Adsorption techniques↗

Optimal load attachment of a deeply embedded ring anchor in clay

A Deeply Embedded Ring Anchor (DERA) system has been developed as a cost-effective solution for mooring arrays of floating offshore wind turbines (FOWTs) to the seabed. The DERA boasts several key features, including its versatility in various soil types, compact size, compatibility with diverse mooring systems, multi-line potential, and robust performance even under unintentional loading conditions. While prior preliminary studies have provided valuable insights into how the DERA can enhance cost-effectiveness by offering a high load capacity, these studies have predominantly focused on optimizing anchor performance under translational horizontal and vertical loading. However, to design the DERA optimally, we must also consider its ability to handle inclined loading conditions in addition to lateral and axial loadings. Due to its shorter length compared to a conventional caisson, the DERA has less resistance to moments, making it more sensitive to horizontal load capacity and the optimal load attachment depth concerning load angle. For this reason, our study introduces an analytical approach to evaluate the effects of inclined loading on anchor performance, utilizing the previously validated upper bound plastic limit analysis (PLA) method. In investigating the optimal load attachment of the DERA, this paper conducts a parametric study to analyze how factors such as load attachment depth, anchor aspect ratio, and load inclination affect the DERA’s load capacity. Our findings indicate that PLA can serve as a valuable analytical tool for assessing the ultimate load capacity of the DERA, particularly under inclined loading conditions.

42 ENGINEERING↗

Revisiting Structural and Electromechanical Properties of the Lead-free (K,Na)NbO 3 High-Piezoelectric Material

Having lead-free systems with excellent piezoelectric responses is crucial to the development of environmentally friendly electromechanical applications. In this work, we build an effective Hamiltonian model to explore the promising (K x Na 1–x )NbO 3 system, whose rich phase diagram near x = 50% remains poorly understood meanwhile exhibiting a colossal effective piezoelectric response. Thanks to the numerical implementation of this effective Hamiltonian scheme into a Monte Carlo Metropolis algorithm, we reveal striking features. First, a long-period state can be the ground state at low temperatures for some concentrations while only a short-period conventional polar ground state exists for larger x. Second, the electric field-driven transformation, via a first-order transition, of this long-period state into a short-period polar state creates large electromechanical strains (on the order of the percent) and is likely the origin of the colossal piezoelectric response reported in KNN, for which we evaluate an effective piezoelectric coefficient of several thousands of pC/N.

(K,Na)NbO3↗

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 μS/cm) and the mean precision of all other sensors combined (9.12 μS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

54 ENVIRONMENTAL SCIENCES↗

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field↗