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Mixed-Flux Techniques for Rational Synthesis and Structural Control in Silver Chalcogenides

The functionality of materials is intrinsically linked to their structures, an axiom encapsulated in the principle of structure-property relationships. The pinnacle of materials design is the tailoring of its structure for a specific function, which requires the ability of rational synthesis and the development of synthesis science. This idea, however, remains elusive for the synthesis of complex extended solids. A major obstacle is the difficulty in using established chemical principles selectively to control reaction paths and favor certain structural patterns over numerous other possible results. In this context, we are developing a synthesis science approach that facilitates the control of the structure and bonding to create new structures. This is achieved by employing a two-component flux consisting of mixed hydroxides and halides as the reaction medium. This enables reaction conditions that allow better control of the structure dimensionality and composition by manipulating the temperature and solvent basicity (via the flux component ratio). Here, we demonstrate the efficacy of this method in controlling their structural motifs to arrive at 23 unreported compositions and 6 unique structure types. These materials are expected to exhibit a broad range of properties, from metallic to semiconducting, with calculations suggesting the potential for emergent phenomena such as Dirac semimetals. The reaction paths afforded by these mixed fluxes establish a direct correlation between the synthetic variables and properties, providing significant insight into a broadly applicable approach for new materials.

Zhou, Xiuquan [Argonne National Laboratory (ANL), ↗

Invited Article: An integrated mid-infrared, far-infrared, and terahertz optical Hall effect instrument

We report on the development of the first integrated mid-infrared, far-infrared, and terahertz optical Hall effect instrument, covering an ultra wide spectral range from 3 cm{sup −1} to 7000 cm{sup −1} (0.1–210 THz or 0.4–870 meV). The instrument comprises four sub-systems, where the magneto-cryostat-transfer sub-system enables the usage of the magneto-cryostat sub-system with the mid-infrared ellipsometer sub-system, and the far-infrared/terahertz ellipsometer sub-system. Both ellipsometer sub-systems can be used as variable angle-of-incidence spectroscopic ellipsometers in reflection or transmission mode, and are equipped with multiple light sources and detectors. The ellipsometer sub-systems are operated in polarizer-sample-rotating-analyzer configuration granting access to the upper left 3 × 3 block of the normalized 4 × 4 Mueller matrix. The closed cycle magneto-cryostat sub-system provides sample temperatures between room temperature and 1.4 K and magnetic fields up to 8 T, enabling the detection of transverse and longitudinal magnetic field-induced birefringence. We discuss theoretical background and practical realization of the integrated mid-infrared, far-infrared, and terahertz optical Hall effect instrument, as well as acquisition of optical Hall effect data and the corresponding model analysis procedures. Exemplarily, epitaxial graphene grown on 6H-SiC, a tellurium doped bulk GaAs sample and an AlGaN/GaN high electron mobility transistor structure are investigated. The selected experimental datasets display the full spectral, magnetic field and temperature range of the instrument and demonstrate data analysis strategies. Effects from free charge carriers in two dimensional confinement and in a volume material, as well as quantum mechanical effects (inter-Landau-level transitions) are observed and discussed exemplarily.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-E-T-191: First Principle Calculation of Quantum Yield in Photodynamic Therapy

Purpose: We present a first-principle method to calculate the spin transfer efficiency in oxygen induced by any photon fields especially in MeV energy range. The optical pumping is mediated through photosensitizers, e.g., porphyrin and/or ensemble of quantum dots. Methods: Under normal conditions, oxygen molecules are in the relatively non-reactive triplet state. In the presence of certain photosensitizer compounds such as porphyrins, electromagnetic radiation of specific wavelengths can excite oxygen to highly reactive singlet state. With selective uptake of photosensitizers by certain malignant cells, photon irradiation of phosensitized tumors can lead to selective killing of cancer cells. This is the basis of photodynamic therapy (PDT). Despite several attempts, PDT has not been clinically successful except in limited superficial cancers. Many parameters such as photon energy, conjugation with quantum dots etc. can be potentially combined with PDT in order to extend the role of PDT in cancer management. The key quantity for this optimization is the spin transfer efficiency in oxygen by any photon field. The first principle calculation model presented here, is an attempt to fill this need. We employ stochastic density matrix description of the quantum jumps and the rate equation methods in quantum optics based on Markov/Poisson processes and calculate time evolution of the population of the optically pumped singlet oxygen. Results: The results demonstrate the feasibility of our model in showing the dependence of the optical yield in generating spin-singlet oxygen on the experimental conditions. The adjustable variables can be tuned to maximize the population of the singlet oxygen hence the efficacy of the photodynamic therapy. Conclusion: The present model can be employed to fit and analyze the experimental data and possibly to assist researchers in optimizing the experimental conditions in photodynamic therapy.

60 APPLIED LIFE SCIENCES↗

Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines

Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. An obstacle to the development of M protein–based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.

60 APPLIED LIFE SCIENCES↗

Review of CTF's Fuel Rod Modeling Using FRAPCON-4.0's Centerline Temperature Predictions

Coolant Boiling in Rod Arrays-Two Fluid (COBRA-TF), or CTF1, is a nuclear thermal hydraulic subchannel code used throughout academia and industry. CTF's fuel rod modeling is originally developed for VIPRE code. Its methodology is based on GAPCON and FRAP fuel performance codes, and material properties are included from MATPRO handbook. This work focuses on review of CTF's fuel rod modeling to address shortcomings in CTF's temperature predictions. CTF is compared to FRAPCON which is U.S. NRC's steady-state fuel performance code for light-water reactor fuel rods. FRAPCON calculates the changes in fuel rod variables and temperatures including the effects of cladding hoop strain, cladding oxidation, hydriding, fuel irradiation swelling, densification, fission gas release and rod internal gas pressure. It uses fuel, clad and gap material properties from MATPRO. Additionally, it has its own models for fission gas release, cladding corrosion and cladding hydrogen pickup. It allows finite difference or finite element approaches for its mechanical model. In this study, FRAPCON-4.0 is used as a reference fuel performance code. In comparison, Halden Reactor Data for IFA432 Rod 1 and Rod 3. CTF simulations are performed in two ways; informing CTF with gap conductance value from FRAPCON, and using CTF's dynamic gap conductance model. First case is chosen to show temperature is predicted correctly with CTF's models for thermal and cladding conductivities once gap conductance is provided. Latter is to review CTF's dynamic gap conductance model. These Halden test cases are selected to be representative of cases with and without any physical contact between fuel-pellet and clad while reviewing functionality of CTF's dynamic gap conductance model. Improving the CTF's dynamic gap conductance model will allow prediction of fuel and cladding thermo-mechanical behavior under irradiation, and better temperature feedbacks from CTF in transient calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument

The quality of exposure assessment is a major determinant of the overall quality of any environmental epidemiology study. The use of biomonitoring as a tool for assessing exposure to ubiquitous chemicals with short physiologic half-lives began relatively recently. These chemicals present several challenges, including their presence in analytical laboratories and sampling equipment, difficulty in establishing temporal order in cross-sectional studies, short- and longterm variability in exposures and biomarker concentrations, and a paucity of information on the number of measurements required for proper exposure classification. To date, the scientific community has not developed a set of systematic guidelines for designing, implementing and interpreting studies of short-lived chemicals that use biomonitoring as the exposure metric or for evaluating the quality of this type of research for WOE assessments or for peer review of grants or publications. We describe key issues that affect epidemiology studies using biomonitoring data on short-lived chemicals and propose a systematic instrument – the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument – for evaluating the quality of research proposals and studies that incorporate biomonitoring data on short-lived chemicals. Quality criteria for three areas considered fundamental to the evaluation of epidemiology studies that include biological measurements of short-lived chemicals are described: 1) biomarker selection and measurement, 2) study design and execution, and 3) general epidemiological study design considerations. We recognize that the development of an evaluative tool such as BEES-C is neither simple nor non-controversial. We hope and anticipate that the instrument will initiate further discussion/debate on this topic.

54 ENVIRONMENTAL SCIENCES↗

Separation of volatile organic contaminants from water using a direct-contact dehumidifier: An experimental study and modeling

A packed-bed, direct-contact dehumidifier (PB-DCD) has been developed to selectively condense water from a gaseous mixture of organic contaminants. In this process, hot air is humidified by mixing with wastewater vapor in a static mixer and is dehumidified by subcooled fresh water passing through the PB-DCD in a counter-current configuration. The goal of this study is to understand the relationship between various operating parameters and how they affect separation of isopropyl alcohol (IPA) from the gaseous mixture with the purpose of expanding the investigation to other contaminants in the future. The process has been successfully used to separate IPA from wastewater. Different parameters including the concentration of IPA in water, feed temperature, air-to-vapor ratio, and cooling-water-to-vapor mass ratio, as well as residence time were examined to determine their influence on contaminant separation and clean water recovery rate. The Buckingham Pi theorem was applied to reduce the number of studying variables by generating non-dimensional groups. Experiments were performed to determine the relationship between the non-dimensional parameters and model mass transfer in the system. Mass transfer coefficients for multicomponent gaseous mixture condensation in a packed-bed direct contact condenser column are calculated and a modified correlation of mass transfer is developed. The parameters of the mass transfer model are obtained from operating conditions of the PB-DCD, stream conditions and thermodynamic properties. A modified Sherwood correlation is developed to predict IPA separation from a gaseous mixture consisting of air, water, and IPA. The modified Sherwood correlation is applied to successfully predict the Sherwood number with a mean absolute error equal to 6.6 %. According to the experimental results, the maximum IPA separation achieved was 76.3 %, which corresponds to a water recovery rate of 58.7 %.

42 ENGINEERING↗

Community structure and function during periods of high performance and system upset in a full-scale mixed microalgal wastewater resource recovery facility

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine a full-scale, intensive WRRF utilizing mixed microalgae for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (D INVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55 %-80 %) that achieved strict nutrient removal (effluent TP < 0.04 mg·L -1 ) and steady biomass concentration (TSS monthly avg . = 400–700 mg·L −1 ). Operational variables including pH, alkalinity, and influent ammonium (NH 4 + ), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO 2 − accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Altogether, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

HEAT TRANSFER ASPECTS OF TWO PISTON SPLAT QUENCHING

This thesis investigates the heat transfer aspects of the two-piston splat quench system by modifying surface roughness and by using copper and stainless steel platens. In additive manufacturing, specifically selective laser melting (SLM), metal is subjected to a very rapid heating and cooling that produces cooling rates in the range from 105-106 °C/s. This rapid solidification produces microstructures that deviate far from equilibrium. Splat quenching is an experimental method that produces rapidly solidified structures under cooling rates that are comparable to those found in additive manufacturing. The splat quenching approach allows for more efficient testing of the rapid solidification behavior of a wide variety of alloys. In this thesis, two platen characteristics, surface roughness and material thermal conductivity, were examined to determine their role in controlling the heat transfer and the subsequent cooling rate during splat quenching of austenitic stainless steel 316L. To that objective, 5 surface finishes were produced using metallographic techniques, from 7046-203 Å Rms. Copper and 316L stainless steel platen material were used to reach different levels of thermal conductance. The combination of these 2 variables created 10 scenarios, which were examined using, backscatter imaging, secondary imaging, and electron back scatter diffraction. Cooling rates were estimated using cell sizing obtained through electrolytic etching and secondary imaging. This thesis determined that both surface modification and changes in material type had a statistically significant impact on the cell sizes observed. Where material type far outweighed surface roughness in its effect on cell size.

Roze, Jonathan↗

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address the negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.

47 OTHER INSTRUMENTATION↗

Guideline for Characterizing and Evaluating a Candidate Project Site for Solar Thermal Applications

This document presents a structured procedure for characterizing and evaluating candidate project sites for concentrating solar power (CSP) and solar heat for industrial processes (SHIP) applications. The objective is to provide project developers, researchers, and other stakeholders with a consistent, technology-agnostic framework for early-stage site assessment, enabling informed decision-making prior to significant investment in project development. Site selection is a critical factor in project success or failure for both CSP and SHIP projects. Key factors such as solar resource availability, land characteristics, environmental and regulatory constraints, infrastructure availability, and community context are determined by the choice of project site and can materially impact project performance, cost, schedule, and overall viability. This procedure is designed to systematically evaluate these factors, identify potential fatal flaws, and prioritize the most favorable candidate sites for further development. The process begins with rapid screening-level evaluation, using publicly available data to assess solar resource, land availability and suitability, zoning and land-use compatibility, and exclusion zones such as protected lands or sensitive habitats. Sites that meet the minimum screening criteria advance to a more detailed characterization. Subsequent sections of this report provide guidance for a next-level assessment of the most important technical and environmental parameters, including: 1) Solar resource quality, variability, and uncertainty using multiyear datasets and, where appropriate, on-site measurement campaigns; 2) Meteorological conditions such as wind, temperature, extreme weather events, and soiling impacts; 3) Land characteristics including slope, shading, and geotechnical conditions; and 4) Environmental and regulatory considerations, including permitting processes, endangered species, cultural resources, and visual impacts. The procedure also addresses infrastructure and integration considerations, including: 1) Grid interconnection requirements for CSP power generation projects; 2) Electrical and operational integration for SHIP facilities; 3) Water availability, quality, and permitting constraints, which are particularly critical for CSP in arid regions; and 4) Site access, construction logistics, and availability of workforce and supporting services. Recognizing the importance of social and economic context, the procedure includes evaluation of community engagement factors, such as stakeholder sentiment, proximity to sensitive visual receptors, workforce development opportunities, and local economic incentives. The outputs of these assessments are synthesized in a cost and risk evaluation, translating site characteristics into expected impacts on capital cost, operating cost, schedule, and technical risk. This is complemented by screening-level performance modeling, including 8760 simulations and long-term projections, to quantify expected energy or thermal output, assess variability thereof, and support comparison between candidate sites. Finally, the procedure provides high-level guidance on a structured go/no-go decision framework, categorizing sites based on identified risks and constraints, and outlining a clear path forward to feasibility studies and front-end engineering design for viable projects. By standardizing the site characterization process across both CSP and SHIP applications, this guideline aims to: 1) Improve consistency and transparency in early-stage project evaluation; 2) Reduce development risk and avoid investment in nonviable project sites; 3) Support collaboration between developers, researchers, and public agencies; and 4) Accelerate successful deployment of concentrating solar technologies for both power generation and industrial process heat.

14 SOLAR ENERGY↗

Fouling modeling and prediction approach for heat exchangers using deep learning

In this article, we develop a generalized and scalable statistical model for accurate prediction of fouling resistance using commonly measured parameters of industrial heat exchangers. This prediction model is based on deep learning where a scalable algorithmic architecture learns non-linear functional relationships between a set of target and predictor variables from large number of training samples. Here, the efficacy of this modeling approach is demonstrated for predicting fouling in an analytically modeled cross-flow heat exchanger, designed for waste heat recovery from flue-gas using room temperature water. The performance results of the trained models demonstrate that the mean absolute prediction errors are under 10 –4 KW –1 for flue-gas side, water side and overall fouling resistances. The coefficients of determination (R 2 ), which characterize the goodness of fit between the predictions and observed data, are over 99%. Even under varying levels of measurement noise in the inputs, we demonstrate that predictions over an ensemble of multiple neural networks achieves better accuracy and robustness to noise. We find that the proposed deep-learning fouling prediction framework learns to follow heat exchanger flow and heat transfer physics, which we confirm using locally interpretable model agnostic explanations around randomly selected operating points. Overall, we provide a robust algorithmic framework for fouling prediction that can be generalized and scaled to various types of industrial heat exchangers.

42 ENGINEERING↗

Fuel Efficient Speed Optimization for Real-World Highway Cruising

This paper introduces an eco-driving highway cruising algorithm based on optimal control theory that is applied to a conventionally-powered connected and automated vehicle. Thanks to connectivity to the cloud and/or to infrastructure, speed limit and slope along the future route can be known with accuracy. This can in turn be used to compute the control variable trajectory that will minimize energy consumption without significantly impacting travel time. Automated driving is necessary to the implementation of this concept, because the chosen control variables (e.g., torque and gear) impact vehicle speed. An optimal control problem is built up where quadratic models are used for the powertrain. The optimization is solved by applying Pontryagin’s minimum principle, which reduces the problem to the minimization of a cost function with parameters called co-states. The proposed algorithm assumes piecewise constant slopes and speed limits, and it solves the transition vehicle speeds for each junction of such segments. In addition, a method to extract route information from digital maps is presented, which complies with the proposed optimization algorithm. The algorithms are evaluated in simulation, using Autonomie, a simulation tool for vehicle energy consumption modeling. The optimal control trajectory (e.g., torque, gear) is first computed offline. It is then applied in an open-loop fashion in online simulation, using a forward-looking model of the vehicle in Autonomie. Simulation results show over 8% fuel saving for two selected real-world routes.

Simulation and modeling, Optimization, Vehicle net↗

Linking DSC/TGA to Cell Levels: Energetics, Evolved Gases, and Thermal Safety of NMC811‐Graphite Micro‐Cell

Thermochemical characterization of battery materials links intrinsic material properties to decomposition pathways, heat generation, and gas evolution that govern performance and safety. Despite extensive work on NMC811-Graphite, variability across partial configurations and the limited adoption of micro-cell architectures (cathode+anode+electrolyte+separator) hinder robust cell-scale interpretation. Accordingly, this work establishes a bottom-up, component-resolved methodology integrating DSC/TGA, evolved gas analysis (EGA), and in situ XRD to link decomposition pathways and energy release across partial and micro-cell configurations, providing a transferable assessment of safety and stability in emerging chemistries. In separator-free configurations, the gas–solid reaction between cathode-evolved O 2 and anode-leached Li dominates the net heat release (1139 J g −1 ). In contrast, in the micro-cell configuration, the separator hinders O 2 transport and alters the timing and pathways of other reactions, and reduces the net energy release to 618 J g −1 . Energy release was organized into defined temperature windows that provide a framework for a thermodynamic model combining quantified gas evolution with selected decomposition pathways and effective reaction enthalpies to estimate net specific energy release, with agreement between DSC and cell-level tests. Ex situ XPS of heat-treated samples extends post-mortem analysis to thermal-abuse regimes, supporting key pathway elements.

25 ENERGY STORAGE↗

Probing the role of carbon in the interstellar ultraviolet extinction

We probe the role of carbon in the ultraviolet (UV) extinction by examining the relations between the amount of carbon required to be locked up in dust [C/H]{sub dust} with the 2175 A-ring extinction bump and the far-UV extinction rise, based on an analysis of the extinction curves along 16 Galactic sightlines for which the gas-phase carbon abundance is known and the 2175 A-ring extinction bump exhibits variable strengths and widths. We derive [C/H]{sub dust} from the Kramers–Kronig relation which relates the wavelength-integrated extinction to the total dust volume. This approach is less model-dependent since it does not require the knowledge of the detailed optical properties and size distribution of the dust.We also derive [C/H]{sub dust} from fitting the observed UV/optical/near-infrared extinction with a mixture of amorphous silicate and graphite. We find that the carbon depletion [C/H]{sub dust} tends to correlate with the strength of the 2175 A-ring bump, while the abundance of silicon depleted in dust shows no correlation with the 2175 A-ring bump. This supports graphite or polycyclic aromatic hydrocarbon molecules as the possible carrier of the 2175 A-ring bump. We also see that [C/H]{sub dust} shows a trend of correlating with 1/R{sub V}, where R{sub V} is the total-to-selective extinction ratio, suggesting that the far-UV extinction is more likely produced by small carbon dust than by small silicate dust.

79 ASTRONOMY AND ASTROPHYSICS↗

OPTICAL SPECTROSCOPY OF X-RAY-SELECTED YOUNG STARS IN THE CARINA NEBULA

We present low-resolution optical spectra for 29 X-ray sources identified as either massive star candidates or low-mass pre-main-sequence (PMS) star candidates in the clusters Trumpler 16 and Trumpler 14 of the Carina Nebula. Spectra of two more objects (one with an X-ray counterpart, and one with no X-ray counterpart), not originally our targets, but found close (∼3″) to two of our targets, are presented as well. Twenty early-type stars, including an O8 star, seven B1–B2 stars, two B3 stars, a B5 star, and nine emission-line stars, are identified. Eleven T Tauri stars, including eight classical T Tauri stars (CTTSs) and three weak-lined T Tauri stars, are identified. The early-type stars in our sample are more reddened compared to the previously known OB stars of the region. The Chandra hardness ratios of our T Tauri stars are found to be consistent with the Chandra hardness ratios of T Tauri stars of the Orion Nebula Cluster. Most early-type stars are found to be nonvariable in X-ray emission, except the B2 star J104518.81–594217.9, the B3 star J104507.84–594134.0, and the Ae star J104424.76–594555.0, which are possible X-ray variables. J104452.20–594155.1, a CTTS, is among the brightest and the hardest X-ray sources in our sample, appears to be a variable, and shows a strong X-ray flare. The mean optical and near-infrared photometric variability in the V and K{sub s} bands, of all sources, is found to be ∼0.04 and 0.05 mag, respectively. The T Tauri stars show significantly larger mean variation, ∼0.1 mag, in the K{sub s} band. The addition of one O star and seven B1–B2 stars reported here contributes to an 11% increase of the known OB population in the observed field. The 11 T Tauri stars are the first ever confirmed low-mass PMS stars in the Carina Nebula region.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗

AMMT Round Robin 316H HFIR Irradiation Test Matrix and Readiness for Insertion

The Round Robin 316H HFIR-2 irradiation campaign, conducted under the Advanced Materials and Manufacturing Technologies (AMMT) Program, is designed to evaluate the variability in irradiation response of laser powder bed fusion (LPBF) stainless steel (SS)-316H across multiple national laboratories, powder heats, and processing conditions, with comparison to wrought counterparts. A total of 11 materials are intended for irradiation in the High Flux Isotope Reactor (HFIR), targeting two irradiation temperatures (400°C and 600°C) and one level of irradiation damage (2 dpa). This irradiation campaign utilizes the standardized general tensile (GENTEN) capsule design to accommodate subsized tensile specimens of these materials. Thermal analyses were performed to ensure appropriate temperature control by design and uniformity within the capsules. All the capsules for this irradiation except one have been successfully assembled, welded, and tested and are ready for HFIR insertion. The last capsule requires re-build following a failed weld. All eight capsules are intended to be inserted in HFIR cycle 517, which is scheduled to start September 8, 2026. This report summarizes the design, material selection, and readiness for insertion of the capsules.

36 MATERIALS SCIENCE↗

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