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At least 667 records · Page 37

Analysis of Coronado State Historic Site artifacts using X-rays

Two historic-period metal artifacts were provided by the New Mexico Historic Sites to Los Alamos National Laboratory for non-destructive analysis. The artifacts were a crossbow quarrel (or bolthead) and a reliquary pendant recovered from Kuaua Pueblo (also known as the Coronado Historic Site) in Bernalillo, NM. The quarrel is a heavily patinated metal that had been flattened due to compressive forces. The pendant consisted of a metal casing that had previously surrounded two center gemstones on the front and rear face of the pendant. The gemstone in the rear setting had fractured and was displaced from the setting, leaving only a small, loose fragment within the pendant for study. The front gem appeared to be very dark, near-black in color, and the fragment of the rear gem was a bright red color. The artifacts were analyzed to ascertain their composition and glean insight into their provenance using the following X-ray techniques: X-ray computed tomography, confocal micro X-ray fluorescence, and X-ray diffraction. Infrared spectroscopy and electron microscopy were used on selected areas. Ultraviolet Raman spectra were collected on the two gems and the pendant. The metal material of the artifacts was found to be primarily composed of copper. The gems in the pendant were composed of manganese (front gem) and calcium (side gem).

36 MATERIALS SCIENCE↗

Puck Loop Seal (Final Project Technical Report)

Sandia National Laboratories (SNL) is advancing technical capabilities used in passive loop seals. The “Puck” seal used a set of International Atomic Energy Agency (IAEA) requirements for new passive loop seals published in 2020 as a design guide. The seal is based on an oxygen-sensitive inner mixture encased in an oxygen-impermeable shell, is monolithic rather than two-part, incorporates self-capturing wire features, contains colored water beads and bubbles formed during processing as unique identifiers (UIDs), and visually indicates tamper (whether from seal body penetration or from seal wire removal) by irreversibly changing the seal body from multi-colored to black. This paper will provide details on the design, development, and testing of Puck seal prototypes.

42 ENGINEERING↗

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Smokeless Chimney using Smoke Opacity as a Combustion Control Parameter (CRADA Final Report)

If operated poorly, wood burning heaters can produce large amounts of particulate matter (PM). Although several instruments are available to monitor PM, most require dilution air and are unable to sample directly from a flue due to the high PM concentrations and temperatures. Opacity sensors can measure color, opacity and smoke density from wood heater stacks. They operate by transmitting a light beam through the emission source and measuring the amount of light intensity lost (opacity) and light not reflected (color). Although opacity sensors are used in several areas, none have been thoroughly evaluated or optimized for measuring smoke from wood heaters.

47 OTHER INSTRUMENTATION↗

Materials for Energy Management across the Electromagnetic Spectrum (MEMES) (LDRD Report)

Electrification of the United States has been a major driver of economic growth, powering industrialization, modern manufacturing, and the digital economy. Today, further economic and environmental benefits can be realized by improving the energy efficiency of the technologies we have come to rely on. This project focused on enhancing the energy efficiency of two cornerstone technologies of modern society: electronic displays and building climatization. While these two technologies operate in different parts of the electromagnetic spectrum (the visible and infrared, respectively), they share a common potential technological solution: electrically-driven displays that change reflectivity. In this work, we developed the first multipixel multicolor reflective display that achieves multi-colorization with fast-changing structural color. In the course of this demonstration, we quantified the structural changes that occur across different time and length scales and resolved device sealing issues, enabling operation of these devices over months (as opposed to days previously). We furthermore developed two reflectivity changing devices in the infrared and demonstrated how these technologies can be used to reduce climatization demands for both smart window and smart wall technologies. Implementing such a device in a scaled down mock room resulted in 10 degree Celsius change.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Properties for Microsample Identification

A study was conducted to determine if individual particle characteristics could be used to identify particles of interest, sub-samples, from bulk post-detonation debris. Three archived post-detonation debris samples were used for this effort. Particles from these samples were identified as active (produced fission tracks), and inactive (did not produce fission tracks), as the first defining characteristic. Morphology was the secondary characteristic to select particles for further study, i.e. spherical/non-spherical. Once particles were identified and isolated, they were characterized by optical microscopy for size in µm, number of fission tracks, morphology, transmitted light color, and reflected light color. Particles were then analyzed by scanning electron microscopy for morphology, elemental content, and compound identification. Raman spectroscopy was attempted on five particles with indeterminate results due to environmental mixing (heterogeneity) during the events of particle formation. Once all non-destructive analyses were completed all particles were analyzed by thermal ionization mass spectrometry to determine isotopic atom percents of plutonium and uranium, and an estimate of atoms of plutonium and uranium in each particle. An estimate of the ratio of uranium to plutonium was also obtained (U/Pu). Data analytics of the data from the particles showed that combining characteristics of the particles have a high probability of identifying particles of interest from bulk post-detonation debris samples. Please note that this version of the report is an abridged version of the full report (Wagnon et al. 2025) that has been edited to be appropriate for public release.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Data Driven Correlated Noise Simulation for the ICEBERG LArTPC

Accurate electronic-noise simulation is essential for low-energy physics in liquid-argon TPCs. More realistic noise modeling allows us to better tune reconstruction algorithms and more reliably assess and optimize signal-detection thresholds. We present a data-driven noise simulation framework developed for the ICEBERG test stand for DUNE that generates synthetic noise waveforms that reproduce both (i) the measured per-channel magnitude of the Fast Fourier Transform (FFT) and (ii) frequency-dependent channel-to-channel correlations observed in ICEBERG noise data. Using a dedicated noise-only dataset, we build a compact noise model containing per-channel FFT-magnitude targets together with a small set of band-wise cross-wire color matrices. White noise is generated in the frequency domain by drawing circular-symmetric complex Gaussian coefficients with random phases and scaling them to match the measured FFT-magnitude targets, and cross-wire correlations are subsequently imposed using the stored color matrices. The model and algorithm were integrated into the LArSoft + Wire-Cell Toolkit simulation chain and validated by comparing waveform structure, frequency-domain spectra, and band-limited correlation matrices from simulated noise and ICEBERG data. This approach can be extended to other LArTPC operating conditions.

Ghosh, Avik [Iowa State U.]↗

J/Psi Photoproduction Near Threshold With CLAS12

The structure of the proton is comprised of quarks and a sea of gluons. A mechanism that can extract the characteristics of the hidden-color correlations of the nuclear wavefunction is the production of charm near threshold. Due to the fact that momentum transfer is large near threshold in the production of J/ψ , all three valence quarks must act coherently to ex- change energy for the reaction to occur. Models have been developed to predict the nature of J/ψ photoproduction at these specific energies. These include production mechanisms with the two-gluon and three-gluon exchanges. The transferred momentum dependence of the differential cross sections are sensitive to the gluonic form factors, which describe the distribution of color charge in the proton. The CLAS12 detector is capable of measuring J/ψ photoproduction at the energy range close to the threshold. Work showcased in this dissertation encompasses the preparation of the CLAS12 experiments, including the optimization of tracking reconstruction through the study of the Torus magnetic field. In terms of software, contributions were made to the CLAS12 Event Builder, a key stage of reconstruction where event-by-event information is summarized for efficient data analysis. After the run periods were successfully completed, analysis of the RG-A data commenced and an analysis framework was developed to measure the differential and total cross sections of J/ψ photoproduction in Hall B.

Newton, Joseph↗

Toward Smart, Automated Junctional Tourniquets—AI Models to Interpret Vessel Occlusion at Physiological Pressure Points

Hemorrhage is the leading cause of preventable death in both civilian and military medicine. Junctional hemorrhages are especially difficult to manage since traditional tourniquet placement is often not possible. Ultrasound can be used to visualize and guide the caretaker to apply pressure at physiological pressure points to stop hemorrhage. However, this process is technically challenging, requiring the vessel to be properly positioned over rigid boney surfaces and applying sufficient pressure to maintain proper occlusion. As a first step toward automating this life-saving intervention, we demonstrate an artificial intelligence algorithm that classifies a vessel as patent or occluded, which can guide a user to apply the appropriate pressure required to stop flow. Neural network models were trained using images captured from a custom tissue-mimicking phantom and an ex vivo swine model of the inguinal region, as pressure was applied using an ultrasound probe with and without color Doppler overlays. Using these images, we developed an image classification algorithm suitable for the determination of patency or occlusion in an ultrasound image containing color Doppler overlay. Separate AI models for both test platforms were able to accurately detect occlusion status in test-image sets to more than 93% accuracy. In conclusion, this methodology can be utilized for guiding and monitoring proper vessel occlusion, which, when combined with automated actuation and other AI models, can allow for automated junctional tourniquet application.

60 APPLIED LIFE SCIENCES↗

3D Printed Chromophoric Sensors

Eight chromophoric indicators are incorporated into Sylgard 184 to develop sensors that are fabricated either by traditional methods such as casting or by more advanced manufacturing techniques such as 3D printing. The sensors exhibit specific color changes when exposed to acidic species, basic species, or elevated temperatures. Additionally, material properties are investigated to assess the chemical structure, Shore A Hardness, and thermal stability. Comparisons between the casted and 3D printed sensors show that the sensing devices fabricated with the advanced manufacturing technique are more efficient because the color changes are more easily detected.

3d printing↗

Real-Time Identification of Oxygen Vacancy Centers in LiNbO 3 and SrTiO 3 during Irradiation with High Energy Particles

Oxygen vacancies are known to play a central role in the optoelectronic properties of oxide perovskites. A detailed description of the exact mechanisms by which oxygen vacancies govern such properties, however, is still quite incomplete. The unambiguous identification of oxygen vacancies has been a subject of intense discussion. Interest in oxygen vacancies is not purely academic. Precise control of oxygen vacancies has potential technological benefits in optoelectronic devices. In this review paper, we focus our attention on the generation of oxygen vacancies by irradiation with high energy particles. Irradiation constitutes an efficient and reliable strategy to introduce, monitor, and characterize oxygen vacancies. Unfortunately, this technique has been underexploited despite its demonstrated advantages. This review revisits the main experimental results that have been obtained for oxygen vacancy centers (a) under high energy electron irradiation (100 keV–1 MeV) in LiNbO 3 , and (b) during irradiation with high-energy heavy (1–20 MeV) ions in SrTiO 3 . In both cases, the experiments have used real-time and in situ optical detection. Moreover, the present paper discusses the obtained results in relation to present knowledge from both the experimental and theoretical perspectives. Our view is that a consistent picture is now emerging on the structure and relevant optical features (absorption and emission spectra) of these centers. One key aspect of the topic pertains to the generation of self-trapped electrons as small polarons by irradiation of the crystal lattice and their stabilization by oxygen vacancies. What has been learned by observing the interplay between polarons and vacancies has inspired new models for color centers in dielectric crystals, models which represent an advancement from the early models of color centers in alkali halides and simple oxides. The topic discussed in this review is particularly useful to better understand the complex effects of different types of radiation on the defect structure of those materials, therefore providing relevant clues for nuclear engineering applications.

36 MATERIALS SCIENCE↗

Leveraging Observations of Untrained Panelists to Screen for Quality of Fresh-Cut Romaine Lettuce

Fresh-cut romaine lettuce’s high perishability challenges ready-to-eat (RTE) salad production. Selecting cultivars less prone to browning and decay is crucial for extending shelf life. Traditional quality evaluation methods using instrumentation and trained panelists are time-consuming and logistically complex. This study investigated the effectiveness of untrained volunteers in assessing fresh-cut romaine lettuce quality. Given that the average consumer in the USA is familiar with the flavor characteristics of romaine lettuce, this study proposed to investigate the value of having untrained volunteers discern the quality of fresh-cut romaine lettuce. Therefore, six romaine lettuce accessions (Green Forest, King Henry, Parris Island Cos, PI 491224, SM13-R2, and Sun Valley) were assessed for sensory quality attributes (browning, green color, decay, and overall quality) and compared with instrumentation analyses (gas composition including O2 and CO2, electrolyte leakage, and color). The results showed significant quality differences (p < 0.05) among the accessions, with some seasonal variability. Very importantly, the consumers’ (n = 159) assessments revealed similar results to those produced by either instrumentation or a trained panel. The consumers provided sensory scores that allowed for the grouping of accessions based on their postharvest quality, which efficiently matched their pedigree relationship. In conclusion, ad hoc consumer panels can be an effective way to characterize the quality of romaine lettuce for RTE salads.

Agriculture↗

Influence of Supplementary Blue and Far-Red Light on the Morphology and Texture of Ocimum basilicum L. Grown in Controlled Environments

Basil (Ocimum basilicum L.) is highly sensitive to environmental conditions and is an ideal candidate for cultivation in controlled environment agriculture (CEA). Light-emitting diode technology has become essential in CEA, offering precise control over light intensity, spectrum, and duration. This study investigated how supplemental blue light, far-red light, or their combination influences basil biomass, morphology, texture, and color when added to a white + red light spectrum. Basil ’Prospera’ and ’Amethyst’ were exposed to five light treatments for 14–28 days: white + red at 180 µmol∙m−2∙s−1 (W) as the control, and four treatments with an additional 60 µmol∙m−2∙s−1 of either white + red (+W60), blue (+B60), far-red (+FR60), or a combination of B and FR (+B30+FR30), for a total photon flux density of 240 µmol∙m−2∙s−1. The results demonstrated that +B60 and +W60 light treatments increased leaf thickness by 17–20% compared to the +FR60 treatment. Conversely, texture analysis revealed that +FR60-treated leaves had higher puncture resistance, with ’Amethyst’ and ’Prospera’ requiring 1.57 ± 0.43 N and 1.45 ± 0.35 N of force, respectively, compared to 1.19 ± 0.32 N and 1.1 ± 0.21 N under +B60. These findings suggest that tailored light recipes in CEA can optimize basil quality, allowing growers to modify traits like leaf color, thickness, and toughness.

Oehler, Madison A. (ORCID:0000000297919667)↗

Studying the Suitability of Nineteen Lignins as Partial Polyol Replacement in Rigid Polyurethane/Polyisocyanurate Foam

In this study, nineteen unmodified lignins from various sources (hardwood, softwood, wheat straw, and corn stover) and isolation processes (kraft, soda, organosolv, sulfite, and enzymatic hydrolysis) were used to replace 30 wt.% of petroleum-based polyol in rigid polyurethane/polyisocyanurate (PUR/PIR) foam formulations. Lignin samples were characterized by measuring their ash content, hydroxyl content (Phosphorus Nuclear Magnetic Resonance Spectroscopy), impurities (Inductively Coupled Plasma), and pH. After foam formulation, properties of lignin-based foams were evaluated and compared with a control foam (with no lignin) via cell morphology, closed-cell content, compression strength, apparent density, thermal conductivity, and color analysis. Lignin-based foams passed all measured standard specifications required by ASTM International C1029-15 for type 1 rigid insulation foams, except for three foams. These three foams had poor compressive strengths, significantly larger cell sizes, darker color, lower closed-cell contents, and slower foaming times. The foam made with corn stover enzymatic hydrolysis lignin showed no significant difference from the control foam in terms of compressive strength and outperformed all other lignin-based foams due to its higher aliphatic and p-hydroxyphenyl hydroxyl contents. Lignin-based foams that passed all required performance testing were made with lignins having higher pH, potassium, sodium, calcium, magnesium, and aliphatic/p-hydroxyphenyl hydroxyl group contents than those that failed.

59 BASIC BIOLOGICAL SCIENCES↗

Vegetation Detection Using Deep Learning and Conventional Methods

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations.

58 GEOSCIENCES↗

Open Cluster IC 1369 and Its Vicinity: Multicolor Photometry and Gaia DR2 Astrometry

The open cluster IC 1369, located in Cygnus close to the galactic equator at the 89.°6 longitude, and its vicinity are investigated by applying two-dimensional photometric classification of stars down to V = 19 mag measured in the Vilnius seven-color photometric system. Employing the Gaia DR2 coordinates, parallaxes, and proper motions, 143 cluster members are found having cluster membership probabilities ≥0.75. The hottest stars of the evolved main sequence are of spectral class B9. Distances to the cluster, determined by two methods based on the Gaia parallaxes, are 3280 and 3370 pc with an uncertainty of 400–500 pc. Employing the physical HR diagram with the coordinates logL/L{sub ⊙} versus logT{sub eff} and the Padova isochrones, the cluster age is found to be between 300 and 350 Myr. Among the cluster members we identified six red giants of spectral classes G5–G8 and luminosities II–III, 17 Am stars, one Ap star, and one B5 blue straggler. The extinction shows a steep rise up to ∼2.0 mag at 300–700 pc, caused by the extensions of the dust cloud LDN 970 and the Great Cygnus Rift, and up to ∼2.5 mag at the edge of the Perseus arm at 3.0 kpc. The extinction is almost constant between 0.9 and 2.5 kpc from the Sun. The average extinction of the cluster members is 2.54 mag. A systematic error of color excesses found in the Argonaut calculator results is discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Census of the Young Stellar Population in the Galactic H ii Region Sh2-242

We present here identification and characterization of the young stellar population associated with an active star-forming site Sh2-242. We used our own new optical imaging and spectroscopic observational data, as well as several archival catalogs, e.g., Pan-STARRS 1, Gaia DR2, IPHAS, Wide-field InfraRed Camera, 2MASS, and Spitzer. Slit spectroscopic results confirm the classification of the main ionizing source BD+26 980 as an early-type star of spectral type B0.5 V. The spectrophotometric distance of the star is estimated as 2.08 ± 0.24 kpc, which confirms the source as a member of the cluster. An extinction map covering a large area (diameter ∼50′) is generated with H and K photometry toward the region. From the map, three distinct locations of peak extinction complexes (A {sub V} ≃ 7–17 mag) are identified for the very first time. Using the infrared color excess, a total of 33 Class I and 137 Class II young objects are classified within the region. The IPHAS photometry reveals classification of 36 Hα emitting sources, which might be class II objects. Among 36 Hα emitting sources, 5 are already identified using infrared excess emission. In total, 201 young objects are classified toward S242 from this study. The membership status of the young sources is further windowed with the inclusion of parallax from the Gaia DR2 catalog. Using the optical and infrared color–magnitude diagrams, the young stellar objects are characterized with an average age of ∼1 Myr and masses in the range 0.1–3.0 M {sub ☉}. The census of the stellar content within the region is discussed using combined photometric and spectroscopic data.

79 ASTRONOMY AND ASTROPHYSICS↗

Cataclysmic Variables in the First Year of the Zwicky Transient Facility

Using selection criteria based on amplitude, time, and color, we have identified 329 objects as known or candidate cataclysmic variables (CVs) during the first year of testing and operation of the Zwicky Transient Facility. Of these, 90 are previously confirmed CVs, 218 are strong candidates based on the shape and color of their light curves obtained during 3–562 days of observation, and the remaining 21 are possible CVs but with too few data points to be listed as good candidates. Almost half of the strong candidates are within 10 deg of the galactic plane, in contrast to most other large surveys that have avoided crowded fields. The available Gaia parallaxes are consistent with sampling the low mass transfer CVs, as predicted by population models. Our follow-up spectra have confirmed Balmer/helium emission lines in 27 objects, with four showing high-excitation He ii emission, including candidates for an AM CVn, a polar, and an intermediate polar. Our results demonstrate that a complete survey of the Galactic plane is needed to accomplish an accurate determination of the number of CVs existing in the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗