Graduate Student Savanah Turner Publishes Study of over 300 L and T dwarfs

We fit archival near-IR spectra of ∼300 brown dwarfs with atmosphere models from the Sonora and Phoenix groups. Using the parameters of the best-fit models as estimates for the physical properties of the brown dwarfs in our sample, we have performed a survey of how brown dwarf atmospheres evolve with spectral type and temperature. We present the fit results and observed trends. We find that clouds have a more significant impact on near-IR spectra than disequilibrium chemistry, and that silicate clouds influence the near-IR spectrum through the late T types. We note where current atmosphere models are able to replicate the data and where the models and data conflict. We also categorize objects with similar spectral morphologies into families and discuss possible causes for their unique spectral traits. We identify two spectral families with morphologies that are likely indicative of binarity.

We describe efforts to develop broadband mirror coatings with high performance that will extend from the far-ultraviolet (FUV) to infrared wavelengths. Our team at the Goddard Space Flight Center has developed a reactive physical vapor deposition (rPVD) process that combines a fluorination with a XeF2 gas (which grants a thin AlF3 layer) in between the Al and the metal-fluoride protection layer (either LiF or MgF2) that are done with the conventional PVD process. This recently developed rPVD process produces protected Al mirrors coatings with an improved average FUV reflectance between 10% and 15% higher (when compared with conventionally prepared samples). We have termed these coatings as XeLiF when the dielectric overcoat is LiF or XeMgF2 when the dielectric overcoat is MgF2. The XeLiF-coated Al mirrors meet current goals for advanced broadband mirrors in the FUV (R>70% at 103 nm and R>80 above 110 nm), whereas the XeMgF2 provides R>80% above 115 nm. The IR/Vis/UV reflectance for either XeLiF or XeMgF2 mirrors is similar to the theoretical reflectance of bare aluminum at wavelengths >200 nm. In addition, long-term lifetime testings of XeLiF mirrors indicate the rPVD process produces more environmentally stable coatings, where a XeLiF sample showed a degradation in the average FUV reflectance of around 1% to 2% when stored in a relative humidity of 40% over a period of 3.5 years. These results are a remarkable improvement when compared with conventionally prepared Al+LiF samples that would degrade their FUV reflectance in a matter of weeks or months when exposed to those kinds of relative humidity levels. Surface topographies on several XeLiF samples with varying Al and LiF thicknesses have been measured with an atomic force microscope (AFM). The root mean square (RMS) roughness (σ) values derived from these AFM results have ranged between 0.6 and 0.9 nm. For comparison, samples without the Xe process start off by having an RMS roughness that is 30% larger than samples treated with the XeF2 gas. We have also determined that these roughness values are showing a slight increase, ranging between 0.9 and 1.0 nm, when samples are exposed to room temperature and relative humidity as high as 50% over one week. Both of these key performance parameters (environmental stability in reflectance and smoothness of ≤1 nm) are key considerations for using the XeLiF coating in the primary and secondary mirrors of the Habitable Worlds Observatory (HWO). We also show evidence that the rPVD coating process is compatible with deposition on Si-based gratings. It is known that XeF2 vapor is a strong Si etchant, thus the demonstration that the native SiO2 layer on Si test samples is sufficient to protect the groove profile of E-beam-ruled Si gratings from degradation is an important and significant finding.

Background

The integration of artificial intelligence (AI) into healthcare is rapidly advancing, with profound implications for medical practice. However, a gap exists in formal AI education for pre-medical students. This study evaluates the effectiveness of the AI in Medicine Association (AIM), an extracurricular program designed to equip pre-medical students with foundational AI knowledge.

Methods

A quasi-experimental pretest-posttest control group design was employed, comparing knowledge acquisition between students participating in the AIM program (cohort group) and a control group of students not participating. The intervention spanned four weeks and included hands-on AI training, ethical considerations, data preprocessing, and model evaluation. Pretest and posttest assessments measured AI knowledge and pathology-related skills.

Results

Participants in the AIM program demonstrated significant improvements in both AI knowledge and pathology-related scores. The cohort group showed a large effect size across all measured domains, particularly in pathology, with Cohen’s d values ranging from 1.83 to 4.74. Statistical analysis confirmed robust, significant improvements in test scores (t-test and Mann-Whitney U test, p < 0.001). There was no significant correlation between previous AI experience or attitudes toward AI and overall score improvement.

Conclusions

The AIM program effectively improved pre-medical students’ understanding of AI and its application in medicine, particularly in pathology. This study highlights the potential of extracurricular programs to address the need for AI education in medical curricula, especially in the pre-medical phase, and suggests that such initiatives could serve as a model for other institutions seeking to integrate AI education into healthcare training.

The Nancy Grace Roman Space Telescope is poised to revolutionize our scientific understanding of exoplanets, dark matter, dark energy, and general astrophysics, including through an innovative community approach to defining and executing sky surveys. The Roman Observations Time Allocation Committee (ROTAC) was convened to recommend time allocations for the three Core Community Surveys (CCS) using the Wide Field Instrument (WFI): the High Latitude Wide Area Survey, the High Latitude Time Domain Survey, and the Galactic Bulge Time Domain Survey, as well as balance the time allocation for the General Astrophysics Surveys. Each CCS had a corresponding Definition Committee that collected community input and designed proposals for a nominal (in-guide) survey, as well as underguide and overguide options with smaller and larger time allocations, respectively. These options explored different ways of fulfilling the mission science requirements while maximizing general astrophysics science goals enabled by the surveys. In this report, the ROTAC lays out its recommendations for the three CCS observing designs and the WFI time allotment for CCS (74.5%) and the General Astrophysics Surveys (25.5%).

Prior work [e.g., McInerny (1992). Noise Control Eng. J. 38(1), 5–16; McInerny (1996). J. Aircraft 33(3), 511–517; Franken (1958). Noise Control 4(3), 8–16] has resulted in models for estimating overall sound power levels (OAPWLs) and maximum overall sound pressure levels (OASPL_max) from jet and rocket engines. Based on fundamental flow properties, this paper builds on previous results and presents simple methods for predicting OAPWL and OASPL_max from heated supersonic jets and rockets. A method for estimating ground effects on OASPL_max is also presented. The model's performance is evaluated for launched Atlas V and Vulcan Centaur rockets and an installed F404 jet engine at engine conditions ranging from 38% thrust through afterburner. The results show good agreement for OASPL_max ⁠, where the root mean square error is confined to less than 2 dB for the rockets and jet engine conditions considered.

We investigated the growth of carbon nanotubes (CNTs) directly on stainless steel substrates. The CNTs were grown using a two-step process: oxidation of the stainless steel surface and CNT growth. The samples were oxidized in an 800 °C furnace fed with a flow of air for 4 min. CNTs were grown by switching the flow to ethylene, which both reduces the oxide and initializes CNT growth. The time of CNT growth was varied to understand how the samples evolved over time. To better understand the growth mechanisms, we isolated cross-sections of the CNT-substrate interface using a focused ion beam. These cross-sections were investigated with transmission electron microscopy and energy dispersive X-ray spectroscopy. CNTs were seen to grow from iron-rich nanoparticles embedded in the oxide layer. The oxide layer was also seen to lose iron over time, suggesting that these iron nanoparticles were reduced out of the oxide. The base particles were embedded in the oxide layer, leaving cavities when the CNTs were removed. The diameters of the nanotubes were also seen to grow over time as a result of carbon infiltration. The effects of the embedded particle and infiltration quickly isolate the catalyst, leading to short CNTs (1–10 µm).