Physical Sciences and Mathematics Commons^™

Mgrre_Geolog_Collections Tope & Stover 3-22 21111395140000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Anderson, Robert C Et Al 1 21133283560000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Adair, Donald L 1-36 21101299010000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Turner, Dale 1-27 21129314230000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Fruit Haven Nursery Inc 1-12 21101318170000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Robarts, Tryphena M 1 21147289980000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Jansma-Gordon-Altschul 1-26 21101307680000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Coder, Russell 1-10 21105300220000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections State Dover 1-27 21137311650000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Krol, Wanda Et Al 1-12 21137309090000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Allmand, Thomas & Johnson, Will Unit 1-24 21137300040000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Hanson, Anna Et Al 1-28 21133314310000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections State Allis 2-35 21141483120000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections State Chester 2-22 21137297500000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Song Of The Morning Ranch 1-19 21137286560000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Koronka, A 1-4 21137307730000, Mgrre Western Michigan University

Geolographs

No abstract provided.

Mgrre_Geolog_Collections Sobota, Thomas P & Rose M 1-25 21101318990000, Mgrre Western Michigan University

Geolographs

No abstract provided.

The Jwst Early Release Science Program For Direct Observations Of Exoplanetary Systems. Iii. Aperture Masking Interferometric Observations Of The Star Hip 65426 At 3.8 Μm, Shrishmoy Ray, Steph Sallum, Sasha Hinkley, Anand Sivaramkrishnan, Rachel Cooper, Jens Kammerer, Alexandra Z. Greebaum, Deeparshi Thatte, Tomas Stolker, Cecilia Lazzoni, Andrei Tokovinin, Matthew De Furio, Samuel Factor, Michael Meyer, Jordan M. Stone, Aarynn Carter, Beth Biller, Andrew Skemer, Genaro Suárez, Jarron M. Leisenring, Marshall D. Perrin, Adam L. Kraus, Olivier Absil, William O. Balmer, Anthony Boccaletti, Mariangela Bonavita, Mickael Bonnefoy, Mark Booth, Brendan P. Bowler, Zackery W. Briesemeister, Marta L. Bryan, Per Calissendorff

Astronomy: Faculty Publications

We present aperture masking interferometry (AMI) observations of the star HIP 65426 at 3.8 μm, as part of the JWST Direct Imaging Early Release Science program, obtained using the Near Infrared Imager and Slitless Spectrograph instrument. This mode provides access to very small inner working angles (even separations slightly below the Michelson limit of 0.5λ/D for an interferometer), which are inaccessible with the classical inner working angles of the JWST coronagraphs. When combined with JWST’s unprecedented infrared sensitivity, this mode has the potential to probe a new portion of parameter space across a wide array of astronomical observations. Using this …

Perceptions Of Ai Skills In Resumes, Brandy Whitford, Patrick J. Cooper

Faculty and Staff Publications & Presentations

No abstract provided.

The Formation Of Glacier Dirt Cones, Ryan M. Strickland, Matthew D. Covington

Geosciences Faculty Publications and Presentations

Glacier dirt cones are meter-scale cones of ice covered with sediment and rock. The cones develop through a process known as differential melt, whereby ice underlying thick debris melts more slowly than bare ice. We report observations of dirt cones on the Kuskulana Glacier, Alaska and develop a model that simulates the growth of dirt cones from debris-filled pits in the ice. With this model, we vary ice melt rates, hillslope debris diffusion rates and pit geometry. Cone heights scale with the square root of debris volume and growth occurs in three distinct stages: emergence, flux-controlled growth and melt-controlled growth. …

2025 April 10 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) 2025 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites (Ur-35) Remedial Action Work Plan (Rawp) (Dated June 14, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Butte Reclamation Evaluation System (Bres) Draft 2024 Field Evaluation Summary And Technical Recommendations Report (Dated November 15, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Utilizing Machine Learning To Predict The Charge Storage Capability Of Lithium-Ion Battery Materials, Manoj Chhetri, Karen S. Martirosyan

Physics & Astronomy Faculty Publications

With the increasing demand for high-performance batteries in applications such as electric vehicles and portable electronics, accurately predicting the charge storage capacity of battery materials is crucial for developing more efficient and reliable energy storage systems. Machine Learning (ML) and data-driven approaches, plays a vital role in enhancing our understanding of Li-ion battery performance, guiding materials design, optimizing system efficiency, and accelerating innovation in energy storage technologies. In this study, an ML-based approach was applied to a dataset of 2345 rechargeable Li-ion battery materials, obtained from the Materials Project online portal, to predict gravimetric charge storage capacity ─ a key …

Boron Nitride Nanosheets, Quantum Dots, And Dots: Synthesis, Properties, And Biomedical Applications, Raksha Dubey, Matthew Cowles, Zohreh Salimi, Xiuling Liu, Rodney Oakley, Nazmiye B. Yapici, Join Uddin, Dongyan Zhang, Yoke Khin Yap

Michigan Tech Publications

This review examines three aspects of hexagonal boron nitride (h-BN) nanomaterials: properties, synthesis methods, and biomedical applications. We focus the scope of review on three types of h-BN nanostructures: boron nitride nanosheets (BNNSs, few-layered h-BN, larger than ∼100 nm in lateral dimensions), boron nitride quantum dots (BN QDs, smaller than ∼10 nm in all dimensions, with inherent excitation-dependent fluorescence), and boron nitride dots (BN dots, smaller than ∼10 nm in all dimensions, wide bandgap without noise fluorescence). The synthesis methods of BNNSs, BN QDs, and BN dots are summarized in top-down and bottom-up approaches. Future synthesis research should focus on …

Data-Driven Strategy For Contact Angle Prediction In Underground Hydrogen Storage Using Machine Learning, Mehdi Nassabeh, Zhenjiang You, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

In response to the surging global demand for clean energy solutions and sustainability, hydrogen is increasingly recognized as a key player in the transition towards a low-carbon future, necessitating efficient storage and transportation methods. The utilization of natural geological formations for underground storage solutions is gaining prominence, ensuring continuous energy supply and enhancing safety measures. However, this approach presents challenges in understanding gas-rock interactions. To bridge the gap, this study proposes a data-driven strategy for contact angle prediction using machine learning techniques. The research leverages a comprehensive dataset compiled from diverse literature sources, comprising 1045 rows and over 5200 data …

Inconsistencies With The Drumian Carbon Isotope Excursion (Dice) In West-Central Utah, Michelle Norman

Student Research Symposium

Geologic Setting

• During the Cambrian Period (539-485.4Ma), the western US was submerged by a shallow ocean
• Carbon cycle fluctuations in stable carbon were preserved in marine sediments
• One such period of geologic time, the Drumian Age (500Ma), is defined by the first appearance of a deepwater trilobite, P. atavus, in west-central Utah
• Researchers have hypothesized we can find Drumian-aged rocks without the fossils using carbon cycle fluctuations preserved in limestone
• the Drumian Carbon Isotope Excursion (DICE) is defined as a -2.5‰ fluctuation in global carbon-bearing rocks

Data Science For Engineers, Heidi Moulton

Student Research Symposium

30% of USU undergraduate students participate in some sort of research, and for engineering students this often means generating large amounts of data.

Data Science for Engineers is a series of four modules that introduce students to data processing, visualization, and graphing in the Python programming language using Pandas DataFrames and Juypter Notebooks.

The modules are intended for students with a basic understanding of programming in Python, specifically those who have taken CS 1400 Introduction to Computer Science.

The Stem Gender Gap: Can It Be Closed?, Makenna Roberts

Student Research Symposium

Introduction

While many industries have achieved gender parity, women remain underrepresented in STEM fields, with participation stagnating between 32% and 35% from 2011 to 2021. Research suggests this gap is influenced by relative cognitive strengths and social/societal factors. This study analyzes two datasets: (1) SAT score report data from the National College Board and (2) employment data from the 2021 NCSES Survey of Recent College Graduates. Findings highlight disparities at the highest percentiles and lower workforce participation among female STEM graduates.