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Journals

Sea turtles across the North Pacific are exposed to perfluoroalkyl substances

Author(s)
Cathryn Wood, George H. Balazs, Marc Rice, Thierry M. Work, T. T. Jones, Eleanor Sterling, Tammy Summers, John Brooker, Lauren Kurpita, Cheryl King, Jennifer Lynch
Perfluorinated alkyl substances (PFASs) are global, persistent, and toxic contaminants. We assessed PFAS concentrations in green (Chelonia mydas) and hawksbill

Database of Ab Initio L-edge X-ray Absorption Near Edge Structure

Author(s)
Yiming Chen, Chi Chen, Chen Zheng, Shyam Dwaraknath, Matthew K. Horton, Jordi Cabana, John J. Rehr, John Vinson, Alan K. Dozier, Kristin A. Persson, Shyue P. Ong
The L-edge X-ray Absorption Near Edge Structure (XANES) is widely used in the characterization of transition metal compounds. Here, we report the development of

Measuring Deadtime and Double-Counts in a Non-Paralyzable Scintillating Neutron Detector using Arrival Time Statistics

Author(s)
Kevin N. Pritchard, Jean Philippe Chabot, Peter Tsai, R. Roubucci, F. S. Choa, A. Osovizky, Jeffrey B. Ziegler, Louis E. Binkley, Nancy Hadad, M. Jackson, C. Hurlbut, George M. Baltic, Charles Majkrzak, Nicholas C. Maliszewskyj
A 6LiF:ZnS(Ag) based cold neutron detector with wavelength shifting (WLS) fibers and SiPM photodetector was developed at the NIST Center for Neutron Research

Witnessing the survival of time-energy entanglement through biological tissue and media

Author(s)
Daniel J. Lum, Michael Mazurek, Alexander Mikhaylov, Kristen M. Parzuchowski, Ryan M. Wilson, Marcus Cicerone, Ralph Jimenez, Thomas Gerrits, Martin Stevens, Charles Camp
In this work, we demonstrate the preservation of time-energy entanglement of near-IR photons through thick biological media ( 1.55 mm) and tissue ( 235 um) at

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models

Author(s)
Jason Hattrick-Simpers, Brian DeCost, Aaron Gilad Kusne, Howard Joress, Winnie Wong-Ng, Debra Kaiser, Andriy Zakutayev, Caleb Phillips, Tonio Buonassisi, Shijing Sun, Janak Thapa
Modern machine learning and autonomous experimentation schemes in materials science rely on accurate analysis of the data ingested by these models

The impact of COVID-19 on CO2 emissions in the Los Angeles and Washington DC/Baltimore metropolitan areas

Author(s)
Kimberly Mueller, Anna Karion, Sharon Gourdji, Israel Lopez Coto, James Whetstone, Vineet Yadav, Geoffrey Roest, Kevin R. Gurney, Kristal R. Verhulst, Jooil Kim, Michael Stock, Elizabeth DiGangi, Steve Prinzivalli, Ralph Keeling, R. F. Weiss, Charles E. Miller, Clayton Fain, Riley Duren, Subhomoy Ghosh
Responses to COVID-19 has resulted in and unintended reductions of city-scale carbon dioxide (CO2) emissions. Here we detect and estimate decreases in CO2

Ray-based framework for state identification in quantum dot devices

Author(s)
Justyna Zwolak, Thomas McJunkin, Sandesh Kalantre, Samuel Neyens, Evan MacQuarrie, Mark A. Eriksson, Jacob Taylor
Quantum dots (QDs) defined with electrostatic gates are a leading platform for a scalable quantum computing implementation. However, with increasing numbers of

Hi-C scaffolded short- and long-read genome assemblies of the California sea lion are broadly consistent for syntenic inference across 45 million years of evolution

Author(s)
Claire R. Peart, Christina Williams, Saurabh Pophaly, Jeremy Johnson, Ben Neely, Frances Gulland, David Adams, Bee Ng, William Cheng, Joseph Hoffman, Matthew Breen, Jochen Wolf
With the advent of chromatin-interaction maps, chromosome-level genome assemblies have become a reality for a wide range of organisms. Scaffolding quality is
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