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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measurement of the background in the CMS muon detector in ${p}{p}$-collisions at $\sqrt{s} = 13$ TeV

The CMS detector, including its muon system, has been operating at the CERN LHC in increasingly challenging conditions for about 15 years. The muon detector was designed to provide excellent triggering and track reconstruction for muons produced in proton–proton collisons at an instantaneous luminosity ($\mathcal{L}$) of 1 x 10 34 cm –2 s –1 . During the Run 2 data-taking period (2015–2018), the LHC achieved an instantaneous luminosity of twice its design value, resulting in larger background rates and making the efficient detection of muons more difficult. While some backgrounds result from natural radioactivity, cosmic rays, and interactions of the circulating protons with residual gas in the beam pipe, the dominant source of background hits in the muon system arises from proton–proton interactions themselves. Charged hadrons leaving the calorimeters produce energy deposits in the muon chambers. In addition, high-energy particles interacting in the hadron calorimeter and forward shielding elements generate thermal neutrons, which leak out of the calorimeter and shielding structures, filling the CMS cavern. We describe the method used to measure the background rates in the various muon subsystems. These rates, in conjunction with simulations, can be used to estimate the expected backgrounds in the High-Luminosity LHC. This machine will run for at least 10 years starting in 2029 reaching an instantaneous luminosity of $\mathcal{L}$ = 5 x 10 34 cm –2 s –1 and increasing ultimately to $\mathcal{L}$ = 7.5 x 10 34 cm –2 s –1 . These background estimates have been a key ingredient for the planning and design of the muon detector upgrade.

Tytgat, M. (ORCID:0000000239902074)↗
DOE OSTI2026

Metabolomics analysis of P. tremula × P. alba ‘717-1B4’ tissue culture hybrids grown in liquid media supplemented with EGGC and d4-EGGC

A metabolite linked to ethylene metabolism in Populus was recently structurally characterized as 2-hydroxyethyl β-D-glucopyranoside, an ethylene glycol glucose conjugate (EGGC). The dataset presented here is associated with the metabolomics analysis of various tissues (i.e., roots, stems/leaves) of plants grown in liquid media supplemented with EGGC and stable-isotope labelled EGGC (i.e., d4-EGGC). Data were collected using a Thermo Scientific gas chromatograph (GC) coupled to a Q Exactive Orbitrap mass spectrometer (MS). Samples were collected at three different timepoints and silylated prior to GCMS analysis.

09 BIOMASS FUELS↗
DOE OSTI2020

Materials Data on P by Materials Project

P is Hittorf-like structured and crystallizes in the triclinic P-1 space group. The structure is one-dimensional and consists of one P ribbon oriented in the (1, 1, 0) direction. there are twenty-one inequivalent P sites. In the first P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are a spread of P–P bond distances ranging from 2.20–2.22 Å. In the second P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.22 Å) and one longer (2.28 Å) P–P bond lengths. In the third P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.20 Å) and one longer (2.21 Å) P–P bond lengths. In the fourth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.20 Å) and one longer (2.29 Å) P–P bond lengths. In the fifth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.24 Å) P–P bond lengths. In the sixth P site, P is bonded in a distorted trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.31 Å) P–P bond lengths. In the seventh P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.25 Å) P–P bond lengths. In the eighth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.29 Å. In the ninth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.20 Å) and two longer (2.22 Å) P–P bond lengths. In the tenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.22 Å. In the eleventh P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.22 Å) P–P bond lengths. In the twelfth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.21 Å. In the thirteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.22 Å) and one longer (2.24 Å) P–P bond lengths. In the fourteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.22 Å. In the fifteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.20 Å) and one longer (2.24 Å) P–P bond lengths. In the sixteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. In the seventeenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.24 Å. In the eighteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.24 Å. In the nineteenth P site, P is bonded in a distorted trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.30 Å. In the twentieth P site, P is bonded in a distorted trigonal non-coplanar geometry to three P atoms. In the twenty-first P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.26 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on P by Materials Project

P is Hittorf structured and crystallizes in the monoclinic P2/c space group. The structure is two-dimensional and consists of two P sheets oriented in the (0, 0, 1) direction. there are twenty-one inequivalent P sites. In the first P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are a spread of P–P bond distances ranging from 2.21–2.23 Å. In the second P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.29 Å) P–P bond lengths. In the third P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are two shorter (2.21 Å) and one longer (2.23 Å) P–P bond lengths. In the fourth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.23 Å) and one longer (2.28 Å) P–P bond lengths. In the fifth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are two shorter (2.22 Å) and one longer (2.30 Å) P–P bond lengths. In the sixth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.22 Å) P–P bond lengths. In the seventh P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are two shorter (2.21 Å) and one longer (2.29 Å) P–P bond lengths. In the eighth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.25 Å) P–P bond lengths. In the ninth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.22 Å. In the tenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.22 Å) P–P bond lengths. In the eleventh P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.24 Å. In the twelfth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.22 Å. In the thirteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. In the fourteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are a spread of P–P bond distances ranging from 2.21–2.24 Å. In the fifteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.21 Å. In the sixteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. There are one shorter (2.21 Å) and one longer (2.24 Å) P–P bond lengths. In the seventeenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. In the eighteenth P site, P is bonded in a trigonal non-coplanar geometry to three P atoms. In the nineteenth P site, P is bonded in a distorted trigonal non-coplanar geometry to three P atoms. The P–P bond length is 2.30 Å. In the twentieth P site, P is bonded in a distorted trigonal non-coplanar geometry to three P atoms. In the twenty-first P site, P is bonded in a trigonal non-coplanar geometry to three P atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions

Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Gluon double-spin asymmetry in the longitudinally polarized p + p collisions

We derive the first-ever small-x expression for the inclusive gluon production cross section in the central rapidity region of the longitudinally polarized proton-proton collisions. The cross section depends on the polarizations of both protons, therefore comprising the numerator of the longitudinal double-spin asymmetry ALL for the produced gluons. The cross section is calculated in the shock wave formalism and is expressed in terms of the polarized dipole scattering amplitudes on the projectile and target protons. We show that the small-x evolution corrections are included into our cross section expression if one evolves these polarized dipole amplitudes using the double-logarithmic helicity evolution derived in [1–4]. Our calculation is performed for the gluon sector only, with the quark contribution left for future work. When that work is complete, the resulting formula will be applicable to longitudinally polarized proton-proton and proton-nucleus collisions, as well as to polarized semi-inclusive deep inelastic scattering (SIDIS) on a proton or a nucleus. Our results should allow one to extend the small-x helicity phenomenology analysis of [5] to the jet/hadron production data reported for the longitudinally polarized proton-proton collisions at RHIC and to polarized SIDIS measurements at central rapidities to be performed at the EIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗