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Results for “FRAGMENTATION”
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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Mapping of fragmented νf 5/2 →πf 7/2 transitions in the 73 Co→ 73 Ni decay
Excited states in 73 , 75 Ni were investigated through the β decay of 73 , 75 Co in an experiment performed at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University (MSU). The experimental results extended the level scheme of Ni 73 to 3.2-MeV excitation energy and provided the experimental information on excited states in Ni 75 . The β -delayed neutron branching ratio for Co 73 was obtained. Furthermore, the experimental results are discussed in comparison with shell-model calculations.
Correlation studies of fission-fragment neutron multiplicities
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Distribution of nuclear matter and radiation in the fragmentation region
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Simultaneous Monte Carlo analysis of parton densities and fragmentation functions
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Charm-quark fragmentation fractions and production cross section at midrapidity in pp collisions at the LHC
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Fragmentation production of fully-charmed tetraquarks at the LHC
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Thermalization, fragmentation, and tidal disruption: The complex galactic dynamics of dark matter superfluidity
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Observation of New Isotopes in the Fragmentation of Pt 198 at FRIB
Five previously unknown isotopes ( 182,183 Tm, 186,187 Yb, 190 Lu) were produced, separated, and identified for the first time at the Facility for Rare Isotope Beams (FRIB) using the Advanced Rare Isotope Separator (ARIS). The new isotopes were formed through the interaction of a 198 Pt beam with a carbon target at an energy of 186 MeV/u and with a primary beam power of 1.5 kW. Event-by-event particle identification of A, Z, and q for the reaction products was performed by combining measurements of the energy loss, time of flight, magnetic rigidity Bρ, and total kinetic energy. The ARIS separator has a novel two-stage design with high resolving power to strongly suppress contaminant beams. Finally, this successful new isotope search was performed less than one year after FRIB operations began and demonstrates the discovery potential of the facility which will ultimately provide 400 kW of primary beam power.
Investigating resonant low-energy electron attachment to formamide: Dynamics of model peptide bond dissociation and other fragmentation channels
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Quantum Versus Classical Spin Fragmentation in Dipolar Kagome Ice Ho 3 Mg 2 Sb 3 O 14
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Overview of Fragment Separator Superconducting Magnets in the Facility for Rare Isotope Beams
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Fragmentation Analysis of High-Energy Heavy Ion Beams for Single-Event Effects Testing at NSRL
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Pyrimidone inhibitors targeting Chikungunya Virus nsP3 macrodomain by fragment-based drug design
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dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design
Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change ( Δ r G ′ o ) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings ( https://github.com/maranasgroup/dGPredictor ).