Results 71 to 80 of about 1,161,743 (330)

Search for heavy resonances decaying to top quarks

open access: yes, 2013
In many models of physics beyond the Standard Model the coupling of new states to third generation quarks is enhanced. A review is presented of searches by the CMS collaboration for heavy particles decaying to final states involving top quarks.
Kogler, Roman
core   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Neutrino factory in stages: Low energy, high energy, off-axis

open access: yes, 2010
We discuss neutrino oscillation physics with a neutrino factory in stages, including the possibility of upgrading the muon energy within the same program. We point out that a detector designed for the low energy neutrino factory may be used off-axis in a
Jian Tang, P. Huber, Walter Winter
core   +1 more source

Bistable Mechanisms 3D Printing for Mechanically Programmable Vibration Control

open access: yesAdvanced Engineering Materials, EarlyView.
This work introduces a 3D‐printed bistable mechanism integrated into tuned mass dampers (TMDs) for mechanically adaptive passive vibration suppression. Through optimized geometry, the bistable design provides adaptable vibration reduction across a broad range of scenarios, achieving effective vibration mitigation without complex controls or external ...
Ali Zolfagharian   +4 more
wiley   +1 more source

Heavy-Flavor Results from CMS

open access: yes, 2012
Heavy-flavor physics offers the opportunity to make indirect tests of physics beyond the Standard Model through precision measurements, and of quantum chromodynamics (QCD) through particle production studies.
Ulmer, Keith
core   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Overview of results from the STAR experiment at RHIC

open access: yes, 2003
The Relativistic Heavy-Ion Collider (RHIC) provides Au+Au collisions at energies up to \sqrtsNN=200 GeV. STAR experiment was designed and constructed to investigate the behavior of strongly interacting matter at high energy density.
Collaboration, STAR, Filimonov, K.
core   +2 more sources

Robocasting of a Water‐Based Biopolymer/WO3 Nanopowder Paste as a Precursor to Tungsten Carbide Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
This study demonstrates a novel, additive manufacturing approach to produce complex, porous tungsten carbide structures using water‐based direct ink writing/robocasting. Leveraging a modified commercial printer and heat treatment, the process yields lightweight, electrically conductive 3D architectures capable of supporting a mechanical load.
James Bentley Bevis   +3 more
wiley   +1 more source

Very Forward proton-proton interactions with the LHCf detector

open access: yes, 2013
The LHCf experiment has been designed to precisely measure very forward neutral particle spectra produced in proton-proton collisions at LHC up to an energy of 14 TeV in the center of mass system.
Tricomi, Alessia
core  

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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