•An improved protocol for preparing TEM samples of CNCs is proposed.•No radioactive stain or altering TEM grid surface properties involved.•A dunking rinse method controls over-application of ...stain.•Troubleshooting table to resolve common issues when imaging CNCs.
Characterization of cellulose nanocrystals (CNCs) is often complex and tedious. With their increased use for biological materials, polymer reinforcing agents, and other applications, better characterization methods of CNCs are needed to ensure product quality. However, because of their small size, hydrogen bonding, and low electron density, individual CNCs are difficult to image with high resolution and magnification using electron microscopy. Methods to help counter these challenges include staining for increased contrast and techniques to increase dispersion. This work tested several stains, dispersing agents, and sample supports to find a consistent method of individualizing CNCs and providing good contrast for imaging in transmission electron microscopy (TEM). The most consistent method found uses a low concentration of CNCs, bovine serum albumin as a dispersing agent, and Nanovan® as the contrasting stain on a silicon monoxide-coated Formvar TEM grid.
The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging ...capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.
Design, calibration, and performance of the MINERvA detector Aliaga, L.; Bagby, L.; Baldin, B. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
04/2014, Letnik:
743
Journal Article
Recenzirano
Odprti dostop
The MINERvA66Main INjector ExpeRiment ν-A. experiment is designed to perform precision studies of neutrino-nucleus scattering using νμ and ν¯μ neutrinos incident at 1–20GeV in the NuMI beam at ...Fermilab. This article presents a detailed description of the MINERvA detector and describes the ex situ and in situ techniques employed to characterize the detector and monitor its performance. The detector is composed of a finely segmented scintillator-based inner tracking region surrounded by electromagnetic and hadronic sampling calorimetry. The upstream portion of the detector includes planes of graphite, iron and lead interleaved between tracking planes to facilitate the study of nuclear effects in neutrino interactions. Observations concerning the detector response over sustained periods of running are reported. The detector design and methods of operation have relevance to future neutrino experiments in which segmented scintillator tracking is utilized.
The D0 Silicon Microstrip Tracker Ahmed, S.N.; Aoki, M.; Åsman, B. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
04/2011, Letnik:
634, Številka:
1
Journal Article
Recenzirano
Odprti dostop
This paper describes the mechanical design, the readout chain, the production, testing and the installation of the Silicon Microstrip Tracker of the D0 experiment at the Fermilab Tevatron collider. ...In addition, we describe the performance and operational experience of the detector during the experiment data collection between 2001 and 2010.
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