High-sensitivity vector magnetometer for measuring magnetic torque at low temperatures

2006 ◽  
Vol 77 (2) ◽  
pp. 025101 ◽  
Author(s):  
L. Benito ◽  
J. I. Arnaudas ◽  
A. del Moral
Keyword(s):  
Low Temperatures ◽  
High Sensitivity ◽  
Magnetic Torque ◽  
Vector Magnetometer ◽  
Sensitivity Vector

Using Exponential Cubic Splines to Predict Low Temperature Behavior of Elastomeric Materials

1994 ◽  
Author(s):  
Terry E. Shoup ◽  
George R. Fegan
Keyword(s):  
Experimental Data ◽  
Elastic Modulus ◽  
Low Temperatures ◽  
Analytical Techniques ◽  
High Sensitivity ◽  
Considerable Difficulty ◽  
Spline Curves ◽  
Different Types ◽  
Elastomeric Materials ◽  
Energy Absorbing

Abstract Because of their desirable elastic and energy absorbing properties, elastomeric materials have been widely used as shock mounts and pressure seals. The high sensitivity of the elastic modulus of these materials to changes in temperature has been a source of considerable difficulty to the development of robust design methods based on analytical techniques. This paper presents a simple analytical method for predicting the elastic modulus for a group of five different types of elastomers when used at low temperatures. The method is based on the application of exponential cubic spline curves to smooth experimental data. The method is applied to experimental data from the literature to illustrate its usefulness.

scholarly journals A highly selective and sensitive H2S sensor at low temperatures based on Cr-doped α-Fe2O3 nanoparticles

RSC Advances ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 4150-4156 ◽  
Author(s):  
Dongyang Xue ◽  
Rui Zhou ◽  
Xiaoping Lin ◽  
Xiaochuan Duan ◽  
Qiuhong Li ◽  
...  
Keyword(s):  
Low Temperature ◽  
Low Temperatures ◽  
Hydrothermal Reaction ◽  
High Sensitivity ◽  
Fe2o3 Nanoparticles ◽  
Sensitivity And Selectivity ◽  
One Step

Cr-doped α-Fe2O3 nanoparticles were synthesized by one-step hydrothermal reaction and showed high sensitivity and selectivity to H2S at low temperature.

Optimally Designed Nonlinear Feedback Excitation for High-Sensitivity Sensing

2009 ◽  
Author(s):  
Andrew R. Sloboda ◽  
Bogdan I. Epureanu
Keyword(s):  
Chaotic Behavior ◽  
High Sensitivity ◽  
Harmonic Excitation ◽  
Pattern Search ◽  
Control Parameters ◽  
Nonlinear Feedback ◽  
Linear Vibration ◽  
Optimal Excitation ◽  
Multiple Sensor ◽  
Sensitivity Vector

Employing sensitivity vector field (SVF) analysis in active micro-sensors can increase both their sensitivity and their ability to differentiate between changes in multiple sensor parameters. However, since SVF analysis is based on quantifying attractor deformations in state space, maximizing its effectiveness depends on selecting a sensor excitation that generates an attractor having suitable deformation with respect to the parameter(s) of interest. This paper addresses issues surrounding such system excitation design for a simple, linear vibration-based sensor having a combination of harmonic and nonlinear feedback excitation. In order to reframe the search for an optimal excitation as a search for a set of optimal control parameters, the excitation is considered to be of a specified form with a set of adjustable control parameters. Determining how to adjust the excitation parameters so as to maximize the magnitude of the resulting sensitivity vectors is then the formal goal. Using a pattern search method that avoids difficulties caused by bifurcations, we show that improved excitation can be designed reliably and efficiently. We also show that for short trajectory evolution times (suitable for “large” sensor perturbations) limit cycle behavior generates the best SVFs while for longer evolution times (suitable for “small” sensor perturbations) chaotic behavior may be more useful. Other issues discussed include the relative importance of various controller terms and the significance of harmonic excitation phase when generating sensitivity vectors.

High-Sensitivity Mass Sensing Based on Enhanced Nonlinear Dynamics and Attractor Morphing Modes

2006 ◽  
Author(s):  
Shih-Hsun Yin ◽  
Bogdan I. Epureanu
Keyword(s):  
Lead Zirconate Titanate ◽  
Vector Fields ◽  
Experimental System ◽  
High Sensitivity ◽  
Lead Zirconate ◽  
Chaotic Regime ◽  
Nonlinear Feedback ◽  
Regime Changes ◽  
Distribution Of Points ◽  
Sensitivity Vector

This paper demonstrates two novel methods for identifying small parametric variations in an experimental system based on the analysis of sensitivity vector fields (SVFs) and probability density functions (PDFs). The experimental system includes a smart sensing beam excited by a nonlinear feedback excitation through two PZT (lead zirconate titanate) patches symmetrically bonded on both sides at the root of the beam. The nonlinear feedback excitation requires the measurement of the dynamics (e.g. velocity of one point at the tip of the beam) and a nonlinear feedback loop, and is designed such that the beam vibrates in a chaotic regime. Changes in the state space attractor of the dynamics due to small parametric variations can be captured by SVFs which, in turn, are collected by applying point cloud averaging (PCA) to points distributed in the attractors for nominal and changed parameters. Also, the PDFs characterize statistically the distribution of points in the attractors. The differences between the PDFs of the attractors for different changed parameters and the baseline attractor can provide different attractor morphing modes for identifying variations in distinct parameters. The experimental results based on the proposed approaches show that very small amounts of added mass at different locations along the beam can be accurately identified.

Manganese Oxide Nanoarchitectures as Chemoresistive Gas Sensors to Monitor Fruit Ripening

2020 ◽  
Vol 20 (5) ◽  
pp. 3025-3030 ◽  
Author(s):  
Lorenzo Bigiani ◽  
Dario Zappa ◽  
Elisabetta Comini ◽  
Chiara Maccato ◽  
Alberto Gasparotto ◽  
...  
Keyword(s):  
Quality Control ◽  
Gas Sensors ◽  
Vapor Deposition ◽  
Low Temperatures ◽  
Metal Particle ◽  
Chemical Vapor ◽  
High Sensitivity ◽  
Food Quality Control ◽  
Efficient Detection ◽  
First Time

The efficient detection of low-concentration ethylene is a challenging issue of key importance for food quality control end-uses. Herein, we report on the fabrication of MnO2-based nanoarchitectures by a two-step plasma-assisted process, consisting in the initial chemical vapor deposition of MnO2 (host) on polycrystalline Al2O3 substrates and the subsequent functionalization with Ag and Au-based nanoparticles (guest) by sputtering processes. The resulting composites, characterized by a high Ag/Au dispersion and an effective host-guest contact, were tested for the first time as chemoresistive gas sensors for ethylene recognition at low temperatures. The high sensitivity and promising responses, enhanced by metal particle introduction, candidate the target systems as attractive platforms for the eventual monitoring of vegetables/fruits ripening and ageing.

scholarly journals ALGORITHMIC COOLING OF SPINS: A PRACTICABLE METHOD FOR INCREASING POLARIZATION

2004 ◽  
Vol 02 (04) ◽  
pp. 461-477 ◽  
Author(s):  
JOSÉ M. FERNANDEZ ◽  
SETH LLOYD ◽  
TAL MOR ◽  
VWANI ROYCHOWDHURY
Keyword(s):  
Nmr Spectroscopy ◽  
Low Temperatures ◽  
Open Systems ◽  
High Sensitivity ◽  
Quantum Gates ◽  
Quantum Computers ◽  
Short Term ◽  
Near Future ◽  
Practicable Method ◽  
Far Future

An efficient technique to generate ensembles of spins that are highly polarized by external magnetic fields is the Holy Grail in Nuclear Magnetic Resonance (NMR) spectroscopy. Since spin-half nuclei have steady-state polarization biases that increase inversely with temperature, spins exhibiting high polarization biases are considered cool, even when their environment is warm. Existing spin-cooling techniques are highly limited in their efficiency and usefulness. Algorithmic cooling is a promising new spin-cooling approach that employs data compression methods in open systems. It reduces the entropy of spins on long molecules to a point far beyond Shannon's bound on reversible entropy manipulations, thus increasing their polarization. Here we present an efficient and experimentally feasible algorithmic cooling technique that cools spins to very low temperatures even on short molecules. This practicable algorithmic cooling could lead to breakthroughs in high-sensitivity NMR spectroscopy in the near future, and to the development of scalable NMR quantum computers in the far future. Moreover, while the cooling algorithm itself is classical, it uses quantum gates in its implementation, thus representing the first short-term application of quantum computing devices.

Faraday Force Magnetometer for High-Sensitivity Magnetization Measurements at Very Low Temperatures and High Fields

1994 ◽  
Vol 33 (Part 1, No. 9A) ◽  
pp. 5067-5072 ◽  
Author(s):  
Toshiro Sakakibara ◽  
Hiroyuki Mitamura ◽  
Takashi Tayama ◽  
Hiroshi Amitsuka
Keyword(s):  
Low Temperatures ◽  
High Sensitivity ◽  
Magnetization Measurements ◽  
High Fields

High-sensitivity vector magnetic field sensor based on side-polished fiber plasmon and ferrofluid

2018 ◽  
Vol 43 (19) ◽  
pp. 4743 ◽  
Author(s):  
Zhupeng Jiang ◽  
Jiangli Dong ◽  
Shiqi Hu ◽  
Yaxin Zhang ◽  
Yaofei Chen ◽  
...  
Keyword(s):  
Magnetic Field ◽  
High Sensitivity ◽  
Magnetic Field Sensor ◽  
Vector Magnetic Field ◽  
Field Sensor ◽  
Sensitivity Vector ◽  
Side Polished Fiber

Bio-templated fabrication of hierarchically porous WO3 microspheres from lotus pollens for NO gas sensing at low temperatures

RSC Advances ◽  
2015 ◽  
Vol 5 (37) ◽  
pp. 29428-29432 ◽  
Author(s):  
Xiao-Xue Wang ◽  
Kuan Tian ◽  
Hua-Yao Li ◽  
Ze-Xing Cai ◽  
Xin Guo
Keyword(s):  
Porous Structure ◽  
Low Temperatures ◽  
Gas Sensing ◽  
High Sensitivity ◽  
Fast Response ◽  
Hierarchically Porous ◽  
Response And Recovery

Lotus pollen was used as a template to prepare WO3 microspheres. The porous structure of the microspheres is ideal for gas sensing. The microsphere-based sensor has high sensitivity (S = 46.2) to 100 ppm NO gas with fast response and recovery speed 62 s/223 s) at 200 °C.

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