Pulsed Electrochemical Mass Spectrometry for Operando Tracking of Interfacial Processes in Small-Time-Constant Electrochemical Devices such as Supercapacitors

2017 ◽  
Vol 9 (47) ◽  
pp. 41224-41232 ◽  
Author(s):  
Nicolas Batisse ◽  
Encarnación Raymundo-Piñero
Keyword(s):  
Mass Spectrometry ◽  
Time Constant ◽  
Small Time ◽  
Interfacial Processes ◽  
Electrochemical Devices

Design and simulation of the AC-coupled burst-mode receiver with the small time constant

2008 ◽  
Author(s):  
Qiuyuan Huang ◽  
Luling Liu ◽  
Senmao Li ◽  
Leijun Sun
Keyword(s):  
Time Constant ◽  
Small Time ◽  
Burst Mode

Dynamic Performance Characteristics, Part 1

2001 ◽  
Author(s):  
Fred V. Brock ◽  
Scott J. Richardson
Keyword(s):  
Differential Equations ◽  
Time Constant ◽  
Dynamic Performance ◽  
Small Time ◽  
Performance Characteristics ◽  
Actual System ◽  
Physical Systems ◽  
Air Speed ◽  
Linear Differential ◽  
Static Sensitivity

When the input to a sensor is changing rapidly, we observe performance characteristics that are due to the change in input and are not related to static performance characteristics. In this chapter we will assume that a static calibration has been applied so that we can consider dynamic performance independently of static characteristics. The terms “linear” and “nonlinear” have been used in chap. 3 in the static sense. Now they are being used in the dynamic sense where “linear” connotes the applicability of the superposition property. A given sensor could be nonlinear in the static sense (e.g., a PRT is nonlinear in that is static sensitivity is not constant over the range) but could be linear in the dynamic sense (modeled by a linear differential equation). We use differential equations to model this dynamic performance while realizing the models can never be exact. If the dynamic behavior of physical systems can be described by linear differential equations with constant coefficients, the analysis is relatively easy because the solutions are well known. Such equations are always approximations to the actual performance of physical systems that are often nonlinear, vary with time, and have distributed parameters. The justification for the use of simple, readily solved models must be the quality of the fit of the solution to the actual system output and the usefulness of the resulting analysis. Dynamic performance characteristics define the way instruments react to measurand fluctuations. When a temperature sensor is mounted on an airplane these characteristics will indicate what the sensor “sees.” If the airplane flies through a cloud with a slow sensor (where time constant is large) it may not register change of temperature or humidity. That would not be tolerable if we wanted to measure the cloud. Similarly, if the airplane flies through turbulence we would like to measure changes in air speed. Variations in temperature and humidity would be vital in the flight of a radiosonde, so again the time constant of the sensors would be considered. Fluxes of heat, water vapor, and momentum near the ground require fast sensors (with small time constants).

Inversions of time-domain spectral induced polarization data using stretched exponential

2019 ◽  
Vol 219 (3) ◽  
pp. 1851-1865
Author(s):  
Seogi Kang ◽  
Douglas W Oldenburg
Keyword(s):  
Time Constant ◽  
Time Domain ◽  
Induced Polarization ◽  
Small Time ◽  
Mineral Deposit ◽  
The Body ◽  
Stretched Exponential ◽  
Simultaneous Inversion ◽  
Spectral Induced Polarization ◽  
Alteration Halo

SUMMARY We provide a two-stage approach to extract spectral induced polarization (SIP) information from time-domain IP data. In the first stage we invert dc data to recover the background conductivity. In the second, we solve a linear inverse problem and invert all time channels simultaneously to recover the IP parameters. The IP decay curves are represented by a stretched exponential (SE) rather than the traditional Cole–Cole model, and we find that defining the parameters in terms of their logarithmic values is advantageous. To demonstrate the capability of our simultaneous SIP inversion we use synthetic data simulating a porphyry mineral deposit. The challenge is to image a mineral body that is hosted within an alteration halo having the same chargeability but a different time constant. For a 2-D problem, we were able to distinguish the body using our simultaneous inversion but we were not successful in using a sequential (or conventional) SIP inversion approach. For the 3-D problem we recovered 3-D distributions of the SIP parameters and used those to construct a 3-D rock model having four rock units. Three chargeable units were distinguished. The compact mineralization zone, having a large time constant, was distinguished from the circular alteration halo that had a small time constant. Finally, to promote the use of the SIP technique, and to have further development of SIP inversion, all examples presented in this paper are available in our open source resources (https://github.com/simpeg-research/kang-2018-spectral-inducedpolarization).

scholarly journals The Measurement of Inductances with very small Time Constant

1911 ◽  
Vol 32 (6) ◽  
pp. 609-611
Author(s):  
F. W. Grover ◽  
H. L. Curtis
Keyword(s):  
Time Constant ◽  
Small Time

How SIMS microscopy can be used in medicine

1992 ◽  
Vol 50 (2) ◽  
pp. 1602-1603
Author(s):  
Philippe Fragu
Keyword(s):  
Mass Spectrometry ◽  
Biomedical Applications ◽  
Secondary Ion Mass Spectrometry ◽  
Chemical Elements ◽  
Biological Applications ◽  
The Past ◽  
Potential Source ◽  
Secondary Ion ◽  
Chemical Integrity ◽  
Scientific Endeavour

The identification, localization and quantification of intracellular chemical elements is an area of scientific endeavour which has not ceased to develop over the past 30 years. Secondary Ion Mass Spectrometry (SIMS) microscopy is widely used for elemental localization problems in geochemistry, metallurgy and electronics. Although the first commercial instruments were available in 1968, biological applications have been gradual as investigators have systematically examined the potential source of artefacts inherent in the method and sought to develop strategies for the analysis of soft biological material with a lateral resolution equivalent to that of the light microscope. In 1992, the prospects offered by this technique are even more encouraging as prototypes of new ion probes appear capable of achieving the ultimate goal, namely the quantitative analysis of micron and submicron regions. The purpose of this review is to underline the requirements for biomedical applications of SIMS microscopy.Sample preparation methodology should preserve both the structural and the chemical integrity of the tissue.

Imaging of Al-Li-Cu alloys with a Scanning Ion Microprobe

1990 ◽  
Vol 48 (2) ◽  
pp. 314-315
Author(s):  
K.K. Soni ◽  
D.B. Williams ◽  
J.M. Chabala ◽  
R. Levi-Setti ◽  
D.E. Newbury
Keyword(s):  
Mass Spectrometry ◽  
Secondary Ion Mass Spectrometry ◽  
Equilibrium Phase ◽  
Icosahedral Symmetry ◽  
Ion Microprobe ◽  
X Ray ◽  
Cu Alloys ◽  
Two Phases ◽  
The University ◽  
Secondary Ion

In contrast to the inability of x-ray microanalysis to detect Li, secondary ion mass spectrometry (SIMS) generates a very strong Li+ signal. The latter’s potential was recently exploited by Williams et al. in the study of binary Al-Li alloys. The present study of Al-Li-Cu was done using the high resolution scanning ion microprobe (SIM) at the University of Chicago (UC). The UC SIM employs a 40 keV, ∼70 nm diameter Ga+ probe extracted from a liquid Ga source, which is scanned over areas smaller than 160×160 μm2 using a 512×512 raster. During this experiment, the sample was held at 2 × 10-8 torr.In the Al-Li-Cu system, two phases of major importance are T1 and T2, with nominal compositions of Al2LiCu and Al6Li3Cu respectively. In commercial alloys, T1 develops a plate-like structure with a thickness <∼2 nm and is therefore inaccessible to conventional microanalytical techniques. T2 is the equilibrium phase with apparent icosahedral symmetry and its presence is undesirable in industrial alloys.

Applications of Time-OF-Flight Secondary Ion Mass Spectrometry (TOF-SIMS)

1990 ◽  
Vol 48 (2) ◽  
pp. 308-309
Author(s):  
Bruno Schueler ◽  
Robert W. Odom
Keyword(s):  
Mass Spectrometry ◽  
Secondary Ion Mass Spectrometry ◽  
Structural Information ◽  
Time Of Flight ◽  
Biological Tissues ◽  
Polymer Surfaces ◽  
Tof Sims ◽  
Secondary Ions ◽  
Ion Mass Spectrometry ◽  
Secondary Ion

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) provides unique capabilities for elemental and molecular compositional analysis of a wide variety of surfaces. This relatively new technique is finding increasing applications in analyses concerned with determining the chemical composition of various polymer surfaces, identifying the composition of organic and inorganic residues on surfaces and the localization of molecular or structurally significant secondary ions signals from biological tissues. TOF-SIMS analyses are typically performed under low primary ion dose (static SIMS) conditions and hence the secondary ions formed often contain significant structural information.This paper will present an overview of current TOF-SIMS instrumentation with particular emphasis on the stigmatic imaging ion microscope developed in the authors’ laboratory. This discussion will be followed by a presentation of several useful applications of the technique for the characterization of polymer surfaces and biological tissues specimens. Particular attention in these applications will focus on how the analytical problem impacts the performance requirements of the mass spectrometer and vice-versa.

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