Clebsch-Gordan Coefficients for the Extended Quantum-Mechanical Poincar\'e Group and Angular Correlations of Decay Products

This paper describes Clebsch-Gordan coefficients (CGCs) for unitary irreducible representations (UIRs) of the extended quantum mechanical Poincar\'e group \pt. `Extended' refers to the extension of the 10 parameter Lie group that is the Poincar\'e group by the discrete symmetries $C$, $P$, and $T$; `quantum mechanical' refers to the fact that we consider projective representations of the group. The particular set of CGCs presented here are applicable to the problem of the reduction of the direct product of two massive, unitary irreducible representations (UIRs) of \pt with positive energy to irreducible components. Of the sixteen inequivalent representations of the discrete symmetries, the two standard representations with $U_C U_P = \pm 1$ are considered. Also included in the analysis are additive internal quantum numbers specifying the superselection sector. As an example, these CGCs are applied to the decay process of the $\Upsilon(4S)$ meson.Comment: 26 pages, double spaced. Version 2: typos corrected, introduction change

Systematic approach for the test data generation and validation of ISC/ ESC detection methods

Various methods published in recent years for reliable detection of battery faults (mainly internal short circuit (ISC)) raise the question of comparability and cross-method evaluation, which cannot yet be answered due to significant differences in training data and boundary conditions. This paper provides a Monte Carlo-like simulation approach to generate a reproducible, comprehensible and large dataset based on an extensive literature background on common assumptions and simulation parameters. In some cases, these assumptions are quite different from field data, as shown by comparison with experimentally determined values. Two relatively simple ISC detection methods are tested on the generated dataset and their performance is evaluated to illustrate the proposed approach. The evaluation of the detection performance by quantitative measures such as the Youden-index shows a high divergence with respect to internal and external parameters such as threshold level and cell-to-cell variations (CtCV), respectively. These results underline the importance of quantitative evaluations based on identical test data. The proposed approach is able to support this task by providing cost-effective test data generation with incorporation of known factors affecting detection quality

Triggering and characterisation of realistic internal short circuits in lithium-ion pouch cells: a new approach using precise needle penetration

The internal short circuit (ISC) in lithium-ion batteries is a serious problem because it is probably the most common cause of a thermal runaway (TR) that still presents many open questions although it has been intensively investigated. Therefore this article focuses on the generation and characterisation of the local single-layer ISC, which is particularly relevant in practice application. A new, very promising method of precise needle penetration made it possible to generate the most safety-critical short-circuit type, the contact between the Al-Collector and the graphite active material of the anode reliable, demonstrated on a 10 Ah Graphite/NMC pouch cell. The special efforts in achieving high reproducibility as well as the detailed analysis of the initiated internal short-circuit conditions led to more reliable and meaningful results. A comprehensive approach to characterisation has been made by detailed measurement of the dynamic short-circuit evolution and a subsequent post-characterisation, which included the application of different electrochemical measurement techniques as well as a post-abuse analysis. It was shown that the cells demonstrated a very individual and difficult-to-predict behaviour, which is a major challenge for early failure detection and risk assessment of cells with an existing or former ISC. On the one hand, it is found that despite high local temperatures of over 1260 ◦C and significant damage to the cell-internal structure, the cell did not develop a TR even with further cycling. On the other hand, it was observed that the TR occurs spontaneously without any previous abnormalities. Based on the overall test results, it was shown that at the high state of charge (SOC = 100 %) even small, dynamically developing voltage drops must be classified as safety-critical for the cell. For reliable and early failure detection, the first voltage drops of the ISC must already be detected

Systematic approach for the test data generation and validation of ISC/ESC detection methods

Various methods published in recent years for reliable detection of battery faults (mainly internal short circuit (ISC)) raise the question of comparability and cross-method evaluation, which cannot yet be answered due to significant differences in training data and boundary conditions. This paper provides a Monte Carlo-like simulation approach to generate a reproducible, comprehensible and large dataset based on an extensive literature search on common assumptions and simulation parameters. In some cases, these assumptions are quite different from field data, as shown by comparison with experimentally determined values. Two relatively simple ISC detection methods are tested on the generated dataset and their performance is evaluated to illustrate the proposed approach. The evaluation of the detection performance by quantitative measures such as the Youden-index shows a high divergence with respect to internal and external parameters such as threshold level and cell-to-cell variations (CtCV), respectively. These results underline the importance of quantitative evaluations based on identical test data. The proposed approach is able to support this task by providing cost-effective test data generation with incorporation of known factors affecting detection quality

Comparison of model-based and sensor-based detection of thermal runaway in Li-ion battery modules for automotive application

In recent years, research on lithium–ion (Li-ion) battery safety and fault detection has become an important topic, providing a broad range of methods for evaluating the cell state based on voltage and temperature measurements. However, other measurement quantities and close-to-application test setups have only been sparsely considered, and there has been no comparison in between methods. In this work, the feasibility of a multi-sensor setup for the detection of Thermal Runaway failure of automotive-size Li-ion battery modules have been investigated in comparison to a model-based approach. For experimental validation, Thermal Runaway tests were conducted in a close-to-application configuration of module and battery case—triggered by external heating with two different heating rates. By two repetitions of each experiment, a high accordance of characteristics and results has been achieved and the signal feasibility for fault detection has been discussed. The model-based method, that had previously been published, recognised the thermal fault in the fastest way—significantly prior to the required 5 min pre-warning time. This requirement was also achieved with smoke and gas sensors in most test runs. Additional criteria for evaluating detection approaches besides detection time have been discussed to provide a good starting point for choosing a suitable approach that is dependent on application defined requirements, e.g., acceptable complexity

Comparison of model-based and sensor-based detection of thermal runaway in Li-ion battery modules for automotive application

In recent years, research on lithium-ion (Li-ion) battery safety and fault detection has become an important topic providing a broad range of methods for evaluating the cell state based on voltage and temperature measurements. However, other measurement quantities and close-to-application test setups were only sparsely considered yet, not has been a comparison in between methods. In this work the feasibility of a multi-sensor setup for detection of Thermal Runaway failure of automotive-size Li-ion battery modules have been investigated in comparison to a model-based approach. For experimental validation Thermal Runaway tests were conducted in a close-to-application configuration of module and battery case – triggered by external heating with two different heating rates. By two repetitions of each experiment high accordance of characteristics and results has been achieved and the signal feasibility for fault detection has been discussed. The before published model-based method recognised the thermal fault in the fastest way – significantly previously the required 5 min pre-warning time. This requirement was also achieved with smoke and gas sensors in most test runs. Additional criteria for evaluating detection approaches besides detection time have been discussed to provide a good starting point for choosing a suitable approach dependent on application defined requirements e.g. acceptable complexity

Biodiversity post-2020: Closing the gap between global targets and national-level implementation

National and local governments need to step up efforts to effectively implement the post-2020 global biodiversity framework of the Convention on Biological Diversity to halt and reverse worsening biodiversity trends. Drawing on recent advances in interdisciplinary biodiversity science, we propose a framework for improved implementation by national and subnational governments. First, the identification of actions and the promotion of ownership across stakeholders need to recognize the multiple values of biodiversity and account for remote responsibility. Second, cross-sectorial implementation and mainstreaming should adopt scalable and multifunctional ecosystem restoration approaches and target positive futures for nature and people. Third, assessment of progress and adaptive management can be informed by novel biodiversity monitoring and modeling approaches handling the multidimensionality of biodiversity change

Nicotinic Receptors Underlying Nicotine Dependence: Evidence from Transgenic Mouse Models.

Nicotine underlies the reinforcing properties of tobacco cigarettes and e-cigarettes. After inhalation and absorption, nicotine binds to various nicotinic acetylcholine receptor (nAChR) subtypes localized on the pre- and postsynaptic membranes of cells, which subsequently leads to the modulation of cellular function and neurotransmitter signaling. In this chapter, we begin by briefly reviewing the current understanding of nicotine's actions on nAChRs and highlight considerations regarding nAChR subtype localization and pharmacodynamics. Thereafter, we discuss the seminal discoveries derived from genetically modified mouse models, which have greatly contributed to our understanding of nicotine's effects on the reward-related mesolimbic pathway and the aversion-related habenulo-interpeduncular pathway. Thereafter, emerging areas of research focusing on modulation of nAChR expression and/or function are considered. Taken together, these discoveries have provided a foundational understanding of various genetic, neurobiological, and behavioral factors underlying the motivation to use nicotine and related dependence processes, which are thereby advancing drug discovery efforts to promote long-term abstinence