In order to better understand the behavior of Lithium-ion batteries under mechanical abuse, a coupled modeling methodology encompassing the mechanical, thermal and electrical response is presented for predicting short circuit under external crush. The combined mechanical-electric-thermal response is simulated in a commercial finite element software LS-DYNA® using a representative-sandwich finite-element model, where electrical-thermal modeling is conducted after an instantaneous mechanical crush. The model includes an explicit representation of each individual component such as the active material, current collector, separator, etc., and predicts their mechanical deformation under quasi-static compression and indentation. Model predictions show good agreement with experiments: the fracture of the battery structure under anindentation test is accurately predicted. The electrical-thermal simulation predicts the current density and temperature distribution in a reasonable manner. Whereas previously reported models consider the mechanical response exclusively, we use the electrical contact between active materials following the failure of the separator as a criterion for short circuit. These results are used to build a lumped-representative sandwich model that is computationally efficient and captures behavior at the cell level without resolving the individual layers.
The safety behavior of lithium-ion batteries under external mechanical crush is a critical concern, especially during large scale deployment. We previously presented a sequentially coupled mechanical-electrical-thermal modeling approach for studying mechanical abuse induced short circuit. In this work, we study different mechanical test conditions and examine the interaction between mechanical failure and electrical-thermal responses, by developing a simultaneous coupled mechanical-electrical-thermal model. The present work utilizes a single representative-sandwich (RS) to model the full pouch cell with explicit representations for each individual component such as the active material, current collector, separator, etc. Anisotropic constitutive material models are presented to describe the mechanical properties of active materials and separator. The model predicts accurately the force-strain response and fracture of battery structure, simulates the local failure of separator layer, and captures the onset of short circuit for lithium-ion battery cell under sphere indentation tests with three different diameters.Electrical-thermal responses to the three different indentation tests are elaborated and discussed. Numerical studies are presented to show the potential impact of test conditions on the electrical-thermal behavior of the cell after the occurrence of short circuit.
Raman spectroscopy and imaging at the singlemolecular level in both signal sensitivity and spatial resolution have been a long dream. A recent experimental study of singlemolecule Raman mapping with a subnanometer resolution by using a tip-enhanced Raman scattering (TERS) technique is a great step closer to this great dream. However, how the subnanometer spatial resolution is possible with a Raman excitation light spot ("hot spot") of diameter over 10 nm formed between the tip−substrate nanogap to excite and probe the molecule still remains mysterious. Here we present an optical theory of Raman scattering that accounts for the strong near-field self-interaction of molecule with the plasmonic nanogap due to multiple elastic scattering of light by the molecule. The result shows that the self-interaction effect strongly modulates the Raman excitation and radiation in both the signal intensity and spatial sensitivity, leading to a "super-hot spot" and subnanometer lateral resolution of Raman mapping. The optical theory can help to uncover the full picture of light-matter interaction of atoms and molecules with plasmonic nanostructures and explore unknown frontiers of physics and chemistry at nanoscale.
Testing hypotheses of neuromuscular function during locomotion ideally requires the ability to record cellular responses and to stimulate the cells being investigated to observe downstream behaviors [1]. The inability to stimulate in free flight has been a long-standing hurdle for insect flight studies. The miniaturization of computation and communication technologies has delivered ultra-small, radio-enabled neuromuscular recorders and stimulators for untethered insects [2-8]. Published stimulation targets include the areas in brain potentially responsible for pattern generation in locomotion [5], the nerve chord for abdominal flexion [9], antennal muscles [2, 10], and the flight muscles (or their excitatory junctions) [7, 11-13]. However, neither fine nor graded control of turning has been demonstrated in free flight, and responses to the stimulation vary widely [2, 5, 7, 9]. Technological limitations have precluded hypotheses of function validation requiring exogenous stimulation during flight. We investigated the role of a muscle involved in wing articulation during flight in a coleopteran. We set out to identify muscles whose stimulation produced a graded turning in free flight, a feat that would enable fine steering control not previously demonstrated. We anticipated that gradation might arise either as a function of the phase of muscle firing relative to the wing stroke (as in the classic fly b1 muscle [14, 15] or the dorsal longitudinal and ventral muscles of moth [16]), or due to regulated tonic control, in which phase-independent summation of twitch responses produces varying amounts of force delivered to the wing linkages [15, 17, 18].
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.