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Recently, miniaturization and three-dimensional integration for improving the performance of electric devices have been accelerated, and smaller storage batteries with higher energy density and shrinked electric components have been more required. Therefore, failure analysis technologies targeted for these cutting-edged devices should be developed for increasing production yields and reducing product accidents. In mass production processes, pre-shipment inspections are performed on the core parts of electronic devices. In the case of electronic parts, energization check is adopted, and in the case of storage batteries, voltage drop, that is called to be an aging test, is checked. However, many cases have been reported in which products, that have passed the inspection, cause accidents. One of the typical causes of failures related about electronic components is internal electric-short caused by foreign matters mixed into the insulation or whiskers accidentally generated from the electrodes and wiring. Similarly, storage batteries also accidentally have internal short circuits due to foreign matter contaminations and dendrite formation at the electrodes. The internal short-circuited points of electronic components and storage batteries are identified by X-ray imaging method. However, it is difficult to acquire the contrast due to the lack of the dynamic range required for visualization of short-circuited parts because the wirings and insulation areas between electrodes have been significantly miniaturized. In addition, short circuits between wirings on the surface of electronic circuit boards have been visualized by thermography, although it is difficult to apply electronic components with multi-layered electrodes. Then we have focused on the relationship between the electric current distribution inside the devices and the magnetic field generated from it and spread toward outside, we have succeeded in deriving the analysis solution of the inverse problem for the first time. Combining this novel theory and a highly-sensitive magnetic field detection based on quantum effect, we have developed a subsurface electric current imaging system capable of detecting electric short-circuited points in the deep region. In this study, we discuss about the details of the theory about the analytical solution of the inverse problem and the visualization system, and show some results of failure analysis for actual electronic components and storage batteries. [1] Yuki Mima, Noriaki Oyabu, Takeshi Inao, Noriaki Kimura, Kenjiro Kimura, “Failure analysis of electric circuit board by high resolution magnetic field microscopy” Proceedings of IEEE CPMT Symposium Japan, pp.257-260, 2013. [2] Kenjiro Kimura, Yuki Mima, Noriaki Kimura, “Local electric current reconstruction theory for nondestructive inspection inside battery cell using magnetic field measurement”, Subsurface Imaging Science & Technology, 1, 1, pp.1-16, 2017. [3] Shogo Suzuki, Hideaki Okada, Kai Yabumoto, Seiju Matsuda, Yuki Mima, Noriaki Kimura, and Kenjiro Kimura, “Non-destructive visualization of short circuits in lithium-ion batteries by a magnetic field imaging system”, Japanese Journal of Applied Physics, Vol 60, No 5, pp.056502-1-4, 2021.

With the rapid spread of electric vehicles and hybrid vehicles in recent years, the energy density of lithium-ion batteries, which are the power sources of them, tends to increase.This means that the risk of ignition is further increased as represented by some fire accident case of an EV vehicle that had taken long time to extinguish, and thus eventually makes the requirement of safety management in the battery manufacturing process be expected stricter.To prevent ignition due to internal short circuit of battery, and eliminate a short-life battery product, we have been developing a technology to non-destructively visualize the self-discharged part inside the storage battery. In this technology, on the first, electric current is applied to the battery from external power source, and the leakage magnetic field that generated due to the internal electric current in the battery is sensed on outside of the battery. Next, the electric current density distribution inside the battery can be reconstructed and visualized three-dimensionally by using the spatial distribution of the measured magnetic field as the boundary condition and solving the inverse problem analytically. To measure leakage magnetic field with high sensitivity, it is necessary to take steps against disturbances as like DC magnetic field derived from magnetism or magnetic materials (often Ni is used for the collector foil), and AC magnetic fields generated from external circuits. In this method, two steps are used in combination for detection sensitivity of the pico-tesla order; (1) An AC current is applied to the battery, and the AC magnetic field generated in synchronization is phase-detected. (2) Install a small coil near the sensor and generate a DC cancel magnetic field by feedback control. By this method, it is possible to detect only the AC magnetic field corresponding to the applied current with high sensitivity in the linear operating region of the magnetic sensor. In actual detection of the leakage magnetic field, a DC voltage that balances with the output voltage of the battery is applied to the AC output of the AC current source connected to the battery so that the SOC of the storage battery is kept constant voltage. In addition to the above, the frequency of the AC output is usually set to 10 Hz or less to avoid the shielding effects of electrodes and the metallic package of the battery.By these steps and scanning two-dimensional of magnetic sensors or using a sensor array in which magnetic sensors are arranged two-dimensionally, the spatial distribution of the two-dimensional magnetic field outside the storage battery can be obtained. Since the sensor detects only one direction component of magnetic field, changing the direction of the sensor by 90 ° is needed. On data processing, some realistic structural assumptions are required to solve the inverse problem. (1) Defining that the plane parallel to the storage battery electrode plane is the XY plane, the Z component of the magnetic field vector is zero around the battery, and only X component and Y component remains as magnetic field vector components generated from internal current of the battery. (2) The thickness of the battery is sufficiently smaller than the size of the battery in the plane direction, that is, the three-dimensional current in the battery is confined in the thin two-dimensional plane. In the first step of the reconstruction, under the fact of (1), Laplace's equation is analytically solved in the "free space from the measurement surface to just above the electrode surface in the battery, without a magnetic source", and derive the two-dimensional magnetic field distribution directly above the electrode surface. In the next step, it is possible to obtain a three-dimensional current distribution inside the battery by analytically solving the Poisson-type equation and the electric current continuity equation under the realistic structural assumption of (2) with first calculation result as the boundary condition. In the presentation, we will introduce in detail the experiment and data processing for identifying the self-discharge point with this technology, including examples of visualizing the magnetic field distribution and current density distribution inside a battery after aging test.

The circadian clock system is associated with feeding and mood. Patients with night eating syndrome (NES) delay their eating rhythm and their mood declines during the evening and night, manifesting as time-specific depression. Therefore, we hypothesized that the NES feeding pattern might cause time-specific depression. We established new NES model by restricted feeding with high-fat diet during the inactive period under normal-fat diet ad libitum. The FST (forced swimming test) immobility time in the NES model group was prolonged only after lights-on, corresponding to evening and early night for humans. We examined the effect of the NES feeding pattern on peripheral clocks using PER2::LUCIFERASE knock-in mice and an in vivo monitoring system. Caloric intake during the inactive period would shift the peripheral clock, and might be an important factor in causing the time-specific depression-like behavior. In the NES model group, synthesis of serotonin and norepinephrine were increased, but utilization and metabolism of these monoamines were decreased under stress. Desipramine shortened some mice’s FST immobility time in the NES model group. The present study suggests that the NES feeding pattern causes phase shift of peripheral clocks and malfunction of the monoamine system, which may contribute to the development of time-specific depression.

In this paper, we report on our experiences with architecture compliance checking - the process of checking whether the planned or specified software architecture is obeyed by the running system - of an OSGi-based, dynamically evolving application in the office domain. To that end, we first show how to dynamically instrument a running system in the context of OSGi in order to collect run-time traces. Second, we explain how to bridge the abstraction gap between run-time traces and software architectures, through the construction of hierarchical Colored Petri nets (CP-nets). In addition, we demonstrate how to design reusable hierarchical CP-nets. In an industry example, we were able to extract views that helped us to identify a number of architecturally relevant issues (e.g., architectural style violations, behavior violations) that would not have been detected otherwise, and could have caused serious problems like system malfunctioning or unauthorized access to sensitive data. Finally, we package valuable experiences and lessons learned from this endeavor.