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For switched mode power converters, boundary conduction mode (BCM) operation is an attractive alternative to improve the bandwidth, overall size, and efficiency. In this article, a sensorless ripple current mode (SRCM) controller is proposed to achieve inductor-deviation-tolerant BCM operation for boost converter. Compared to conventional approaches with current sensing or ZCD, the proposed controller relies on a digital algorithm to ensure consistent BCM operation. The algorithm calculates on/off durations of the main switch so that the inductor current valley value converges to zero. The convergence process is proved by a damped current model with considerations of parasitics and output voltage ripple. Since the convergence is not related to the inductor value, the SRCM controller achieves inductor-deviation-tolerant BCM operation. Furthermore, to improve the power efficiency, an optimal transition condition and a compensation time are adopted to achieve valley switching (VS). Finally, both consistent BCM operation and VS are achieved by the proposed control strategy. Simulations and experimental results prove that the controller effectively improves the closed-loop stability, the robustness to inductor deviation, and the power efficiency. [ABSTRACT FROM AUTHOR]

In this paper, a linearized discrete charge balance (LDCB) control strategy is proposed for buck converter operating in discontinuous conduction mode (DCM). For DC-DC power converters, discrete charge balance (DCB) control is an attractive approach to improve the output voltage transient response. However, as a non-linear control strategy, the algorithm is complex, which is difficult for implementation. To reduce the complexity, this paper proposes the LDCB control strategy that is derived through linearizing conventional DCB controller. By deriving the differential functions of the DCB control algorithm, the small signal relationship between the input and output of DCB controller is explored. Furthermore, based on the relationship, the LDCB controller is formed through three parallel feed loops to the duty ratio. As a linear control approach, the achieved LDCB controller is greatly simplified for implementation. This not only saves the hardware cost, but also reduces the calculation lag, which provides potential to improve the switching frequency. Besides, since the LDCB controller shares the same small signal model as that of DCB controller, it achieves similar control loop bandwidth and transient performance. Effectiveness of the proposed LDCB control is verified by zero/pole plots, transient analyses and experimental results. [ABSTRACT FROM AUTHOR]

This article investigates modeling and control approaches to optimize the efficiency and power factor for discontinuous conduction mode boost power factor correction converters. First, with detailed consideration of parasitics and GaN HEMT transients, the input and output charges of the converter are exactly derived, where the rate forms the comprehensive charge rate (CCR) model. Second, based on the CCR model, the overall efficiency is derived. Since the overall efficiency is only related to the input voltage, output voltage, and switching on-time, an optimal on-time is calculated to achieve the maximum efficiency. Furthermore, with the optimal on-time, a maximum efficiency average current (MEAC) controller is proposed to regulate the input current while maintaining the maximum efficiency. With the predefined optimal on-time, a switching cycle modulation method is adopted to regulate the input current as sinusoid, which improves the power factor to unity. Finally, effectiveness of the MEAC control strategy is verified by simulations and experiments. Compared with conventional constant on-time control, it achieves an optimized efficiency and power factor over a large operation range. [ABSTRACT FROM AUTHOR]

Digital peak current mode (DPCM) control is widely used for dc–dc converters operating in continuous current mode. However, current tracking delay (CTD) in the system is normally neglected in the modeling stage, which leads to poor compensator design and degraded performance. This paper investigates CTD effect in boost converter with different DPCM controls. Based on dynamic relationship between the reference current and actual inductor current, the CTD transfer functions are derived, which improves the accuracy of small signal model. Since CTD degrades the phase margin of the system, equivalent migration of right half plane zero is proposed to model CTD effect. This method is very simple and straightforward, which facilitates the compensator design. Furthermore, two novel DPCM control strategies with minimized CTD are proposed, and they are based on duty cycle restriction and duty cycle extension, respectively. Both controls greatly reduce the CTD effect and improve the response speed. Besides, the duty cycle extension benefits from an extended pulsewidth modulation (ExPWM). This optimizes the calculation algorithm and speed, while improving the time margin for digital calculations. Combined with the proposed models and controls, the CTD effect is greatly reduced. The effectiveness is verified through detailed simulations and experiments. [ABSTRACT FROM AUTHOR]

This article reveals parasitics-induced current distortion (PCD) effect in discontinuous conduction mode boost power factor (PF) correction (PFC) converter. With consideration of parasitics, accurate inductor current is derived through total differential functions of line voltage, output voltage and duty cycle. Furthermore, the proposed current model is used to analyze PFC converter under conventional sensorless average current mode (SACM) control, which is achieved by a variable duty cycle. It is found that parasitics have considerable influence to the input current, and PCD leads to a degraded PF. In order to solve this issue, a current reshaping strategy is proposed to reduce the PCD phenomenon. Based on the damped current equations, a compensation gain is derived to reshape the input current, which reduces the current damping and distortion caused by parasitics. Both the PCD phenomenon and the current reshaping strategy are verified by simulations and experiments. [ABSTRACT FROM AUTHOR]

We achieve low-temperature Cu-to-Cu direct bonding using highly (111)-orientated Cu films. The bonding temperature can be lowered to 200°C at a stress of 114psi for 30min at 10−3 torr. The temperature is lower than the reflow temperature of 250°C for Pb-free solders. Our breakthrough is based on the finding that the Cu (111) surface diffusivity is the fastest among all the planes of Cu and the bonding process can occur through surface diffusion creep on the (111) surfaces. [ABSTRACT FROM AUTHOR]

Direct Cu-to-Cu bonding was achieved at temperatures of 150-250 °C using a compressive stress of 100 psi (0.69 MPa) held for 10-60 min at 10−3 torr. The key controlling parameter for direct bonding is rapid surface diffusion on (111) surface of Cu. Instead of using (111) oriented single crystal of Cu, oriented (111) texture of extremely high degree, exceeding 90%, was fabricated using the oriented nano-twin Cu. The bonded interface between two (111) surfaces forms a twist-type grain boundary. If the grain boundary has a low angle, it has a hexagonal network of screw dislocations. Such network image was obtained by plan-view transmission electron microscopy. A simple kinetic model of surface creep is presented; and the calculated and measured time of bonding is in reasonable agreement. [ABSTRACT FROM AUTHOR]

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain., Competing Interests: Competing interests: The authors declare no competing interests.

The brain's functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain., Competing Interests: Competing interests: The authors declare no competing interests.

Brain activity is intrinsically organised into spatiotemporal patterns, but it is still not clear whether these intrinsic patterns are functional or epiphenomenal. Using a simultaneous fMRI-EEG implementation of a well-known bistable visual task, we showed that the latent transient states in the intrinsic EEG oscillations can predict upcoming involuntarily perceptual transitions. The critical state predicting a dominant perceptual transition was characterised by the phase coupling between the precuneus (PCU), a key node of the Default Mode Network (DMN), and the primary visual cortex (V1). The interaction between the lifetime of this state and the PCU- > V1 Granger-causal effect is correlated with the perceptual fluctuation rate. Our study suggests that the brain's endogenous dynamics are phenomenologically relevant, as they can elicit a diversion between potential visual processing pathways, while external stimuli remain the same. In this sense, the intrinsic DMN dynamics pre-empt the content of consciousness., (© 2022. The Author(s).)

Human brains interpret external stimuli based on internal representations. One untested hypothesis is that the default-mode network (DMN), widely considered responsible for internally oriented cognition, can decode external information. Here, we posit that the unique structural and functional fingerprint of the precuneus (PCu) supports a prominent role for the posterior part of the DMN in this process. By analyzing the imaging data of 100 participants performing two attention-demanding tasks, we found that the PCu is functionally divided into dorsal and ventral subdivisions. We then conducted a comprehensive examination of their connectivity profiles and found that at rest, both the ventral PCu (vPCu) and dorsal PCu (dPCu) are mainly connected with the DMN but also are differentially connected with internally oriented networks (IoN) and externally oriented networks (EoN). During tasks, the double associations between the v/dPCu and the IoN/EoN are correlated with task performance and can switch depending on cognitive demand. Furthermore, dynamic causal modeling (DCM) revealed that the strength and direction of the effective connectivity (EC) between v/dPCu is modulated by task difficulty in a manner potentially dictated by the balance of internal versus external cognitive demands. Our study provides evidence that the posterior medial part of the DMN may drive interactions between large-scale networks, potentially allowing access to stored representations for moment-to-moment interpretation of an ever-changing environment. SIGNIFICANCE STATEMENT The default-mode network (DMN) is widely known for its association with internalized thinking processes, e.g., spontaneous thoughts, which is the most interesting but least understood component in human consciousness. The precuneus (PCu), a posteromedial DMN hub, is thought to play a role in this, but a mechanistic explanation has not yet been established. In this study we found that the associations between ventral PCu (vPCu)/dorsal PCu (dPCu) subdivisions and internally oriented network (IoN)/externally oriented network (EoN) are flexibly modulated by cognitive demand and correlate with task performance. We further propose that the recurrent causal connectivity between the ventral and dorsal PCu supports conscious processing by constantly interpreting external information based on an internal model, meanwhile updating the internal model with the incoming information., (Copyright © 2021 the authors.)