Abstract: Semiconductor structures and method for forming the same are provided. The semiconductor structure includes a substrate and a first channel layer and a second channel layer. The semiconductor structure further includes an isolation structure over the substrate and a first gate structure over the first channel layer and the isolation structure. The semiconductor structure further includes a second gate structure over the second channel layer and the isolation structure and an isolation feature laterally sandwiched between the first gate structure and the second gate structure and extending over the isolation structure. In addition, the isolation feature has a top width and a bottom width that is greater than the top width, and an interface between the isolation feature and the first gate structure includes a curved profile.

Abstract: Semiconductor structures and methods for manufacturing the same are provided. The semiconductor structure includes a plurality of first nanostructures formed over a substrate along a first direction, and a plurality of second nanostructures formed adjacent to the first nanostructures. The semiconductor structure includes a first gate structure formed on the first nanostructures along a second direction, and the first gate structure includes a first gate dielectric layer. The semiconductor structure includes a second gate structure formed on the second nanostructures. The semiconductor structure includes a dielectric wall structure between the first gate structure and the second gate structure along the first direction. The dielectric wall structure has a top portion and a bottom portion, and the bottom portion is wider than the top portion.

Abstract: The present invention focuses on advancing perovskite solar cells (PSCs) by improving the management of ionic defects within the perovskite photoactive layer during both fabrication and operation. Traditional perovskite passivators tend to remain fixed on the surface after deposition, but perovskites are sensitive to environmental conditions that can alter their structure and create new defects. As a result, conventional passivators are often ineffective in addressing these changes. This innovation incorporates thiocarbamate bonds into the passivating molecules, allowing them to dissociate under high temperatures and release additional passivators to passivate newly formed defects.

Abstract: A circuit. The circuit includes a transformer having a primary winding magnetically coupled to a secondary winding, the primary winding including a first terminal connected to an input voltage and a second terminal coupled to a ground via a primary switch, where the secondary winding includes a third terminal connected to an output terminal, and further includes a fourth terminal connected to a secondary switch, where the secondary switch includes a gate terminal, a source terminal and a drain terminal, and a comparator having a first input connected to a predetermined voltage, a second input connected to the drain terminal, and an output coupled to a half-bridge circuit. In one aspect, the comparator and the half-bridge circuit are arranged to receive a voltage signal from the drain terminal and generate a corresponding gate voltage signal at the gate terminal to control a conductivity state of the secondary switch.

Abstract: A method for manufacturing a semiconductor structure is provided.

Abstract: A method includes: receiving N sets of weights of a convolutional layer of a neural network, each set of the weights having a same number of weights and corresponding to one of a sequence of output channels (OCs) of the convolutional layer; and performing a pruning process to prune M sets of the weights among the N sets of the weights such that each of the M sets of the weights has a same number of non-zero weights, M being smaller than or equal to N, M being equal to a number of active OCs to be processed in parallel in a neural network processor.

Abstract: A method for manufacturing a semiconductor structure is provided. The method includes forming a fin structure protruding from a substrate, wherein the fin structure includes first semiconductor material layers and second semiconductor material layers alternately stacked. The method includes forming a dummy gate structure across the fin structure. The method includes forming a gate spacer on the sidewall of the dummy gate structure. The method includes removing the dummy gate structure to expose the fin structure. The method includes partially removing the second semiconductor material layers to form concave portions on sidewalls of the second semiconductor material layers. The method includes forming dielectric spacers in the concave portions. The method includes removing the first semiconductor material layers to form gaps. The method includes forming a gate structure in the gaps to wrap around the second semiconductor material layers and the dielectric spacers.

Abstract: A method for manufacturing a semiconductor structure is provided. The method includes forming a fin structure protruding from a substrate, wherein the fin structure includes first semiconductor material layers and second semiconductor material layers alternately stacked. The method includes forming a dummy gate structure across the fin structure. The method includes forming a gate spacer on the sidewall of the dummy gate structure. The method includes removing the dummy gate structure to expose the fin structure. The method includes partially removing the second semiconductor material layers to form concave portions on sidewalls of the second semiconductor material layers. The method includes forming dielectric spacers in the concave portions. The method includes removing the first semiconductor material layers to form gaps. The method includes forming a gate structure in the gaps to wrap around the second semiconductor material layers and the dielectric spacers.

Abstract: The disclosure provides a disease classification method and a disease classification device. The disease classification method includes: inputting samples into a first stage model and obtaining a first stage determination result; inputting first samples determined positive by the first stage model into a second stage high specificity model to obtain second samples determined to be positive and third samples determined to be negative and rule in the second samples; inputting fourth samples determined negative by the first stage model into a second stage high sensitivity model to obtain fifth samples determined to be positive and sixth samples determined to be negative and rule out the sixth samples; obtaining a second stage determination result of the second and sixth samples; and inputting the third and fifth samples not ruled in or ruled out into a third stage model and obtaining a third stage determination result of the third and fifth samples.

Abstract: The present application provides a control device, a power-supply device, and a method for controlling a power-supply device. The control device, applied to a power converter, includes a primary controller, a secondary controller and a voltage detector, wherein the power converter includes a transformer having a primary winding and a secondary winding. The primary controller is configured to generate a PWM signal having an off-time and an on-time, wherein the power converter is operative to deliver power from the primary winding to the secondary winding during the on-time. The secondary controller monitors an output voltage of the power converter and applies a preset voltage to the secondary winding according to a threshold voltage and the output voltage. The voltage detector, coupled to the primary winding, drives the primary controller to adjust a period of the PWM signal in response to the application of the preset voltage.

Abstract: A method of balancing workloads among processing elements (PEs) in a neural network processor can include receiving first weights and second weights of a neural network. The first and second weights are associated with a first and a second output channel (OC), respectively. A first PE computes a partial sum (PSUM) of an output activation of the first OC based on the non-zero weights in the first weights. A second PE computes a PSUM of an output activation of the second OC based on the non-zero weights in the second weights. A controller can allocate one or more non-zero weights of the first weights to the second PE for computing the PSUM of the output activation of the first OC to balance a workload.

Abstract: A nano-twinned crystal film and a method thereof are disclosed. The method of fabricating a nano-twinned crystal film includes utilizing an electrolyte solution including copper salt, acid, and a water or alcohol-soluble organic additive, and performing electrodeposition, under conditions of a current density of 20˜100 mA/cm2, a voltage of 0.2˜1.0V, and a cathode-anode distance of 10˜300 mm, to form the nano-twinned crystal film on a surface at the cathode. The nano-twinned crystal film formed by the method includes a plurality of nano-twinned copper grains and a region of random crystal phases between some of adjacent nano-twinned copper grains, wherein at least some of the nano-twinned copper grains have a pillar cap configuration with a wide top and a narrow bottom.

Abstract: A physiological status evaluation method and a physiological status evaluation apparatus are provided. The method includes the following: obtaining original electrocardiogram data of a user by an electrocardiogram detection apparatus; converting the original electrocardiogram data into digital integration data; obtaining a plurality of physiological characteristic parameters according to the digital integration data; filtering the physiological characteristic parameters for at least one notable characteristic parameter through at least one filter model, where decision importance of the at least one notable characteristic parameter in a decision process of the at least one filter model is greater than a threshold; building a prediction model according to the at least one notable characteristic parameter; and evaluating a physiological status of the user through the prediction model.

Abstract: A physiological status evaluation method and a physiological status evaluation apparatus are provided. The method includes the following: obtaining original electrocardiogram data of a user by an electrocardiogram detection apparatus; converting the original electrocardiogram data into digital integration data; obtaining a plurality of physiological characteristic parameters according to the digital integration data; filtering the physiological characteristic parameters for at least one notable characteristic parameter through at least one filter model, where decision importance of the at least one notable characteristic parameter in a decision process of the at least one filter model is greater than a threshold; building a prediction model according to the at least one notable characteristic parameter; and evaluating a physiological status of the user through the prediction model.

Abstract: The disclosure provides a disease classification method and a disease classification device. The disease classification method includes: inputting samples into a first stage model and obtaining a first stage determination result; inputting first samples determined positive by the first stage model into a second stage high specificity model to obtain second samples determined to be positive and third samples determined to be negative and rule in the second samples; inputting fourth samples determined negative by the first stage model into a second stage high sensitivity model to obtain fifth samples determined to be positive and sixth samples determined to be negative and rule out the sixth samples; obtaining a second stage determination result of the second and sixth samples; and inputting the third and fifth samples not ruled in or ruled out into a third stage model and obtaining a third stage determination result of the third and fifth samples.

Abstract: A nano-twinned crystal film and a method thereof are disclosed. The method of fabricating a nano-twinned crystal film includes utilizing an electrolyte solution including copper salt, acid, and a water or alcohol-soluble organic additive, and performing electrodeposition, under conditions of a current density of 20˜100 mA/cm2, a voltage of 0.2˜1.0V, and a cathode-anode distance of 10˜300 mm, to form the nano-twinned crystal film on a surface at the cathode. The nano-twinned crystal film formed by the method includes a plurality of nano-twinned copper grains and a region of random crystal phases between some of adjacent nano-twinned copper grains, wherein at least some of the nano-twinned copper grains have a pillar cap configuration with a wide top and a narrow bottom.

Abstract: The surface temperature of a portable device is estimated. The portable device includes a sensor for detecting the internal temperature of the portable device. The portable device also includes circuitry for estimating the surface temperature, using the internal temperature and an ambient temperature of the portable device as input to a circuit model. The circuit model describes thermal behaviors of the portable device. The circuitry is operative to identify a scenario in which the portable device operates, and determine the ambient temperature using the scenario and at least the internal temperature.

Abstract: The surface temperature of a portable device is estimated. The portable device includes a sensor for detecting the internal temperature of the portable device. The portable device also includes circuitry for estimating the surface temperature, using the internal temperature and an ambient temperature of the portable device as input to a circuit model. The circuit model describes thermal behaviors of the portable device. The circuitry is operative to identify a scenario in which the portable device operates, and determine the ambient temperature using the scenario and at least the internal temperature.

Abstract: The surface temperature of a portable device is estimated. A sensor detects the internal temperature of the portable device. The internal temperature and an ambient temperature are used as input to a circuit model that describes thermal behaviors of the portable device. Dynamic thermal management may be performed based on the estimated surface temperature.

Abstract: A deep learning accelerator (DLA) includes processing elements (PEs) grouped into PE groups to perform convolutional neural network (CNN) computations, by applying multi-dimensional weights on an input activation to produce an output activation. The DLA also includes a dispatcher which dispatches input data in the input activation and non-zero weights in the multi-dimensional weights to the processing elements according to a control mask. The DLA also includes a buffer memory which stores the control mask which specifies positions of zero weights in the multi-dimensional weights. The PE groups generate output data of respective output channels in the output activation, and share a same control mask specifying same positions of the zero weights.