Method of contactless measurement of the conductivity of semiconductors, said method being implemented by: a first assembly comprising a signal emission/reception system a second assembly comprising at least one semi-conducting target and an inductor element, a third assembly, said method comprising at least the following steps: a) the first assembly emits a multifrequency signal, b) the second assembly reflects or transmits at least one part of the multifrequency signal emitted, c) the first assembly receives the reflected multifrequency signal reflected by the second assembly, d) the third assembly calculates the coefficient of reflection or of transmission of the emitted signal, e) the third assembly provides the conductivity of the semiconducting target.

A semiconductor device testing system, with a platform for supporting a semiconductor substrate, a light emitting system directed toward the platform, a controller, coupled to the light emitting system and adapted to selectively alter an operational parameter of the light emitting system, and a tester configured to characterize an electrical parameter of an electrical device formed in or over the semiconductor substrate while the electrical device is illuminated by one or more wavelengths of light emitted by the light emitting system under direction of the controller.

Described herein are a system and method of preparing integrated circuits (ICs) so that the ICs remain electrically active and can have their active circuitry probed for diagnostic and characterization purposes using charged particle beams. The system employs an infrared camera capable of looking through the silicon substrate of the ICs to image electrical circuits therein, a focused ion beam system that can both image the IC and selectively remove substrate material from the IC, a scanning electron microscope that can both image structures on the IC and measure voltage contrast signals from active circuits on the IC, and a means of extracting heat generated by the active IC. The method uses the system to identify the region of the IC to be probed, and to selectively remove all substrate material over the region to be probed using ion bombardment, and further identifies endpoint detection means of milling to the required depth so as to observe electrical states and waveforms on the active IC.

Disclosed are a system and method, wherein, during manufacturing of integrated circuit chips on a semiconductor wafer, an in-line optical inspection is performed to acquire a two-dimensional (2D) image of an area of the semiconductor wafer and to confirm and classify a defect in the area. The 2D image is then converted into a virtual three-dimensional (3D) image. To ensure that the 3D image is accurate, techniques are employed to determine the topography of the surface shown in the 2D image based on material-specific image intensity information and, optionally, to filter out any edge effects that result in anomalies within the 3D image. The resulting 3D image is usable for performing an in-line failure analysis to determine a root cause of a defect. Such an in-line failure analysis can be performed significantly faster than any off-line failure analysis and, thus, allows for essentially real-time advanced process control (APC).

A light source device includes a light source that generates incoherent light, and an optical amplifier having gain characteristics indicating a gain at each wavelength, which receives the incoherent light output by the light source as input light, and outputs amplified light obtained by amplifying the input light, and a central wavelength of an intensity distribution indicating an intensity at each wavelength of the input light is a wavelength longer than a central wavelength of the gain characteristics indicating a gain at each wavelength of the optical amplifier.

A semiconductor device inspection apparatus is an apparatus for inspecting a semiconductor device which is an object to be inspected based on a result signal which is output in accordance with input of a test pattern signal to the semiconductor device, the apparatus including: an ultrasonic transducer, disposed to face the semiconductor device, which generates ultrasonic waves; a stage for moving a relative position of the semiconductor device and the ultrasonic transducer; a stimulation condition control unit for controlling a condition of stimulation by the ultrasonic waves applied to the semiconductor device; and an analysis unit for generating a measurement image based on the result signal which is output from the semiconductor device.

A semiconductor device inspection apparatus is an apparatus for inspecting a semiconductor device which is an object to be inspected based on a result signal which is output in accordance with input of a test pattern signal to the semiconductor device, the apparatus including: an ultrasonic transducer, disposed to face the semiconductor device, which generates ultrasonic waves; a stage for moving a relative position of the semiconductor device and the ultrasonic transducer; a stimulation condition control unit for controlling a condition of stimulation by the ultrasonic waves applied to the semiconductor device; and an analysis unit for generating a measurement image based on the result signal which is output from the semiconductor device.

Neutron soft error rate derivation is calculated from data at the low energy neutron radiation. An outline value of an SEU cross-section function corresponding to a given neutron energy value is outputted. This outline value and the low energy neutron spectrum data are used to calculate an error count basic value of errors to occur over time. An error count actual measurement value over time is calculated from an error count during radiation of low energy neutrons and low energy neutron radiation time. The error count basic value and the error count actual measurement are used to calculate a proportionality coefficient of the SEU cross-section function. While holding a natural neutron spectrum, an error rate calculator outputs a neutron flux corresponding to a neutron energy value. The neutron soft error rate is calculated by an integration operation of multiplying the SEU cross-section function with the natural neuron spectrum.

Neutron soft error rate derivation is calculated from data at the low energy neutron radiation. An outline value of an SEU cross-section function corresponding to a given neutron energy value is outputted. This outline value and the low energy neutron spectrum data are used to calculate an error count basic value of errors to occur over time. An error count actual measurement value over time is calculated from an error count during radiation of low energy neutrons and low energy neutron radiation time. The error count basic value and the error count actual measurement are used to calculate a proportionality coefficient of the SEU cross-section function. While holding a natural neutron spectrum, an error rate calculator outputs a neutron flux corresponding to a neutron energy value. The neutron soft error rate is calculated by an integration operation of multiplying the SEU cross-section function with the natural neuron spectrum.

A heat source position inside a measurement object is identified with high accuracy by improving time resolution.

An analysis system according to the present invention is an analysis system that identifies a heat source position inside a measurement object, and includes a condition setting unit that sets a measurement point for one surface of the measurement object, a tester that applies a stimulation signal to the measurement object, a light source that irradiates the measurement point of the measurement object with light, a photo detector that detects light reflected from a predetermined measurement point on the surface of the measurement object according to the irradiation of light and outputs a detection signal, and an analysis unit that derives a distance from the measurement point to the heat source position based on the detection signal and the stimulation signal and identifies the heat source position.