The present invention relates to a Raman-enhanced substrate fixing device and a Raman-enhanced detecting system. the Raman-enhanced substrate fixing device comprises a fixing base, wherein the fixing base is provided with a substrate receiving portion and a probe connecting portion, the substrate receiving portion is used for receiving a Raman-enhanced substrate, the probe connecting portion is used for connection with a probe of a Raman spectrometer, and the probe connecting portion and the substrate receiving portion are disposed such that light emitted by the probe is capable of being irradiated onto the Raman-enhanced substrate.

Systems for protein quantitation using a Fabry-Perot interferometer. In one arrangement, a quantitation device includes an infrared source, a sample holder, and a Fabry-Perot interferometer positioned to receive infrared radiation from the source passing through a sample on the sample holder. A band pass optical filter sets the working range of the interferometer, and radiation exiting the interferometer falls on a detector that produces a signal indicating the intensity of the received radiation. A controller causes the interferometer to be tuned to a number of different resonance wavelengths and receives the intensity signals, for determination of an absorbance spectrum.

Systems, devices, and methods for combined wafer and photomask inspection are provided. In some embodiments, chucks are provided, the chucks comprising: a removable insert, wherein the removable insert is configured to support a wafer so that an examination surface of the wafer lies within a focal range when the chuck is in a first configuration, wherein the removable insert is inserted into the chuck in the first configuration; and a first structure forming a recess that has a depth sufficient to support a photomask so that an examination surface of the photomask lies within the focal range when the chuck is in a second configuration, wherein the removable insert is not inserted into the chuck in the second configuration.

A Laser Induced Breakdown Spectrocopy (LIBS) system (2) for the analysis of a sample pellet (12) of a consolidated granular material retained in a tubular container (20), the system (2) comprising a laser source (4) configured to emit a pulsed laser beam (6) towards an exposed surface of the sample pellet (12); and a sample station (18) configured to hold the tubular container (20) with the sample pellet (12) orientated to present the exposed surface towards the pulsed laser beam and comprising an actuator configured to slide the sample pellet (12) along a movement axis out of the tubular container (20) and thereby present a portion of an outer surface (10) of the sample pellet (12) previously constrained by an inner surface of the tubular container (20) as the exposed surface.

An arrangement for the spectrometric measurement of products, such as cereals, oleaginous products, or derived products, includes a mechanism for selective adjustment of the position of a light beam in vertical and horizontal planes, and a selective adjustment device for ensuring that rays of the light beam are parallel.

A sample detection plate according to the present disclosure includes a first substrate having a first surface, and a sample container that is provided on the first surface of the first substrate to contain a sample that absorbs electromagnetic waves having a predetermined wavelength. The first substrate includes a first material that emits autofluorescence in response to the electromagnetic waves having the predetermined wavelength.

A system for identifying a biological sample in a sample holder. The system comprising a light source for emitting substantially monochrome light directed at the sample holder; a light sensor for detecting the amount of light reflected or transmitted by the biological sample and 5 configured to output measurements indicative of the amount of light detected; and a controller connected to the light sensor and configured to identify the biological sample based on the output measurements of the light sensor.

An object is to develop a measurement method, and a measurement substrate, for measuring SPF or other value in a single measurement, instead of having to measure it on many substrates as has been the case to date. As a solution, a substrate for UV transmittance evaluation, including a base material that allows UV rays in a range of 290 to 400 nm to transmit through, and a layer provided on one side thereof that contains at least one type of compound other than cellulose triacetate that has a sugar skeleton but is not a salt, is provided.

A system for performing grazing angle measurements is disclosed herein. The system includes a laser configured to emit a beam of light and a series of reflective elements configured to direct the beam of light and a hollow sphere is rotatable about a sphere axis with the sphere axis extending through a central region of the hollow sphere. The hollow sphere defines an elongated slot for accepting the beam of light when the hollow sphere is in one of a plurality of predetermined rotational positions about the sphere axis. A mounting arm extends into a central region of the hollow sphere and includes a sample mount configured to receive a sample. The system further includes a spectral hemispherical reflectance detector having a field of view extending into the hollow sphere and a baffle horizontally interposed relative to the sphere axis between the spectral hemispherical reflectance detector and the elongated slot.

The apparatus (100A) comprises a cover plate (102) for focusing a terahertz beam (108) and a bottom plate (104) for enhancing an absorption signal of a sample (106) to the terahertz beam (108). The apparatus (100A) comprises a terahertz time-domain spectroscopy module (110) for acquiring (802) terahertz time-domain spectroscopy (THz TDS) data. The apparatus (100A) comprises a processor (120) configured to implement a trained machine learning model (130) that is trained on training dataset (114) comprising a pure compound dataset (114a) and a mixture dataset (114b). The trained machine learning model (130) is configured to process (804) an acquired THz TDS data (116) for obtaining a reduced dimensionality dataset (118); extract (806) at least one feature (118a) from the reduced dimensionality dataset (118); generate (808) a classification label (122) for the reduced dimensionality dataset (118); and indicate (810) a probability of identifying the chemical compound (112).