a b s t r a c tGlass fiber-reinforced composite laminates in polyetherimide resin have been studied via terahertz imaging and ultrasonic C-scans. The forced delamination is created by inserting Teflon film between various layers inside the samples prior to consolidating the laminates. Using reflective pulsed terahertz imaging, we find high-resolution, low-artifact terahertz C-scan and B-scan images locating and sizing the delamination in three dimensions. Furthermore, terahertz imaging enables us to determine the thicknesses of the delamination and of the layers constituting the laminate. Ultrasonic C-scan images are also successfully obtained; however, in our samples with small thickness-to-wavelength ratio, detailed ultrasonic B-scan images providing quantitative information in depth cannot be obtained by 5 MHz or 10 MHz focused transducers. Comparative analysis between terahertz imaging and ultrasonic C-scans with regard to spatial resolution is carried out demonstrating that terahertz imaging provides higher spatial resolution for imaging, and can be regarded as an alternative or complementary modality to ultrasonic C-scans for this class of glass fiber-reinforced composites.

Terahertz frequency-wavelet deconvolution is utilized specifically for the stratigraphic and subsurface investigation of art paintings with terahertz reflective imaging. In order to resolve the optically thin paint layers, a deconvolution technique is enhanced by the combination of frequency-domain filtering and stationary wavelet shrinkage, and applied to investigate a mid-20th century Italian oil painting on paperboard, After Fishing, by Ausonio Tanda. Based on the deconvolved terahertz data, the stratigraphy of the painting including the paint layers is reconstructed and subsurface features are clearly revealed, demonstrating that terahertz frequency-wavelet deconvolution can be an effective tool to characterize stratified systems with optically thin layers.

The process by which art paintings are produced typically involves the successive applications of preparatory and paint layers to a canvas or other support; however, there is an absence of nondestructive modalities to provide a global mapping of the stratigraphy, information that is crucial for evaluation of its authenticity and attribution, for insights into historical or artist-specific techniques, as well as for conservation. We demonstrate sparsity-based terahertz reflectometry can be applied to extract a detailed 3D mapping of the layer structure of the 17th century easel painting Madonna in Preghiera by the workshop of Giovanni Battista Salvi da Sassoferrato, in which the structure of the canvas support, the ground, imprimatura, underpainting, pictorial, and varnish layers are identified quantitatively. In addition, a hitherto unidentified restoration of the varnish has been found. Our approach unlocks the full promise of terahertz reflectometry to provide a global and detailed account of an easel painting’s stratigraphy by exploiting the sparse deconvolution, without which terahertz reflectometry in the past has only provided a meager tool for the characterization of paintings with paint-layer thicknesses smaller than 50 μm. The proposed modality can also be employed across a broad range of applications in nondestructive testing and biomedical imaging.

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Terahertz imaging is applied to characterize a hybrid fiber-reinforced composite laminate subject to low-velocity impact in this study. The hybrid fiberreinforced composite laminate comprises unidirectional glass/epoxy and carbon/epoxy plies with a cross-ply stack pattern. Both impact-induced intraand inter-laminar damages are successfully detected, and the damage evolution throughout the thickness is also evaluated. The interaction between the terahertz polarization and carbon-fiber orientation is investigated in detail.Inter-laminar damage at the interface and the intra-laminar damage close to the same interface can be differentiated via polarization-resolved imaging.With a parameter fitting method based on multiple regression analysis, delamination is characterized quantitatively. Terahertz C-and B-scan images

Terahertz(THz) reflection imaging is applied to characterize a woven glass fiber-reinforced composite laminate with a small region of forced delamination. The forced delamination is created by inserting a disk of 25 µm thick Upilex film, which is below the THz axial resolution, resulting in one featured echo with small amplitude in the reflected THz pulses. Low-amplitude components of the temporal signal due to ambient water vapor produce features of comparable amplitude with features associated with the THz pulse reflected off the interfaces of the delamination, and suppress the contrast of THz C-and B-scans. Wavelet shrinkage de-noising is performed to remove water-vapor features, leading to enhanced THz C-and B-scans to locate the delamination in three dimensions with high contrast.

Polarization-sensitive terahertz imaging is applied to characterize subsurface damage in woven carbon fiberreinforced composite laminates in this study. Terahertz subsurface spectral imaging based on terahertz deconvolution is tailored and applied to detect, in a nondestructive fashion, the subsurface damage within the first ply of the laminate caused by a four-point bending test. Subsurface damage types, including matrix cracking, fiber distortion/fracture, as well as intra-ply delamination, are successfully characterized. Our results show that, although the conductivity of carbon fibers rapidly attenuates terahertz propagation with depth, the imaging capability of terahertz radiation on woven carbon fiber-reinforced composites can nonetheless be significantly enhanced by taking advantage of the terahertz polarization and terahertz deconvolution. The method demonstrated in this study is capable of extracting and visualizing a number of fine details of the subsurface damage in woven carbon fiber-reinforced composites, and the results achieved are confirmed by comparative studies with X-ray tomography.

This Letter presents a method for enhancing the depth resolution of terahertz deconvolution based on autoregressive (AR) spectral extrapolation. The terahertz frequency components with a high signal-to-noise ratio (SNR) are modeled with an AR process, and the missing frequency components in the regions with low SNRs are extrapolated based on the AR model. In this way, the entire terahertz frequency spectrum of the impulse response function, corresponding to the material structure, is recovered. This method, which is verified numerically and experimentally, is able to provide a "quasi-ideal" impulse response function and, therefore, greatly enhances the depth resolution for characterizing optically thin layers in the terahertz regime.