Fast and quantitative 2D and 3D orientation mapping using Raman microscopy

Dehydration regulates structural reorganization of dynamic hydrogels

The dehydration process is widely recognized as a significant phenomenon in nature. Hydrogels, which are important functional materials with high water content and crosslinked networks, encounter the issue of dehydration in their practical applications. Here, we report the distinctive anisotropic dehydration modality of dynamic hydrogels, which is fundamentally different from the more commonly observed isotropic dehydration of covalent hydrogels. Xerogels derived from dynamic hydrogel dehydration will fully cover a curved substrate surface and exhibit hollow structures with internal knots, in contrast to the bulk xerogels produced by covalent hydrogel dehydration. Depending on the competing cohesion of polymer chains and the adhesion at the hydrogel-substrate interface, the previously overlooked reorganization of polymer networks within dynamic hydrogels, triggered by dehydration-induced stress, has been discovered to regulate such macroscopic structural reconstruction for dynamic hydrogel dehydration. With the attached hydrogel-substrate interface, the surface microstructures of substrates can also be engraved onto xerogels with high resolution and on a large scale. This work will greatly enhance our understanding of the soft matter dehydration process and broaden the applications of dehydration technologies using water-containing materials.

Stacking textured films on lattice-mismatched transparent conducting oxides via matched Voronoi cell of oxygen sublattice

Transparent conducting oxides are a critical component in modern (opto)electronic devices and solar energy conversion systems, and forming textured functional films on them is highly desirable for property manipulation and performance optimization. However, technologically important materials show varied crystal structures, making it difficult to establish coherent interfaces and consequently the oriented growth of these materials on transparent conducting oxides. Here, taking lattice-mismatched hexagonal α-Fe2O3 and tetragonal fluorine-doped tin oxide as the example, atomic-level investigations reveal that a coherent ordered structure forms at their interface, and via an oxygen-mediated dimensional and chemical-matching manner, that is, matched Voronoi cells of oxygen sublattices, [110]-oriented α-Fe2O3 films develop on fluorine-doped tin oxide. Further measurements of charge transport characteristics and photoelectronic effects highlight the importance and advantages of coherent interfaces and well-defined orientation in textured α-Fe2O3 films. Textured growth of lattice-mismatched oxides, including spinel Co3O4, fluorite CeO2, perovskite BiFeO3 and even halide perovskite Cs2AgBiBr6, on fluorine-doped tin oxide is also achieved, offering new opportunities to develop high-performance transparent-conducting-oxide-supported devices.

Impact of Raman mapping area and intra-tablet homogeneity on the accuracy of sustained-release tablet dissolution prediction

This exploratory study investigated the minimum required Raman mapping area for predicting sustained-release tablet dissolution profiles based on intra-tablet homogeneity. The aim was to minimize scanning time while achieving reliable dissolution profile predictions. To construct the sample set, we controlled the blending time to introduce variability in the homogeneity of the tablets. The dissolution prediction models were established using the partial least squares regression under different Raman mapping area. The accuracies of the prediction results were evaluated according to the difference factor f1 and Intersection-Union two one-sided t-tests (IU TOST) methods, and the implications conveyed by the results were discussed. The results showed that the homogeneity of sustained-release tablet affects the minimum required mapping area, and the tablets with higher homogeneity show higher prediction accuracy when using the same mapping area to model the dissolution profiles of tablets.

3D Orientation Imaging of Polymer Chains with Polarization-Controlled Coherent Raman Microscopy

Despite the ubiquity of three-dimensional (3D) anisotropic materials, their 3D molecular alignment cannot be measured using conventional two-dimensional (2D) polarization imaging. Here, we present images of the 3D angles of molecular orientations with submicrometer spatial resolution acquired through polarization-controlled coherent anti-Stokes Raman scattering microscopy. The hyperspectral Raman data of a polyethylene (PE) film were converted into images, showing the polymer chains' 3D angles and order parameters. The 3D orientation images of PE chains in ring-banded spherulites show that the azimuthal angles of the chains are perpendicular to the crystal growth direction, while the out-of-plane angles display limited-range oscillations synchronous with ring banding. The prevailing crystal growth model of fully twisting lamellae is inconsistent with the observed restricted oscillations of the out-of-plane direction, which are unobservable through conventional 2D projected imaging. This high-resolution, label-free, quantitative imaging of 3D molecular orientation can become a standard measurement tool for the microscopic structures of complex synthetic and biological materials.

Confocal Raman microscope with versatile dual polarization snapshot acquisition

In this paper we propose a new strategy towards simultaneous co- and cross-polarized measurements of Raman spectra in a confocal microscope. One of the advantages of this strategy is that it is immune to polarization-dependent efficiency of diffraction gratings. It is shown via linear angle-resolved and circular polarization measurements that the accuracy of these snapshot polarization measurements on solid and liquid samples are in good agreement with available models and data. The interest of simultaneous acquisition of the total Raman response and the degree of polarization is discussed as well.

Quantitative multi-image analysis in metals research

Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure-property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1557/s43579-022-00265-7.

Raman mapping-based non-destructive dissolution prediction of sustained-release tablets

In this paper, the applicability of Raman chemical imaging for the non-destructive prediction of the in vitro dissolution profile of sustained-release tablets is demonstrated for the first time. Raman chemical maps contain a plethora of information about the spatial distribution and the particle size of the components, compression force and even polymorphism. With proper data analysis techniques, this can be converted into simple numerical information which can be used as input in a machine learning model. In our work, sustained-release tablets using hydroxypropyl methylcellulose (HPMC) as matrix polymer are prepared, the concentration and particle size of this component varied between samples. Chemical maps of HPMC are converted into histograms with two different methods, an approach based on discretizing concentration values and a wavelet analysis technique. These histograms are then subjected to Principal Component Analysis, the score value of the first two principal components was found to represent HPMC content and particle size. These values are used as input in Artificial Neural Networks which are trained to predict the dissolution profile of the tablets. As a result, accurate predictions were obtained for the test tablets (the average f₂ similarity value is higher than 59 with both methods). The presented methodology lays the foundations of the analysis of far more extensive datasets acquired with the emerging fast Raman imaging technology.

Automated Hyperspectral 2D/3D Raman Analysis Using the Learner-Predictor Strategy: Machine Learning-Based Inline Raman Data Analytics

Synchronously detecting multiple Raman spectral signatures in two-dimensional/three-dimensional (2D/3D) hyperspectral Raman analysis is a daunting challenge. The underlying reasons notwithstanding the enormous volume of the data and also the complexities involved in the end-to-end Raman analytics pipeline: baseline removal, cosmic noise elimination, and extraction of trusted spectral signatures and abundance maps. Elimination of cosmic noise is the bottleneck in the entire Raman analytics pipeline. Unless this issue is addressed, the realization of autonomous Raman analytics is impractical. Here, we present a learner-predictor strategy-based "automated hyperspectral Raman analysis framework" to rapidly fingerprint the molecular variations in the hyperspectral 2D/3D Raman dataset. We introduce the spectrum angle mapper (SAM) technique to eradicate the cosmic noise from the hyperspectral Raman dataset. The learner-predictor strategy eludes the necessity of human inference, and analytics can be done in autonomous mode. The learner owns the ability to learn; it automatically eliminates the baseline and cosmic noise from the Raman dataset, extracts the predominant spectral signatures, and renders the respective abundance maps. In a nutshell, the learner precisely learned the spectral features space during the hyperspectral Raman analysis. Afterward, the learned spectral features space was translated into a neural network (LNN) model. In the predictor, machine-learned intelligence (LNN) is utilized to predict the alternate batch specimen's abundance maps in real time. The qualitative/quantitative evaluation of abundance maps implicitly lays the foundation for monitoring the offline/inline industrial qualitative/quantitative quality control (QA/QC) process. The present strategy is best suited for 2D/3D/four-dimensional (4D) hyperspectral Raman spectroscopic techniques. The proposed ML framework is intuitive because it obviates human intelligence, sophisticated computational hardware, and solely a personal computer is enough for the end-to-end pipeline.

Collagen orientation probed by polarized Raman spectra can serve as differential diagnosis indicator between different grades of meniscus degeneration

The purpose of the present study was to analyze normal and degenerated menisci with Raman methodology on thin sections of formalin fixed paraffin embedding tissues and to correlate the Raman findings with the grade of meniscus degeneration. Menisci (n = 27) were removed from human knee joints after total knee replacement or meniscectomy. Following routine histopathological analysis to determine the grade of meniscal lesions obtained from healthy and degenerated formaline fixed paraffin embedded (FFPE) meniscal sections, Raman polarization approach was applied to evaluate the orientation of collagen fibrils in different levels of the same 5 μm thick FFPE meniscal tissue sections, used for histopathological assessment. We collected Raman spectra in two different polarization geometries, v-HH and v-VV, and calculated the mean value of the v-HH/v-VV intensity ratio of two Raman bands, sensitive and non-sensitive to the molecular orientation. The collagen specific amide I band at 1665 cm^-1, has the higher sensitivity dependence on the Raman polarization. The mean values of ratio v-HH/v-VV of the 1665 cm^-1 peak intensity was significantly higher in healthy, mean ± SD: 2.56 ± 0.46, compared to degenerated menisci, mean ± SD: 1.85 ± 0.42 (p = 0.0014). The mean values of v-HH/v-VV intensity ratio were 2.18 and 1.50 for low and high degenerated menisci, respectively (p < 0.0001). The difference of peak intensities in the two laser polarizations is decreased in the degenerated meniscus; this difference is diminishing as the degeneration increases. The v-HH/v-VV ratio was also of significant difference in low as compared to control and high grade meniscus lesions (p = 0.036 and p < 0.0001, respectively) offering valuable information for the approach of its biology and function. In the present study we showed that the 5 μm thick sections can be used for Raman analysis of meniscal tissue with great reliability, in terms of sensitivity, specificity, false-negative and false-positive results. Our data introduce the interesting hypothesis that compact portable Raman microscopy on tissue sections can be used intra-operatively for fast diagnosis and hence, accurate procedure design in the operating room.

Understanding angle-resolved polarized Raman scattering from black phosphorus at normal and oblique laser incidences

The selection rule for angle-resolved polarized Raman (ARPR) intensity of phonons from standard group-theoretical method in isotropic materials would break down in anisotropic layered materials (ALMs) due to birefringence and linear dichroism effects. The two effects result in depth-dependent polarization and intensity of incident laser and scattered signal inside ALMs and thus make a challenge to predict ARPR intensity at any laser incidence direction. Herein, taking in-plane anisotropic black phosphorus as a prototype, we developed a so-called birefringence-linear-dichroism (BLD) model to quantitatively understand its ARPR intensity at both normal and oblique laser incidences by the same set of real Raman tensors for certain laser excitation. No fitting parameter is needed, once the birefringence and linear dichroism effects are considered with the complex refractive indexes. An approach was proposed to experimentally determine real Raman tensor and complex refractive indexes, respectively, from the relative Raman intensity along its principle axes and incident-angle resolved reflectivity by Fresnel's law. The results suggest that the previously reported ARPR intensity of ultrathin ALM flakes deposited on a multilayered substrate at normal laser incidence can be also understood based on the BLD model by considering the depth-dependent polarization and intensity of incident laser and scattered Raman signal induced by both birefringence and linear dichroism effects within ALM flakes and the interference effects in the multilayered structures, which are dependent on the excitation wavelength, thickness of ALM flakes and dielectric layers of the substrate. This work can be generally applicable to any opaque anisotropic crystals, offering a promising route to predict and manipulate the polarized behaviors of related phonons.

Characterization of thymine microcrystals by CARS and SHG microscopy

Identification of chemically homologous microcrystals in a polycrystal sample is a big challenge and requires developing specific highly sensitive tools. Second harmonic (SHG) and coherent anti-Stokes Raman scattering (CARS) spectroscopy can be used to reveal arrangement of thymine molecules, one of the DNA bases, in microcrystalline sample. Strong dependence of CARS and SHG intensity on the orientation of the linear polarization of the excitation light allows to obtain high resolution images of thymine microcrystals by additionally utilizing the scanning microscopy technique. Experimental findings and theoretical interpretation of the results are compared. Presented experimental data together with quantum chemistry-based theoretical interpretation allowed us to determine the most probable organization of the thymine molecules.

A Raman imaging-based technique to assess HPMC substituent contents and their effects on the drug release of commercial extended-release tablets

In this study, we tried to assess the substitute contents of HPMC used in commercial extended-release tablets directly by an innovative Raman imaging-based analysis technique and find their effects on the in vitro performance of these pharmaceuticals. Twenty-seven batches of metformin hydrochloride extended-release tablets from various sources were collected in the Chinese mainland market. While Raman imaging was used to qualitatively analyze the composition of the tablets, the MeO and HPO contents of HPMC were quantitatively assessed by a newly proposed calculation method based on the Raman intensity of corresponding characteristic band. Additionally, the dissolution test was performed to evaluate the relationship between HPMC substitution pattern and in vitro behavior. In sum, our findings indicate that the drug release rate can be downregulated by increasing the MeO content of HPMC, while the high HPO content would largely eliminate the variation of drug release profiles among batches.

Inter- and Intragrain Inhomogeneity in 2D Perovskite Thin Films Revealed by Relative Grain Orientation Imaging Using Low-Frequency Polarized Raman Microspectroscopy

Two-dimensional (2D) organic-inorganic hybrid lead halide perovskites make up an emerging class of semiconductor materials for optoelectronic applications such as solar cells. The grain structure of polycrystalline 2D perovskites is one of the key factors that dictate their functionality in the devices, but currently available methods for in situ, chemically specific characterization of 2D perovskite grains are scarce. Here we show that ultra-low-frequency polarized Raman microspectroscopy is a facile yet powerful tool for visualizing relative grain orientations within 2D perovskite thin films. We demonstrate this method on the simplest 2D perovskite, (CH₃(CH₂)₃NH₃)₂PbI₄. Hierarchical clustering and detailed band decomposition analysis of the low-frequency polarized Raman imaging data reveal not only relative grain orientations but also intragrain inhomogeneity. We envisage that with high chemical specificity, this method will find broad applications ranging from other 2D perovskites to perovskite-based optoelectronic devices.