Enhancing forensic investigations: Identifying bloodstains on various substrates through ATR-FTIR spectroscopy combined with machine learning algorithms.

The forensic analysis of bloodstains on various substrates plays a crucial role in criminal investigations. This study presents a novel approach for analyzing bloodstains using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR) in combination with machine learning. ATR-FTIR offers non-destructive and non-invasive advantages, requiring minimal sample preparation. By detecting specific chemical bonds in blood components, it enables the differentiation of various body fluids. However, the subjective interpretation of the spectra poses challenges in distinguishing different fluids. To address this, we employ machine learning techniques. Machine learning is extensively used in chemometrics to analyze chemical data, build models, and extract useful information. This includes both unsupervised learning and supervised learning methods, which provide objective characterization and differentiation. The focus of this study was to identify human and porcine blood on substrates using ATR-FTIR spectroscopy. The substrates included paper, plastic, cloth, and wood. Data preprocessing was performed using Principal Component Analysis (PCA) to reduce dimensionality and analyze latent variables. Subsequently, six machine learning algorithms were used to build classification models and compare their performance. These algorithms comprise Partial Least Squares Discriminant Analysis (PLS-DA), Decision Trees (DT), Logistic Regression (LR), Naive Bayes Classifier (NBC), Support Vector Machine (SVM), and Neural Network (NN). The results indicate that the PCA-NN model provides the optimal solution on most substrates. Although ATR-FTIR spectroscopy combined with machine learning effectively identifies bloodstains on substrates, the performance of different identification models still varies based on the type of substrate. The integration of these disciplines enables researchers to harness the power of data-driven approaches for solving complex forensic problems. The objective differentiation of bloodstains using machine learning holds significant implications for criminal investigations. This technique offers a non-destructive, simple, selective, and rapid approach for forensic analysis, thereby assisting forensic scientists and investigators in determining crucial evidence related to bloodstains.

Azeotropic Binary Solvent System Containing Nonfluorinated Polymer-Grafted Silica Nanoparticles for the Fabrication of a Superhydrophobic Surface.

This study describes a method for fabricating a superhydrophobic surface on glass via a colloidal deposition technique based on solvent evaporation-induced aggregation. Silica nanoparticles with a low grafting density of long-chain poly(cyclohexyl methacrylate) (PCH) were dispersed in a binary solvent system consisting of tetrahydrofuran (THF) and methanol (MeOH) with an azeotropic point and the nonfluorinated and hydrophobic PCHMA having a solubility parameter similar to that of THF. In the early stages of evaporation, the binary mixtures tend to induce the aggregation of PCH-NP due to the azeotropic point of the solvent components, leading to the formation of surface structures ranging from smooth to rough on the substrate. By adjusting the initial ratio of the binary solvents, a superhydrophobic coating with a water contact angle of 154 ± 2° and a sliding angle of less than 10° was achieved at a THF content of 60 wt %. This facile approach using azeotropes successfully shows that changes in the solvent composition of the binary solvent system during evaporation can be used to prepare superhydrophobic coatings with well-controlled surface structures.

A Novel Method for the Fabrication of Antibacterial Stainless Steel with Uniform Silver Dispersions by Silver Nanoparticle/Polyethyleneimine Composites.

Only a few studies have so far focused on the addition of silver to SS316L alloys by conventional sintering methods. Unfortunately, the metallurgical process of silver-containing antimicrobial SS is greatly limited due to the extremely low solubility of silver in iron and its tendency to precipitate at the grain boundaries, resulting in an inhomogeneous distribution of the antimicrobial phase and loss of antimicrobial properties. In this work, we present a novel approach to fabricate antibacterial stainless steel 316L by functional polyethyleneimine-glutaraldehyde copolymer (PEI-co-GA/Ag catalyst) composites. PEI is a highly branched cationic polymer, which makes it exhibit very good adhesion on the surface of the substrate. Unlike the effect of the conventional silver mirror reaction, the introduction of functional polymers can effectively improve the adhesion and distribution of Ag particles on the surface of 316LSS. It can be seen from the SEM images that a large number of silver particles are retained and well dispersed in 316LSS after sintering. PEI-co-GA/Ag 316LSS exhibits excellent antimicrobial properties and does not release free silver ions to affect the surrounding environment. Furthermore, the probable mechanism for the influence of the functional composites on the enhancement of adhesion is also proposed. The formation of a large number of hydrogen bonds and van der Waals forces, as well as the negative zeta potential of the 316LSS surface, can effectively enable the formation of a tight attraction between the Cu layer and the surface of 316LSS. These results meet our expectations of designing passive antimicrobial properties on the contact surface of medical devices.

Design and Ballistic Performance of Hybrid Plates Manufactured from Aramid Composites for Developing Multilayered Armor Systems.

In this study, the impact resistance of aramid fabric reinforced with shear thickening fluids (STFs), epoxy or polyurea elastomers is examined through ballistic tests. According to the ballistic test results, the aramid composite structure treated with polyurea elastomers absorbs the most impact energy per unit area density and has the best impact resistance. However, the occurrence of stress concentration during ballistic impact reduces the impact resistance of the aramid composite structure treated with epoxy. On the other hand, aramid fabric impregnated with STF improves structural protection, but it also increases the weight of the composite structure and reduces the specific energy absorption (SEA). The results of this study analyze the energy absorption properties, deformation characteristics, and damage modes of different aramid composites, which will be of interest to future researchers developing next-generation protective equipment.

Total Liquid Transfer with Enhanced Contact Line Slippage.

A new surface treatment method is developed to achieve total liquid transfer. The transfer process of a liquid droplet is recorded through high-speed photography and analyzed via image analysis to investigate the hydrodynamic interactions. For a pristine PMMA surface, a viscous and viscoelastic liquid facilitates transfer by increased viscous and inertial forces and delayed liquid bridge breakage but is limited by slow contact line slippage. Hydrophobic surface treatments can increase contact line slippage and the receding angle to achieve transfer ratios up to 98%. However, pinning and contact angle hysteresis from surface roughness features limit liquid transfer, especially for smaller droplets and higher separation velocities. A lubricant-infused surface treatment with PDMS and a thin layer of less viscous silicone oil provides a smooth, homogeneous surface with fast slippage, low contact angle hysteresis, and only a slight oil wetting ridge. Liquid could then transfer at high ratios (∼99.9%), regardless of droplet size and separation velocity. Finally, complete transfer liquid from indented cells is demonstrated to show the potential of this surface modification method for gravure printing.

Preparation and Ballistic Performance of a Multi-Layer Armor System Composed of Kevlar/Polyurea Composites and Shear Thickening Fluid (STF)-Filled Paper Honeycomb Panels.

In this study, the ballistic performance of armors composed of a polyurea elastomer/Kevlar fabric composite and a shear thickening fluid (STF) structure was investigated. The polyurea used was a reaction product of aromatic diphenylmethane isocyanate (A agent) and amine-terminated polyether resin (B agent). The A and B agents were diluted, mixed and brushed onto Kevlar fabric. After the reaction of A and B agents was complete, the polyurea/Kevlar composite was formed. STF structure was prepared through pouring the STF into a honeycomb paper panel. The ballistic tests were conducted with reference to NIJ 0101.06 Ballistic Test Specification Class II and Class IIIA, using 9 mm FMJ and 44 magnum bullets. The ballistic test results reveal that polyurea/Kevlar fabric composites offer better impact resistance than conventional Kevlar fabrics and a 2 mm STF structure could replace approximately 10 layers of Kevlar in a ballistic resistant layer. Our results also showed that a high-strength composite laminate using the best polyurea/Kevlar plates combined with the STF structure was more than 17% lighter and thinner than the conventional Kevlar laminate, indicating that the high-strength protective material developed in this study is superior to the traditional protective materials.