Improving remote material classification ability with thermal imagery.

Material recognition using optical sensors is a key enabler technology in the field of automation. Nowadays, in the age of deep learning, the challenge shifted from (manual) feature engineering to collecting big data. State of the art recognition approaches are based on deep neural networks employing huge databases. But still, it is difficult to transfer these latest recognition results into the wild-various lighting conditions, a changing image quality, or different and new material classes are challenging complications. Evaluating a larger electromagnetic spectrum is one way to master these challenges. In this study, the infrared (IR) emissivity as a material specific property is investigated regarding its suitability for increasing the material classification reliability. Predictions of a deep learning model are combined with engineered features from IR data. This approach increases the overall accuracy and helps to differentiate between materials that visually appear similar. The solution is verified using real data from the field of automatized disinfection processes.

A Pitfall in Heavy Metal Separation with Amino-modified Silica Adsorbents from Aqueous Solution: The Occurring pH Shift.

Selective separation of heavy metal ions from acidic aqueous solutions is of strong interest for certain industrial processes, such as electroplating, as well as environmental protection, for example battery recycling. Amino-functionalized adsorbents are often discussed as suitable material for this purpose. Herein, two silica-based adsorbents functionalized with 3-aminopropyl- and 3-[2-[2-aminoethylamino]-ethylamino]-propyl-ligands resulting in adsorbents MonoA and TriA, respectively, were investigated regarding their separation behavior with focus on nickel(II) and cobalt(II) in batch as well as continuous flow experiments in acidic aqueous solutions. For both adsorbents, pH shifts into the alkaline range were observed in the process solutions, causing precipitation of metal hydroxides mainly in the particle pores in case of adsorbent MonoA and a combination of precipitation and adsorption regarding adsorbent TriA. Contrary to prior studies, our findings evidence that amino-functionalized adsorbents are not applicable for nickel(II) and cobalt(II) in selective adsorption processes and additionally demonstrate that, besides batch investigations, continuous flow experiments are essential for well-founded adsorbent selections in process development.

Aerosol disinfection of bacterial spores by peracetic acid on antibacterial surfaces and other technical materials.

BACKGROUND: The effectiveness of aerosol disinfection processes based on peracetic acid (PAA) might differ depending on the surface targeted. Especially antibacterial, oligodynamic materials have to be regarded as they could cause elevated decomposition of PAA. AIM: This study aimed on the determination of differences in disinfection effectiveness using PAA caused by the treated material. METHODS: Aerosol disinfection of Geobacillus stearothermophilus spores was performed on the antibacterial, oligodynamic materials copper and brass in comparison to stainless steel and aluminium as well as polyvinylchloride, wood, and ceramics. Additionally, the influence of the materials on the decomposition reaction of PAA was evaluated. RESULTS: For aluminium and stainless steel as well as ceramics and polyvinylchloride, a disinfection of 106 spores of Geobacillus stearothermophilus on 40 cm² was obtained by the employment of 60 mL aerosolized disinfectant/m³ on laboratory scale (0.5 m³). For the application on the oligodynamic materials copper and brass an over 30% higher amount of disinfectant was necessary to achieve significant disinfection results, than for the other material surfaces. In contrast to aluminium and stainless steel, copper and brass caused elevated decomposition of PAA what seems to be the reason for the lowered disinfection effectiveness. CONCLUSIONS: Applying aerosol disinfection processes, in addition to parameters such as room size and geometry, the treated materials have to be considered when determining the necessary amount of disinfectant.