Deep learning strategies for addressing issues with small datasets in 2D materials research: Microbial Corrosion.

Protective coatings based on two dimensional materials such as graphene have gained traction for diverse applications. Their impermeability, inertness, excellent bonding with metals, and amenability to functionalization renders them as promising coatings for both abiotic and microbiologically influenced corrosion (MIC). Owing to the success of graphene coatings, the whole family of 2D materials, including hexagonal boron nitride and molybdenum disulphide are being screened to obtain other promising coatings. AI-based data-driven models can accelerate virtual screening of 2D coatings with desirable physical and chemical properties. However, lack of large experimental datasets renders training of classifiers difficult and often results in over-fitting. Generate large datasets for MIC resistance of 2D coatings is both complex and laborious. Deep learning data augmentation methods can alleviate this issue by generating synthetic electrochemical data that resembles the training data classes. Here, we investigated two different deep generative models, namely variation autoencoder (VAE) and generative adversarial network (GAN) for generating synthetic data for expanding small experimental datasets. Our model experimental system included few layered graphene over copper surfaces. The synthetic data generated using GAN displayed a greater neural network system performance (83-85% accuracy) than VAE generated synthetic data (78-80% accuracy). However, VAE data performed better (90% accuracy) than GAN data (84%-85% accuracy) when using XGBoost. Finally, we show that synthetic data based on VAE and GAN models can drive machine learning models for developing MIC resistant 2D coatings.

Enhanced electrical conductivity of anticorrosive coatings by functionalized carbon nanotubes: effect of hydrogen bonding.

Carbon nanotubes and nanofibers (CNFs) are well-known nano additives to produce coating materials with high electrical and thermal conductivity and corrosion resistance. In this paper, coating materials incorporating hydrogen bonding offered significantly lower electrical resistance. The hydrogen bonding formed between functionalized carbon nanotubes and ethanol helped create a well-dispersed carbon nanotube network as the electron pathways. Electrical resistivity as low as 6.8 Ω cm has been achieved by adding 4.5 wt% functionalized multiwalled carbon nanotubes (MWNT-OH) to 75%polyurethane/25%ethanol. Moreover, the thermal conductivity of polyurethane was improved by 332% with 10 wt% addition of CNF. Electrochemical methods were used to evaluate the anti-corrosion properties of the fabricated coating materials. 75%polyurethane/25%ethanol with the addition of 3.0 wt% of MWNT-OH showed an excellent corrosion rate of 5.105 × 10-3mm year-1, with a protection efficiency of 99.5% against corrosive environments. The adhesion properties of the coating materials were measured following ASTM standard test methods. 75%polyurethane/25%ethanol with 3.0 wt% of MWNT-OH belonged to class 5 (ASTM D3359), indicating the outstanding adhesion of the coating to the substrate. These nanocoatings with enhanced electrical, thermal, and anti-corrosion properties consist of a choice of traditional coating materials, such as polyurethane, yielding coating durability with the ability to tailor the electrical and thermal properties to fit the desired application.

Gene Sets and Mechanisms of Sulfate-Reducing Bacteria Biofilm Formation and Quorum Sensing With Impact on Corrosion.

Sulfate-reducing bacteria (SRB) have a unique ability to respire under anaerobic conditions using sulfate as a terminal electron acceptor, reducing it to hydrogen sulfide. SRB thrives in many natural environments (freshwater sediments and salty marshes), deep subsurface environments (oil wells and hydrothermal vents), and processing facilities in an industrial setting. Owing to their ability to alter the physicochemical properties of underlying metals, SRB can induce fouling, corrosion, and pipeline clogging challenges. Indigenous SRB causes oil souring and associated product loss and, subsequently, the abandonment of impacted oil wells. The sessile cells in biofilms are 1,000 times more resistant to biocides and induce 100-fold greater corrosion than their planktonic counterparts. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation and corrosion. Here, we examine the critical genes involved in biofilm formation and microbiologically influenced corrosion and categorize them into various functional categories. The current effort also discusses chemical and biological methods for controlling the SRB biofilms. Finally, we highlight the importance of surface engineering approaches for controlling biofilm formation on underlying metal surfaces.