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This article presents findings of the Clean Tyne project. This project was part of the Clean Maritime Demonstration, funded by the United Kingdom’s Department for Transport and delivered in partnership with Innovate UK.

Formaldehyde (HCHO) is a common indoor pollutant, long-term exposure to HCHO may harm human health. Its efficient removal at mild conditions is still challenging. The catalytic oxidation of HCHO molecules on a single atomic catalyst, Ti-decorated Ti3C2O2(Ti/Ti3C2O2) monolayer, is investigated by performing the first principles calculations in this work. It demonstrates that Ti atoms can be easily well dispersed at the form of single atom on Ti3C2O2monolayer without aggregation. For HCHO catalytic oxidation, both Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms are considered. The results show that the step of HCHO dissociative adsorption on Ti/Ti3C2O2with activated O2can release high energy of 4.05 eV based on the ER mechanism, which can help to overcome the energy barrier (1.04 eV) of the subsequent reaction steps. The charge transfer from *OH group to CO molecule (dissociated from HCHO) not only promotes *OH group activation but also plays an important role in the H2O generation along the ER mechanism. Therefore, HCHO can be oxidized easily on Ti/Ti3C2O2monolayer, this work could provide significant guidance to develop effective non-noble metal catalysts for HCHO oxidation and broaden the applications of MXene-based materials.

In this work, density function theory calculations were employed to investigate the catalytic oxidation degradation of HCHO on single Al atom doped graphene system.

Potent neutralizing antibodies (nAbs) against SARS-CoV-2 are a promising therapeutic against the ongoing COVID-19 pandemic. However, the continuous emergence of neutralizing antibody escape variants makes it challenging for antibody therapeutics based on monospecific nAbs. Here, we generated an IgG-like bispecific antibody (bsAb), Bi-Nab, based on a pair of human neutralizing antibodies targeting multiple and invariant sites of the spike receptor binding domain (RBD): 35B5 and 32C7. We demonstrated that Bi-Nab exhibited higher binding affinity to the Delta spike protein than its parental antibodies and presented an extended inhibition breadth of preventing RBD binding to angiotensin-converting enzyme 2 (ACE2), the cellular receptor of SARS-CoV-2. In addition, pseudovirus neutralization results showed that Bi-Nab improved the neutralization potency and breadth with a lower half maximum inhibitory concentration (IC50) against wild-type SARS-CoV-2, variants being monitored (VBMs) and variants of concern (VOCs). Notably, the IgG-like Bi-Nab enhanced the neutralizing activity against Omicron variants with potent capabilities for transmission and immune evasion in comparison with its parental monoclonal antibody (mAb) 32C7 and a cocktail (with the lowest IC50values of 31.6 ng/mL against the Omicron BA.1 and 399.2 ng/mL against the Omicron BA.2), showing evidence of synergistic neutralization potency of Bi-Nab against the Omicron variants. Thus, Bi-Nab represents a feasible and effective strategy against SARS-CoV-2 variants of concern.

The interactions between nanoparticles and humic acid (HA) are critical to understanding the environmental risks and applications of nanoparticles. However, the interactions between HA fractions and graphene oxide (GO, a popular carbon nanosheet) at the molecular level remain largely unclear. Four HA fractions with molecular weights ranging from 4.6 to 23.8 kDa were separated, and the large HA fractions presented low oxygen contents and many aromatic structures. The binding constants of the large HA fractions on GO were 2.6- to 3551-fold higher than those of the small HA fractions, while the maximum adsorption capacities of the larger HA fractions onto GO were much higher. Atomic force microscopy (AFM) found that the small and large HA fractions were spread over the center and the edge of the GO nanosheets, respectively. Density functional theory (DFT) simulation and nuclear magnetic resonance spectroscopy confirmed the above phenomena (three adsorption patterns, “vs”, “ps”, and “pea”) and revealed that HA bonded to the GO nanosheets mainly through van der Waals force and π–π interactions. The integrating analysis of binding affinity, AFM, and DFT provides new insights into the environmental behavior of GO and the applications of GO in pollutant removal under exposure from HA.

Decision making for investing in a new pipeline project can be a long and costly process. This is usually due to the uncertainty and missing information regarding the interactions of parameters (e.g. brine chemistry, flow conditions or scale deposition) during internal corrosion assessment. In addition, these interactions result in multiple forms of internal corrosion threats (i.e. uniform corrosion, localised corrosion, erosion-corrosion and microbiologically influenced corrosion). Currently, there are no corrosion models in the market that consider all the different corrosion threats, and the predicted corrosion rates are normally conservative, leading to high overall project cost from the usage of higher grade construction material or strict maintenance regime. To predict a much more accurate internal corrosion rate with consideration of all possible corrosion mechanisms in a pipeline, a Bayesian network (BN) model was created that identifies and quantifies the causal relationships between parameters influencing internal corrosion. The model had previously proven its accuracy in predicting the internal condition of operational pipelines where explicit knowledge is available. However, the model has never been applied for a pipeline in design stage, where the design is based on tacit knowledge. In this study, to evaluate the applicability of this BN model on the pipeline at design stage, an offshore pipeline was assessed for internal corrosion.