•Effect of high volume GGBS on the UHPC under different curing conditions.•Increase in incorporation of GGBS significantly improves the flowability.•Hardened properties are improved up to 60% of GGBS ...under temperature curing.•Uni-axial tensile results of UHPC are arrived using direct tensile test.•SEM and EDX confirm the dense microstructure and bonding of steel fibre-matrix.
The supplementary cementitious materials (SCMs) are used as a substitute for the cement to reduce the environmental issues backed by concrete industry for the past three decades. Additionally, the use of industrial waste as SCMs can mitigate the wastes dumped in lagoons and landfills sites. Ground granulated blast furnace slag (GGBS) is one of the potential candidates as it possesses strength, durability, economic, and environmental benefits. In this study, GGBS is used in Ultra high performance concrete (UHPC) up to 80% replacement level of cement. Various properties such as flowability, compressive strength, tensile strength, fracture, and durability of UHPC with a high volume GGBS are experimentally evaluated under two curing conditions (Standard water and elevated temperature curing). Uniaxial tensile (UAT) strength test is conducted to determine the tensile strength for UHPC. The test results inferred that the hardened properties of GGBS based UHPC are significant upto 40% cement replacement level under standard water curing. Elevated temperature curing, improves its performance upto 60% replacement level. Finally, microstructure properties are studied using scanning electron microscopy which confirms the dense microstructure of UHPC with a high volume GGBS.
Materials databases generated by high-throughput computational screening, typically using density functional theory (DFT), have become valuable resources for discovering new heterogeneous catalysts, ...though the computational cost associated with generating them presents a crucial roadblock. Hence there is a significant demand for developing descriptors or features, in lieu of DFT, to accurately predict catalytic properties, such as adsorption energies. Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS). The model, DOSnet, is evaluated for a diverse set of adsorbates and surfaces, yielding a mean absolute error on the order of 0.1 eV. In addition, DOSnet can provide physically meaningful predictions and insights by predicting responses to external perturbations to the electronic structure without additional DFT calculations, paving the way for the accelerated discovery of materials and catalysts by exploration of the electronic space.
Asparagine(N)297-linked glycosylation of immunoglobulin G (IgG) Fc is required for binding to FcγRIIa, IIb, and IIIa, although it is unclear how it contributes. We found the quaternary structure of ...glycosylated Fc was indistinguishable from aglycosylated Fc, indicating that N-glycosylation does not maintain relative Fc Cγ2/Cγ3 domain orientation. However, the conformation of the C′E loop, which contains N297, was significantly perturbed in the aglycosylated Fc variant. The conformation of the C′E loop as measured with a range of Fc variants shows a strong correlation with FcγRIIIa affinity. These results indicate that the primary role of the IgG1 Fc N-glycan is to stabilize the C′E loop through intramolecular interactions between carbohydrate and amino acid residues, and preorganize the FcγRIIIa interface for optimal binding affinity. The features that contribute to the capacity of the IgG1 Fc N-glycan to restrict protein conformation and tune binding affinity are conserved in other antibodies including IgG2–IgG4, IgD, IgE, and IgM.
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•The 4° structure of glycosylated Fc was indistinguishable from aglycosylated Fc•The N-glycan stabilizes the Fc C′E loop•Residue substitutions targeting the C′E loop conformation reduce FcγRIIIa affinity•Stabilizing the first N-glycan residue linked to N297 is essential
It is well known that immunoglobulin G N-glycosylation is required for recognition by immune cell receptors; however, it is not clear why. Subedi and Barb demonstrate that N-glycosylation stabilizes a single small protein loop on the Fc.
Abstract
An affordable and sustainable tertiary treatment is imperative to solve the secondary contamination issues related to wastewater reuse. To decontaminate and disinfect the actual secondary ...treated wastewater, various types of advanced oxidation processes (AOPs) have been studied. The optimization of the oxidant and catalyst is carried out to identify the best-performing system. Under selected experimental conditions, UV/peroxymonosulfate (PMS), O3/PMS, UV/MnO2, O3/MnO2, UV/O3/H2O2, O3/MnO2/H2O2, UV/MnO2/H2O2, and UV/O3/MnO2 has been identified as an efficient treatment option for simultaneous decontamination (>90% COD removal) and disinfection (100% inactivation of the total viable count of bacteria). The techno-economic assessment revealed that UV/MnO2 (23.5 $ kg−1 of COD) UV/O3/MnO2 (37.4 $ kg−1 of COD), UV/H2O2/MnO2 (36.4 $ kg−1 of COD), and O3/MnO2/H2O2 (32.5 $ kg−1 of COD) are comparatively low-cost treatment processes. Overall, UV/MnO2, UV/H2O2/MnO2, and O3/MnO2/H2O2 are the three best treatments. Nevertheless, further investigation on by-product and catalyst toxicity/recovery is needed. The results showed that AOPs are a technologically feasible treatment for simultaneously removing persistent organic pollutants and pathogens from secondary treated wastewater.
The electronic structure of a material, such as its density of states (DOS), provides key insights into its physical and functional properties and serves as a valuable source of high-quality features ...for many materials screening and discovery workflows. However, the computational cost of calculating the DOS, most commonly with density functional theory (DFT), becomes prohibitive for meeting high-fidelity or high-throughput requirements, necessitating a cheaper but sufficiently accurate surrogate. To fulfill this demand, we develop a general machine learning method based on graph neural networks for predicting the DOS purely from atomic positions, six orders of magnitude faster than DFT. This approach can effectively use large materials databases and be applied generally across the entire periodic table to materials classes of arbitrary compositional and structural diversity. We furthermore devise a highly adaptable scheme for physically informed learning which encourages the DOS prediction to favor physically reasonable solutions defined by any set of desired constraints. This functionality provides a means for ensuring that the predicted DOS is reliable enough to be used as an input to downstream materials screening workflows to predict more complex functional properties, which rely on accurate physical features.
2D materials have attracted tremendous interest as functional materials because of their diverse and tunable properties, especially at their edges. A material’s work function is a critical parameter ...in many electronic devices; however, a fundamental understanding and a path toward large alterations of the work function in 2D materials still remain elusive. Here, we report the first evidence for anisotropy of the work function in 2D MoS2 from first-principles calculations. We also demonstrate large work-function tunability (in the range of 3.45–6.29 eV) choosing the 2H phase of MoS2 as a model system by sampling various edge configurations. We furthermore reveal the origin of this work function anisotropy and tunability by extending the existing work function relation to the local dipole moment at surfaces of 3D materials to those at edges in 2D materials. We then use machine-learning approaches to correlate work function with edge structures. These results pave the way for intrinsic edge engineering for electronic and catalytic applications.
For the first time, we report a facile one pot aqueous method for support-free Pd85Pt15 nano-porous structures (NPoS) synthesis from PdMn nano-alloys at ambient conditions. A hierarchical approach ...was successfully employed through a simple “self-settlement” process with descending amounts of carbon to carbon-free electro-catalysts to improve catalyst utilization and avoid carbon degradation during fuel cell operating conditions. Pd85Pt15 NPoS exhibits enhanced methanol resistive oxygen reduction reaction (ORR) activity owing to the presence of highly active and unique surface PdPt islands compared to HiSPEC Pt/C catalysts. Accelerated durability tests of the support-free PdPt NPoS show enhanced durability in harsh acidic environment (1.0 N H2SO4) compared to HiSPEC Pt/C and DOE 2017–2020 durability target. Preliminary direct methanol fuel cell studies using hierarchically derived Pd85Pt15 NPoS variants were performed at ultra-low Pt content. The effects of carbon content and catalyst layer thickness on fuel cell activities are well discussed.
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•Facile and novel one pot aqueous synthesis of support free nano-porous Pd85Pt15 electro-catalysts from PdMn nano-alloy.•Exhibits enhanced methanol resistive oxygen reduction activity owing to the presence of surface active Pd-Pt nano-islands.•Accelerated durability tests shows excellent stability in 1.0 N H2SO4 electrolyte.•Direct methanol fuel cell studies shows a highest power density (85 mWmg−1Ptcm−2) at ultra-low total Pt content.
The management of post-consumer discarded plastic wastes (PCPW) creates new challenges in developing countries due to the lack of amenities, technological interventions, and associated negative ...environmental externalities. The fate of untreated recyclable and non-recyclable plastic wastes lies in open dumping along with other solid waste, and improper management leads to environmental externalities such as pollution, global climate change, and health issues. Additionally, open dumping upsurges the emerging microplastics and nano plastics (MNPs) contaminants. The externalities depend on the waste generating sources (household, industries, commercial), waste composition, and its characteristics. However, urban mining can minimize environmental externalities where waste plastics can convert into potential anthropogenic resources and also helps in achieving the target of sustainable development goals (SDGs 11 & 12). Moreover, various treatment technologies that help in the sustainable utilization of plastic wastes are extensively reviewed in this study and evaluate the costs benefits arising during various stages of treating plastic waste through recycling (R), incineration (I), and landfilling (L). The recycling of plastic waste has demonstrated the lowest impact on global warming potential (GWP) and total energy use (TEU), followed by landfilling and incineration (R < L < I). Nevertheless, when energy is recovered from inert (non-recyclable) plastic waste in the form of fuel or by its utilization in construction purposes, the environmental impacts are more negligible (Incineration < Landfilling). Therefore, this study determines the significance of circular economy with legislative approach and standards on plastic waste management, which help in reducing environmental externalities besides yielding a secondary resource as energy and materials through urban mining. A sustainable plastic waste management (SPWM) model is proposed for developing countries to convert plastic waste into resources and use it as a sustainable tool in urban mining.
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•Globally, 0.4 billion tons of plastic wastes have been generated.•Mismanagement of plastic waste creates negative environmental externalities.•The SPWM model reduces environmental externalities.•Urban mining is a sustainable tool to convert plastic waste into resources.
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