Review of next generation hydrogen production from offshore wind using water electrolysis

\ua9 2023 The Author(s)Hydrogen produced using renewable energy from offshore wind provides a versatile method of energy storage and power-to-gas concepts. However, few dedicated floating offshore electrolyser facilities currently exist and therefore conditions of the offshore environment on hydrogen production cost and efficiency remain uncertain. Therefore, this review focuses on the conversion of electrical energy to hydrogen, using water electrolysis located in offshore areas. The challenges associated with the remote locations, fluctuating power and harsh conditions are highlighted and recommendations for future electrolysis system designs are suggested. The latest research in polymer electrolyte membrane, alkaline and membraneless electrolysis are evaluated in order to understand their capital costs, efficiency and current research status for achieving scaled manufacturing to the GW scale required in the next three decades. Operating fundamentals that govern the performance of each device are investigated and future recommendations of research specifically for the integration of water electrolysers with offshore wind turbines is presented

Boosting the oxygen evolution activity in non-stoichiometric praseodymium ferrite-based perovskites by A site substitution for alkaline electrolyser anodes

Sustainable fossil fuel free systems are crucial for tackling climate change in the global energy market, and the identification and understanding of catalysts needed to build these systems plays a vital role in their development. ABO3−δ perovskite oxides have been observed to be potential replacement materials for the high-performing, but low ionic conducting and economically unfavourable Pt and IrO2 water splitting catalysts. In this work increased addition of Sr2+ aliovalent dopant ions into the crystal lattice of Pr1−xSrxFeO3−δ perovskites via A site substitution was seen to drastically improve the electrocatalytic activity of the oxygen evolution reaction (OER) in alkaline environments. The undoped PrFeO3−δ catalyst was not catalytically active up to 1.70 V against the reversible hydrogen electrode (RHE), whilst an onset potential of 1.62 V was observed for x = 0.5. Increased strontium content in Pr1−xSrxFeO3−δ was found to cause a reduction in the lattice parameters and crystal volume whilst retaining the orthorhombic Pbnm space group throughout all dopant levels, analysed using the Rietveld method. However, it was noted that the orthorhombic distortion was reduced as more Sr2+ replaced Pr3+. The mechanism for the increased electrocatalytic activity with increased strontium is due to the increasing concentration of oxygen vacancy (δ), leading to increased catalyst site availability, and the increased average oxidation state of Fe cations, consistent with the iodometric titration results. This results in shifting the average d shell eg electron filling further towards unity. X-ray photoelectron spectrum of the O 1s core level also shows the presence of lattice oxide and surface hydroxide/carbonate. This work shows promise in that using the more abundant and more economically friendly material of strontium allows for improved OER catalytic activity in otherwise inactive perovskite catalyst oxides

Designing Molybdenum Trioxide and Hard Carbon Architecture for Stable Lithium-Ion Battery Anodes

\ua9 2024 The Author(s). Advanced Materials Interfaces published by Wiley-VCH GmbH. Molybdenum Trioxide (MoO3) is a promising candidate as an anode material for lithium-ion batteries (LIB), with a theoretical capacity of 1 117 mAhg−1. Nevertheless, MoO3 has inherent lower electronic conductivity and suffers from significant volume expansion during the charge–discharge cycle, which hinders its ability to attain a substantial capacity and cyclability for practical applications. In this study, a novel material design strategy is reported for LIB anodes containing MoO3 and hard carbon (HC) architecture fabricated using a Physical Vapor Deposition (PVD) technique. MoO3/HC as anode materials are evaluated for LIBs, which demonstrate an exceptional performance with a capacity of 953 mAhg−1 at a discharging rate of 0.2 C. Additionally, MoO3/HC anode demonstrated exceptional rate capability during fast charging at 5 C and achieved a capacity of 342 mAhg−1. The MoO3/HC anode demonstrates remarkable cycle life, retaining over > 99% Coulombic efficiency after 3 000 cycles at a rate of 0.2 C. The exceptional performance of MoO3/HC anode can be attributed to the novel material design strategy based on a multi-layered structure where HC provides a barrier against the possible volumetric expansion of LIB anode

An efficient cathode electrocatalyst for anion exchange membrane water electrolyzer

\ua9 2024 The AuthorsA high performance and durable electrocatalyst for the cathodic hydrogen evolution reaction (HER) in anion exchange membrane (AEM) water electrolyzers is crucial for the emerging hydrogen economy. Herein, we synthesized Pt–C core-shell nanoparticles (core: Pt nanoparticles, shell: N-containing carbon) were uniformly coated on hierarchical MoS2/GNF using pyrolysis of h-MoS2/GNF with a Pt-aniline complex. The synthesized Pt–C core-shell@h-MoS2/GNF (with 11.3 % Pt loading) showed HER activity with a lower overpotential of 30 mV at 10 mA cm−2 as compared to the benchmark catalyst 20 % Pt–C (41 mV at 10 mA cm−2) with improved durability over 94 h at 10 mA cm−2. Furthermore, we investigated the structural stability and hydrogen adsorption energy for Pt13 cluster, C90 molecule, h-MoS2 sheet, Pt13–C90 core-shell, and Pt13–C90 core-shell deposited h-MoS2 sheets using density functional theory (DFT) simulations. We investigated the Pt–C core-shell@h-MoS2/GNF catalyst active sites during HER performance using in-situ Raman analysis as well as DFT. We fabricated AEM water electrolyzers with cathode catalysts of Pt–C core-shell@h-MoS2/GNF and evaluated device performance with 0.1 and 1.0 M KOH at 20 and 60 \ub0C. Our work provides a new pathway to design core-shell electrocatalysts for use in AEM water electrolyzers to generate hydrogen

Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization

In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain unclear. Here, we use non-negative matrix factorization (NMF) – a dimensionality reduction technique – to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor dimensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner. We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures

Leveraging machine learning in porous media

\ua9 2024 The Royal Society of Chemistry.The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML), has had a significant impact on engineering and the fundamental sciences, resulting in advances in various fields. The use of ML has significantly enhanced data processing and analysis, eliciting the development of new and improved technologies. Specifically, ML is projected to play an increasingly significant role in helping researchers better understand and predict the behavior of porous media. Furthermore, ML models will be able to make use of sizable datasets, such as subsurface data and experiments, to produce accurate predictions and simulations of porous media systems. This capability could help optimize the design of porous materials for specific applications and improve the effectiveness of industrial processes. To this end, this review paper attempts to provide an overview of the present status quo in this context, i.e., the interface of ML and porous media in six different applications, namely, heat exchanger and storage, energy storage and combustion, electrochemical devices, hydrocarbon reservoirs, carbon capture and sequestration, and groundwater, stressing the advances made in the application of ML to porous media and offering insights into the challenges and opportunities for future research. Each section also entails a supplementary database of the literature as a spreadsheet, which includes the details of ML models, datasets, key findings, etc., and mentions relevant available online datasets that can be used to train ML models. Future research trends include employing hybrid models by combining ML models with physics-based models of porous media to improve predictions concerning accuracy and interpretability

A RAS-independent biomarker panel to reliably predict response to MEK inhibition in colorectal cancer

BACKGROUND: In colorectal cancer (CRC), mutations of genes associated with the TGF-β/BMP signaling pathway, particularly affecting SMAD4, are known to correlate with decreased overall survival and it is assumed that this signaling axis plays a key role in chemoresistance. METHODS: Using CRISPR technology on syngeneic patient-derived organoids (PDOs), we investigated the role of a loss-of-function of SMAD4 in sensitivity to MEK-inhibitors. CRISPR-engineered SMAD4(R361H) PDOs were subjected to drug screening, RNA-Sequencing, and multiplex protein profiling (DigiWest(R)). Initial observations were validated on an additional set of 62 PDOs with known mutational status. RESULTS: We show that loss-of-function of SMAD4 renders PDOs sensitive to MEK-inhibitors. Multiomics analyses indicate that disruption of the BMP branch within the TGF-β/BMP pathway is the pivotal mechanism of increased drug sensitivity. Further investigation led to the identification of the SFAB-signature (SMAD4, FBXW7, ARID1A, or BMPR2), coherently predicting sensitivity towards MEK-inhibitors, independent of both RAS and BRAF status. CONCLUSION: We identified a novel mutational signature that reliably predicts sensitivity towards MEK-inhibitors, regardless of the RAS and BRAF status. This finding poses a significant step towards better-tailored cancer therapies guided by the use of molecular biomarkers