Exploring the catalytic hydrothermal liquefaction of Namibian encroacher bush.

An urgent ecological issue is the threat posed by invasive species, which are becoming more widespread especially in Africa. These encroachments damage ecosystems, pose a threat to biodiversity, and outcompete local plants and animals. This article focuses on converting Acacia Mellifera from Namibia, commonly known as encroacher bush (EB) into high-quality drop-in intermediates for the chemical and transport industry via hydrothermal liquefaction (HTL).

Ultrasound-Guided vs Non-Ultrasound-Guided Angio-Seal Vascular Hemosasis After Endovascular Treatment for Peripheral Artery Disease: An Observational Study.

Ultrasound visualization of vascular closure devices during endovascular access closure leads to a significant decrease in overall and major post interventional access site complications. This non-invasive and often readily available imaging technique could therefore lead to an important decrease in morbidity and subsequent overall health care costs when added to the standard intervention protocol. With the increasing use of endovascular techniques to treat peripheral artery disease, the addition of ultrasound-techniques in closure of endovascular access sites could potentially have a large clinical impact, both on patient outcomes as well as financial outcomes.

Techno-economic assessment of different small-scale electrochemical NH production plants.

Electrochemical ammonia synthesis the nitrogen reduction reaction (NRR) has been poised as one of the promising technologies for the sustainable production of green ammonia. In this work, we developed extensive process models of fully integrated electrochemical NH production plants at small scale (91 tonnes per day), including their techno-economic assessments, for (Li-)mediated, direct and indirect NRR pathways at ambient and elevated temperatures, which were compared with electrified and steam-methane reforming (SMR) Haber-Bosch processes. The levelized cost of ammonia (LCOA) of aqueous NRR at ambient conditions only becomes comparable with SMR Haber-Bosch at very optimistic electrolyzer performance parameters (FE > 80% at ≥ 0.

Equivariant Neural Networks Utilizing Molecular Clusters for Accurate Molecular Crystal Lattice Energy Predictions.

Equivariant neural networks have emerged as prominent models in advancing the construction of interatomic potentials due to their remarkable data efficiency and generalization capabilities for out-of-distribution data. Here, we expand the utility of these networks to the prediction of crystal structures consisting of organic molecules. Traditional methods for computing crystal structure properties, such as plane-wave quantum chemical methods based on density functional theory (DFT), are prohibitively resource-intensive, often necessitating compromises in accuracy and the choice of exchange-correlation functional.