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LuSi crystallizes in the orthorhombic Cmcm space group. The structure is three-dimensional. Lu is bonded in a 5-coordinate geometry to seven equivalent Si atoms. There are a spread of Lu–Si bond distances ranging from 2.88–3.07 Å. Si is bonded in a 9-coordinate geometry to seven equivalent Lu and two equivalent Si atoms. Both Si–Si bond lengths are 2.48 Å.
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Fast pyrolysis is a robust deconstruction technology for chemically upcycling waste plastics without losing significant carbon to noncondensable gases. However, fast pyrolysis of polyolefins often produces hydrocarbons with broad molecular weight distributions, mainly waxes, which can also negatively affect the commercial reactor operation and downstream upgrading of the products. We discovered that combining molten-phase thermal treatment with subsequent fast pyrolysis offers a facile method to enhance polyolefin pyrolysis and catalytic upgrading. The molten-phase thermal treatment increased unsaturated C–C bonds in the treated polyolefins. During subsequent pyrolysis, the preheated polyolefins significantly reduced wax range hydrocarbons in the condensable products without an increase in gas formation. Here, the wax yields from pyrolysis of high-density polyethylene (HDPE) preheated to 295 °C and low-density polyethylene (LDPE) preheated to 275 °C were 20.5% and 26.5%, respectively, compared to 38.6% and 46% produced from pyrolyzing untreated polyolefins. When catalytically pyrolyzed using a zeolite catalyst, the preheated polyolefins promoted higher yields of olefins during ex-situ catalytic pyrolysis and higher yields of aromatic hydrocarbons during in-situ catalytic pyrolysis. During ex-situ catalytic pyrolysis, ethylene yields were 23.3% and 24.7% for the preheated HDPE and LDPE compared to 16.7% and 9.3% for untreated HDPE and LDPE, respectively.
Mechanical recycling and chemical upcycling by thermochemical reactions have been the major approaches for recycling end-of-life plastics. Herein, we report an electrified approach to upcycle waste plastics into carbon-negative commodity chemicals using greenhouse gas CO 2 as the oxidant and additional carbon source. In this non-equilibrium plasma process, waste polyolefins were oxidatively depolymerized by plasma-activated CO 2 to produce oleochemicals and hydrocarbon chemicals in a single-step process at high reaction rates. In addition, a mixture of CO 2 and a small amount of O 2 was employed as plasma gases to selectively produce fatty alcohols from polyolefins. Based on this atmospheric pressure, non-solvent, and non-catalyst process, up to 97.6% of fatty alcohols could be produced within minutes. In this article, the co-conversion approach was demonstrated using common polyolefins and real-world mixed waste plastics to obtain comparable results. The techno-economic analysis estimates the internal rate of return to be 42.2% and 43.5% for the plasma-based conversion of waste plastics, depending on the plasma gas composition. Lifecycle assessment indicates the global warming potential is between −3.33 and −3.07 kg CO 2e per kg of plastic.
Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals’ demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI’s potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the ‘loss of control’ (27.6%) and ‘diagnostic errors’ (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.