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Responsible disposal of vehicles at the end of life is a pressing environmental concern. In particular, waste plastic forms the largest proportion of non-recycled waste material from light-duty vehicles, and often ends up in a landfill. Here we report the upcycling of depolluted, dismantled and shredded end-of-life waste plastic into flash graphene using flash Joule heating. The synthetic process requires no separation or sorting of plastics and uses no solvents or water. We demonstrate the practical value of the graphene as a re-inforcing agent in automotive polyurethane foam composite, where its introduction leads to improved tensile strength and low frequency noise absorption properties. We demonstrate process continuity by upcycling the resulting foam composite back into equal-quality flash graphene. A prospective cradle-to-gate life cycle assessment suggests that our method may afford lower cumulative energy demand and water use, and a decrease in global warming potential compared to traditional graphene synthesis methods.

Molecular motors (MM) are molecular machines, or nanomachines, that rotate unidirectionally upon photostimulation and perform mechanical work on their environment. In the last several years, it has been shown that the photomechanical action of MM can be used to permeabilize lipid bilayers, thereby killing cancer cells and pathogenic microorganisms and controlling cell signaling. The work contributes to a growing acknowledgement that the molecular actuation characteristic of these systems is useful for various applications in biology. However, the mechanical effects of molecular motion on biological materials are difficult to disentangle from photodynamic and photothermal action, which are also present when a light‐absorbing fluorophore is irradiated with light. Here, an overview of the key methods used by various research groups to distinguish the effects of photomechanical, photodynamic, and photothermal action is provided. It is anticipated that this discussion will be helpful to the community seeking to use MM to develop new and distinctive medical technologies that result from mechanical disruption of biological materials.

Hydrogen gas (H₂) is the primary storable fuel for pollution‐free energy production, with over 90 million tonnes used globally per year. More than 95% of H₂is synthesized through metal‐catalyzed steam methane reforming that produces 11 tonnes of carbon dioxide (CO₂) per tonne H₂. “Green H₂” from water electrolysis using renewable energy evolves no CO₂, but costs 2–3× more, making it presently economically unviable. Here catalyst‐free conversion of waste plastic into clean H₂along with high purity graphene is reported. The scalable procedure evolves no CO₂when deconstructing polyolefins and produces H₂in purities up to 94% at high mass yields. The sale of graphene byproduct at just 5% of its current value yields H₂production at a negative cost. Life‐cycle assessment demonstrates a 39–84% reduction in emissions compared to other H₂production methods, suggesting the flash H₂process to be an economically viable, clean H₂production route.

In the past 17 years, the larger‐scale production of graphene and graphene family materials has proven difficult and costly, thus slowing wider‐scale commercial applications. The quality of the graphene that is prepared on larger scales has often been poor, demonstrating a need for improved quality controls. Here, current industrial graphene synthetic and analytical methods, as well as recent academic advancements in larger‐scale or sustainable synthesis of graphene, defined here as weights more than 200 mg or films larger than 200 cm², are compiled and reviewed. There is a specific emphasis on recent research in the use of flash Joule heating as a rapid, efficient, and scalable method to produce graphene and other 2D nanomaterials. Reactor design, synthetic strategies, safety considerations, feedstock selection, Raman spectroscopy, and future outlooks for flash Joule heating syntheses are presented. To conclude, the remaining challenges and opportunities in the larger‐scale synthesis of graphene and a perspective on the broader use of flash Joule heating for larger‐scale 2D materials synthesis are discussed.

Hydrogen sulfide (H₂S) is a noxious, potentially poisonous, but necessary gas produced from sulfur metabolism in humans. In Down Syndrome (DS), the production of H₂S is elevated and associated with degraded mitochondrial function. Therefore, removing H₂S from the body as a stable oxide could be an approach to reducing the deleterious effects of H₂S in DS. In this report we describe the catalytic oxidation of hydrogen sulfide (H₂S) to polysulfides (HS_2+n⁻) and thiosulfate (S₂O₃²⁻) by poly(ethylene glycol) hydrophilic carbon clusters (PEG‐HCCs) and poly(ethylene glycol) oxidized activated charcoal (PEG‐OACs), examples of oxidized carbon nanozymes (OCNs). We show that OCNs oxidize H₂S to polysulfides and S₂O₃²⁻in a dose‐dependent manner. The reaction is dependent on O₂and the presence of quinone groups on the OCNs. In DS donor lymphocytes we found that OCNs increased polysulfide production, proliferation, and afforded protection against additional toxic levels of H₂S compared to untreated DS lymphocytes. Finally, in Dp16 and Ts65DN murine models of DS, we found that OCNs restored osteoclast differentiation. This new action suggests potential facile translation into the clinic for conditions involving excess H₂S exemplified by DS.

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low‐value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves anr²score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction‐limited to diffusion‐limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta‐learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. These results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.