Robert N. Grass

Polyolefins are essential plastics to modern life yet create mounting sustainability challenges. Chemical recycling technologies are key but often require harsh conditions, costly hydrogen, noble metals, or complex catalysts with challenging design. We report hydrogen- and solvent-free depolymerization of polypropylene consumer goods at 240 °C, achieving >80% yield into gasoline hydrocarbons with stable performance. A library of tungstated zirconia catalysts synthesized by flame spray pyrolysis with controlled tungsten speciation enables correlating performance with the density of W–O–Zr ensembles prevalent in sub-nanoclusters, with W:Zr = 1:9 emerging as optimal. These acid sites formed during reaction mediate internal hydrogen transfer and selective backbone C–C scission, as deduced from operando spectroscopy. Life cycle and technoeconomic studies, benchmarked against hydrotreatment-based recycling in a harmonized framework, indicate competitive environmental and economic advantages. Together, this work establishes this route’s promise and underscores the value of precision catalyst synthesis in polyolefin valorization.

DNA represents a promising solution for high‐density and long‐term data storage. In this study, we explore the scalability and robustness of DNA‐of‐Things (DoT) technology by embedding digital data encoded in silica‐encapsulated DNA in newspaper ink. In honor of the 75th anniversary of the German Basic Law the “Grundgesetz” was encoded in DNA, encapsulated in silica nanoparticles, and mixed with paraffin‐based offset ink for mass distribution in a newspaper with a circulation of over 500 000 copies of “The Süddeutsche Zeitung.” We assessed the integrity and recoverability of the DNA after printing by retrieving, sequencing, and decoding the embedded data. Our results demonstrate the sensitivity and scalability of DNA‐of‐things technology. As a proof of concept, the DNA was reliably stored in printed media and successfully retrieved from a single dot of ink containing approximately 14 femtograms of DNA.

Many codecs with different error-correction approaches have been implemented for DNA data storage to date. However, no studies have systematically benchmarked codec implementations to establish their current state-of-the-art. Here, we use in silico and in vitro experiments to compare the performance of six representative codecs from literature. In isolation, these codecs can tolerate error rates up to 14% and a sequence loss of 65%. Under realistic conditions, we further establish that storage densities as high as 117 EB g ⁻¹ are feasible using existing codecs and current synthesis and sequencing technologies. Verifying our results experimentally, we demonstrate data storage at 43 EB g ⁻¹ using synthesis by material deposition and 13 EB g ⁻¹ using electrochemical synthesis, employing existing codecs from literature. Besides closing in on the physical limits of DNA data storage, this study thus demonstrates the maturity of error-correction coding, defines its current state-of-the-art, and establishes best practices for codec benchmarking.

Indium–zirconium oxides rank among the most selective and stable catalysts for CO ₂ hydrogenation to methanol. Yet, despite extensive research, the mechanistic origin of the exceptional role of monoclinic zirconia remains unresolved and continues to set the benchmark in the field. Here we show that monoclinic hafnia, a wide-bandgap oxide rarely explored in catalysis, can outperform this benchmark. Nanostructured indium–hafnium oxides synthesized via flame spray pyrolysis achieve up to 70% higher indium-specific methanol productivity than indium–zirconium oxides, with the largest gains observed for single atoms of indium. Experimental and theoretical analyses reveal that a combination of stable monoclinic support surfaces, flexible chemical potential of indium single atoms and the presence of a cooperative hydride–proton reservoir collectively enhance CO ₂ activation and intermediate hydrogenation. Crucially, the precise control of surface hydroxylation is required. These findings establish a new benchmark for green methanol synthesis and provide generalizable design principles for next-generation oxide supports in single-atom catalysis.

Background: Personal protective equipment (PPE) should effectively protect health care workers (HCWs) when treating infectious patients. However, during doffing contamination from outside of the PPE could be transferred and might cause serious infection. Therefore, complex doffing procedures have been developed, which include disinfection steps and would thereby protect the HCWs even if a contamination event occurred during doffing. However, assessing these complex multi-step procedures regarding risk of contamination and infection is challenging. The use of harmless surrogates with pathogen mimicking properties such as lipid nanoparticles encapsulating DNA (LNPs) could provide valuable insights into the effectiveness of doffing and disinfection procedures. Compared to the state-of-the-art method of contamination monitoring using fluorescent lotions LNPs promise to be more sensitive and give additional insights into the value of the disinfection steps. Methods: After pre-testing the suitability of LNPs as viral surrogates in terms of detection limit and susceptibility to ethanolic disinfection, LNPs with different barcodes were used to evaluate the PPE doffing procedure in place at the Cantonal Hospital Baden (Switzerland). During the biannual HCWs’ PPE training, several sites of the PPE were deliberately contaminated with LNPs after donning. After completion of the doffing procedure, the hands and faces of the HCWs and several environmental sites were analysed for LNP contamination via qPCR. Results: The analysis showed that no contamination of HCWs’ hands and faces was detectable, indicating the effective protection of HCWs. But some environmental sites were contaminated during the doffing procedure. Owing to the disinfection sensitivity of the LNPs it could be shown that the LNPs detected were disintegrated during one of the disinfection steps of the procedure. Conclusions: This study demonstrates that LNPs can be used as viral surrogates during the evaluation of PPE doffing procedures. LNPs can lead to insightful results due to their low detection limit and the susceptibility towards disinfection, making this method superior to fluorescent lotions. Consequently, indications for the procedures’ effectivity in inhibiting pathogen transfer to HCWs were found using LNPs. At the same time, blind spots in environmental contamination were uncovered, and the necessity of the disinfection steps in the protocol was displayed.

This work presents AutoFSP, an automated platform for the high-speed synthesis of nanoparticles by flame spray pyrolysis (FSP).

Multi-template polymerase chain reaction (PCR) is a critical technique enabling the parallel amplification of diverse DNA molecules, thereby facilitating applications in fields from quantitative molecular biology to DNA data storage. However, non-homogeneous amplification due to sequence-specific amplification efficiencies often results in skewed abundance data, compromising accuracy and sensitivity. In this study, we address amplification efficiency in complex amplicon libraries by employing one-dimensional convolutional neural networks (1D-CNNs) to predict sequence-specific amplification efficiencies, based on sequence information alone. Trained on reliably annotated datasets derived from synthetic DNA pools, these models achieve a high predictive performance (AUROC: 0.88, AUPRC: 0.44), thereby enabling the design of inherently homogeneous amplicon libraries. We further introduce CluMo, a deep learning interpretation framework that identifies specific motifs adjacent to adapter priming sites as closely associated with poor amplification. This insight leads to the elucidation of adapter-mediated self-priming as the major mechanism causing low amplification efficiency, challenging long-standing PCR design assumptions. By addressing the basis for non-homogeneous amplification in multi-template PCR, our deep-learning approach reduces the required sequencing depth to recover 99% of amplicon sequences fourfold, and opens new avenues to improve the efficiency of DNA amplification in fields such as genomics, diagnostics, and synthetic biology.

Clean, disinfected surfaces and medical instruments are critical to maintaining a hygienic environment, especially in healthcare settings. Current methods for disinfection validation and training require either a long evaluation time or do not distinguish between physical (dilution) and chemical (disintegration) disinfection procedures. However, to achieve effective disinfection, both effects, dilution and disintegration, are required for many commonly used disinfectants (e.g., alcohol, sodium hypochlorite, quaternary ammonium compounds). In this study, a method is established for the real‐time monitoring of surface disinfection using fluorescence‐labeled DNA and lipid nanoparticles (LNP) encapsulating such DNA. It is shown that the spatial separation of quencher‐modified DNA and fluorophore‐modified complementary DNA by LNPs can be disrupted by ethanolic disinfectants, facilitating the disintegration of LNPs. The resulting quenching of fluorescence can immediately be detected using a manual setup comprising a hand‐held laser, a color filter, and a smartphone camera. To demonstrate a potential application of this novel disinfection detection technology, disinfection of a commonly used medical instrument, a scalpel, is validated using the qualitative change in fluorescence upon disintegration of LNPs, enabling distinction between physical dilution and chemical disintegration. Therefore, LNPs spatially separating quencher and fluorophore offer real‐time, qualitative monitoring of surface disinfection.