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Diallyl phthalate (DAP), a crucial raw material in producing resin materials, has been studied widely in terms of its polymerization process and application in material modification. However, less attention has been paid to its safety. In this study, the influence of initiators on the thermal hazard of DAP was examined from various viewpoints by conducting thermogravimetric and differential scanning calorimetry experiments and by performing thermokinetic analysis with multiple models. Moreover, the reaction mechanism of DAP was studied. The three-step autocatalysis reaction simulations agreed well with the experimental findings obtained for DAP. The simulated conversion limit time and time to the maximum rate under adiabatic conditions indicate that the thermal hazard of DAP can serve as a reference for controlling its production and storage temperatures.

Autocatalysis is essential for the origin of life and chemical evolution. However, the lack of a unified framework so far prevents a systematic study of autocatalysis. Here, we derive, from basic principles, general stoichiometric conditions for catalysis and autocatalysis in chemical reaction networks. This allows for a classification of minimal autocatalytic motifs called cores. While all known autocatalytic systems indeed contain minimal motifs, the classification also reveals hitherto unidentified motifs. We further examine conditions for kinetic viability of such networks, which depends on the autocatalytic motifs they contain and is notably increased by internal catalytic cycles. Finally, we show how this framework extends the range of conceivable autocatalytic systems, by applying our stoichiometric and kinetic analysis to autocatalysis emerging from coupled compartments. The unified approach to autocatalysis presented in this work lays a foundation toward the building of a systems-level theory of chemical evolution.

Layered oxides widely used as lithium-ion battery electrodes are designed to be cycled under conditions that avoid phase transitions. Although the desired single-phase composition ranges are well established near equilibrium, operando diffraction studies on many-particle porous electrodes have suggested phase separation during delithiation. Notably, the separation is not always observed, and never during lithiation. These anomalies have been attributed to irreversible processes during the first delithiation or reversible concentration-dependent diffusion. However, these explanations are not consistent with all experimental observations such as rate and path dependencies and particle-by-particle lithium concentration changes. Here, we show that the apparent phase separation is a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions, that is, an interfacial exchange current that increases with the extent of delithiation. We experimentally validate this population-dynamics model using the single-phase material Li x (Ni 1/3 Mn 1/3 Co 1/3 )O 2 (0.5 <  x  < 1) and demonstrate generality with other transition-metal compositions. Operando diffraction and nanoscale oxidation-state mapping unambiguously prove that this fictitious phase separation is a repeatable non-equilibrium effect. We quantitatively confirm the theory with multiple-datastream-driven model extraction. More generally, our study experimentally demonstrates the control of ensemble stability by electro-autocatalysis, highlighting the importance of population dynamics in battery electrodes (even non-phase-separating ones). Although layered oxides electrodes in lithium-ion batteries are designed under conditions avoiding phase transitions, phase separation during delithiation has been observed. This apparent phase separation is shown to be a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions.

Control of CRISPR/Cas12a trans -cleavage is crucial for biosensor development. Here, we show that small circular DNA nanostructures which partially match guide RNA sequences only minimally activate Cas12a ribonucleoproteins. However, linearizing these structures restores activation. Building on this finding, an Autocatalytic Cas12a Circular DNA Amplification Reaction (AutoCAR) system is established which allows a single nucleic acid target to activate multiple ribonucleoproteins, and greatly increases the achievable reporter cleavage rates per target. A rate-equation-based model explains the observed near-exponential rate trends. Autocatalysis is also sustained with DNA nanostructures modified with fluorophore-quencher pairs achieving 1 aM level (<1 copy/μL) DNA detection (10 6 times improvement), without additional amplification, within 15 min, at room temperature. The detection range is tuneable, spanning 3 to 11 orders of magnitude. We demonstrate 1 aM level detection of SNP mutations in circulating tumor DNA from blood plasma, genomic DNA ( H. Pylori ) and RNA (SARS-CoV-2) without reverse transcription as well as colorimetric lateral flow tests of cancer mutations with ~100 aM sensitivity. The authors find that small circular DNA nanostructures which partially match gRNA sequences only minimally activate Cas12a. They report AutoCAR (Autocatalytic Cas12a Circular DNA Amplification Reaction) which allows a single nucleic acid target to activate multiple ribonucleoproteins, and increases reporter cleavage rates.

Reaction currents in chemical networks usually increase when increasing their driving affinities. But far from equilibrium the opposite can also happen. We find that such negative differential response (NDR) occurs in reaction schemes of major biological relevance, namely, substrate inhibition and autocatalysis. We do so by deriving the full counting statistics of two minimal representative models using large deviation methods. We argue that NDR implies the existence of optimal affinities that maximize the robustness against environmental and intrinsic noise at intermediate values of dissipation. An analogous behavior is found in dissipative self-assembly, for which we identify the optimal working conditions set by NDR.

Here we show how a simple inorganic salt can spontaneously form autocatalytic sets of replicating inorganic molecules that work via molecular recognition based on the {PMo12} ≡ [PMo12O40]3– Keggin ion, and {Mo36} ≡ [H₃Mo57M₆(NO)₆O183(H₂O)18]22– cluster. These small clusters are able to catalyze their own formation via an autocatalytic network, which subsequently template the assembly of gigantic molybdenum-blue wheel {Mo154} ≡ [Mo154O462H14(H₂O)70]14–, {Mo132} ≡ [MoVI 72MoV 60O372(CH₃COO)30(H₂O)72]42– ball-shaped species containing 154 and 132 molybdenum atoms, and a {PMo12}⊂{Mo124Ce₄} ≡ [H16MoVI 100MoV 24Ce₄O376(H₂O)56 (PMoVI 10MoV₂O40)(C₆H12N₂O₄S₂)₄]5– nanostructure. Kinetic investigations revealed key traits of autocatalytic systems including molecular recognition and kinetic saturation. A stochastic model confirms the presence of an autocatalytic network involving molecular recognition and assembly processes, where the larger clusters are the only products stabilized by the cycle, isolated due to a critical transition in the network.

Water influences critically the kinetics of the autocatalytic conversion of methanol to hydrocarbons in acid zeolites. At very low conversions but otherwise typical reaction conditions, the initiation of the reaction is delayed in presence of H₂O. In absence of hydrocarbons, the main reactions are the methanol and dimethyl ether (DME) interconversion and the formation of a C₁ reactive mixture—which in turn initiates the formation of first hydrocarbons in the zeolite pores. We conclude that the dominant reactions for the formation of a reactive C₁ pool at this stage involve hydrogen transfer from both MeOH and DME to surface methoxy groups, leading to methane and formaldehyde in a 1:1 stoichiometry. While formaldehyde reacts further to other C₁ intermediates and initiates the formation of first C–C bonds, CH₄ is not reacting. The hydride transfer to methoxy groups is the rate-determining step in the initiation of the conversion of methanol and DME to hydrocarbons. Thus, CH₄ formation rates at very low conversions, i.e., in the initiation stage before autocatalysis starts, are used to gauge the formation rates of first hydrocarbons. Kinetics, in good agreement with theoretical calculations, show surprisingly that hydrogen transfer from DME to methoxy species is 10 times faster than hydrogen transfer from methanol. This difference in reactivity causes the observed faster formation of hydrocarbons in dry feeds, when the concentration of methanol is lower than in presence of water. Importantly, the kinetic analysis of CH₄ formation rates provides a unique quantitative parameter to characterize the activity of catalysts in the methanol-to-hydrocarbon process.

A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first \"living\" systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where self-reproducing and evolving proto-metabolic networks are assumed to have predated self-replicating genes. Recent theoretical work shows that \"compositional genomes\" (i.e., the counts of different molecular species in an assembly) are able to propagate compositional information and can provide a setup on which natural selection acts. Accordingly, if we stick to the notion of replicator as an entity that passes on its structure largely intact in successive replications, those macromolecular aggregates could be dubbed \"ensemble replicators\" (composomes) and quite different from the more familiar genes and memes. In sharp contrast with template-dependent replication dynamics, we demonstrate here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and, therefore, the system lacks evolvability (i.e., it cannot substantially depart from the asymptotic steady-state solution already built-in in the dynamical equations). We conclude that this fundamental limitation of ensemble replicators cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.

The major applications of PGMs are as catalysts in automotive industry, petroleum refining, environmental (gas remediation), industrial chemical production (e.g., ammonia production, fine chemicals), electronics, and medical fields. As the next generation energy technologies for hydrogen production, such as electrolysers and fuel cells for stationary and transport applications, become mature, the demand for PGMs is expected to further increase. Reserves and annual production of Ru, Rh, Pd, Ir, and Pt have been determined and reported. Based on currently available resources, there is around 200 years lifetime based on current demand for all PGMs, apart from Pd, which may be closer to 100 years. Annual primary production of 190 t/a for Pt and 217 t/a for Pd, in combination with recycling of 65.4 t/a for Pt and 97.2 t/a for Pd, satisfies current demand. By far, the largest demand for PGMs is for all forms of catalysis, with the largest demand in auto catalysis. In fact, the biggest driver of demand and price for Pt, Pd, and Rh, in particular, is auto emission regulation, which has driven auto-catalyst design. Recovery of PGMs through recycling is generally good, but some catalytic processes, particularly auto-catalysis, result in significant dissipation. In the US, about 70% of the recycling stream from the end-of-life vehicles is a significant source of global secondary PGMs recovered from spent auto-catalyst. The significant use of PGMs in the large global auto industry is likely to continue, but the long-term transition towards electric vehicles will alter demand profiles.