ChemSystemsChem最新文献

Temporal control of the chemical properties of a molecular system is a main goal of the research focused on dissipative systems, systems chemistry, and smart materials. In this work, we show that nitroacetic acid, a typical activated carboxylic acid (ACA), can be exploited to transiently amplify the electrical conductivity of an aqueous solution. The addition of nitroacetic acid to a water solution induces a transient increase in conductivity, which then decreases over time following the kinetically first order conversion of nitroacetic acid into nitromethane. The rate of the decrease in conductivity can be modulated by varying the temperature or the concentration of an auxiliary base further added to the solution. The time-control of the conductivity is exploited to build a variable resistor which is integrated in simple circuits to operate electrical devices.

Nonenzymatic self-replication is considered as one of the most primordial functions of RNA, which likely preceded the emergence of more complex ribozymes. Among different possible scenarios, nucleotide activation with imidazole derivatives attracted substantial attention over the last years. However, despite the progress in proposing plausible variants of nonenzymatic RNA template copying with phosphoroimidazolides, mechanistic aspects of this process still remain obscure. Furthermore, efficient RNA self-replication involving activated uridine and adenosine still remains a challenge. Here, we employed classical molecular dynamics simulations to evaluate the binding specificity of different imidazolium-bridged dinucleotide intermediates, which was suggested to control the yield and fidelity of the reaction. In particular, RMSD-based clustering of the MD trajectories revealed previously unknown structural arrangements of activated dinucleotide intermediates that may play a critical role in nonenzymatic primer extension. Most importantly, our results indicate that yield and fidelity of nonenzymatic RNA template copying cannot be simply associated with the number of Watson–Crick hydrogen bonds between the activated dinucleotides and the templating strand. Instead, the efficiency of the reaction correlates with the preference for the formation of the canonically stacked form of the activated dinucleotide intermediate, which can then selectively bind to the template and participate in the primer extension reaction.

Catalysis plays a central role in the creation of life and is vital for living systems. How catalysts have evolved over the years remains a mystery. The answer to this question is central for understanding enzyme evolution and developing new catalytic entities. Enzymes are folded sequences of coded amino acids. These building blocks may have been present under prebiotic conditions. However, how simple amino acids evolved to create complicated and functional macromolecules such as enzymes is still unknown. Previous reports have shown that coded amino acids, their assemblies, and complexes with metals can have catalytic activity. We have recently demonstrated that even a noncoded amino acid, l-3,4-dihydroxyphenylalanine (DOPA), can catalyze two hydrolysis reactions mediated by its hydroxybenzene moiety. DOPA is found in marine mussels' foot proteins. These proteins function in an environment characterized by high salt concentrations and UV radiation similar to suggested prebiotic conditions. Here, we show that other hydroxybenzene molecules, such as pyrogallol, can also catalyze hydrolysis reactions. The catalytic activity of the hydrolysis reactions of p-nitrophenylacetate and thioacetylcholine depended on the number of hydroxyl groups and their relative position on the benzene rings. The catalytic activity of pyrogallol and tannic acid is stable even at high temperatures, close to the boiling point of water, suggesting they can function as stable artificial catalysts.

Learning and memory, once associated only with intelligent life forms, are now increasingly recognized in both physical and virtual systems, such as simple organisms, machines, and even designed chemical systems. The Perspective by Kübra Kaygisiz and Rein V. Ulijn explores how molecular components can be engineered to create supramolecular systems capable of learning, with potential applications in materials science and next-generation computing.

The idea that organic chemistry can gradually self-organize towards the emergence of life has been challenged by views considering that the most important driver should be the existence of a crucial thermodynamic disequilibrium. In this work, past views are critically addressed and a mechanism through which disequilibrium can promote the emergence and development of organized systems is suggested. This analysis is based on the propensity of carbon to form covalent bonds with other elements, which usually corresponds to deep energy wells generating high kinetic barriers hindering reactions. Potential energy wells and the associated kinetic barriers are considered as storing a prepaid entropy loss within a potential energy surface and therefore constitute a potential giving room for subsequent self-organization processes. This potential associated with the notion of Kinetically Stable Thermodynamically Activated (KSTA) compounds gives rise to the possibility of alternative pathways based on non-linear autocatalytic processes. As other systems working in a far-from-equilibrium context, like molecular machines, kinetic parameters are crucial for determining how they proceed and how they change, which suggests that interactions between the fields of molecular machines and of the emergence of life could be mutually beneficial.

In systems chemistry, a key goal is to design molecular networks that exhibit emergent behaviors beyond those of their individual components. Dynamic combinatorial libraries (DCLs), which consist of molecular species interconverting through reversible reactions, provide a powerful platform to achieve this. This study introduces a DCL constructed using reversible exchange reactions involving thiols, dithioacetals, thioesters, and disulfides. The library is organized into two distinct yet interconnected layers: one activated under acidic conditions via thiol/dithioacetal exchange, and the other responsive to basic conditions through thiol/thioester/disulfide exchange, with temperature further modulating these processes. The layers operate independently but share thiol intermediates, enabling redistribution of molecular components in response to environmental changes. Transient variations in pH or temperature alter the system's connectivity, driving shifts in its final steady-state composition. Notably, the system encodes information about the nature and timing of these disturbances, which persists even after the external stimuli are removed. This “chemical memory” is reflected in the equilibrium state reached after 24 hours, offering new insights into how dynamic systems can retain environmental information.

In this study, we developed a novel self-propulsion system using the mesoscopic state of an amphiphilic molecular layer. A benzoic acid (BA) disk and 4-stearoyl amidobenzoic acid (SABA) were used as the self-propelled object and amphiphile, respectively. The BA disk was driven by the difference in surface tension around it on the aqueous surface, and its motion was influenced by the intermolecular interactions between BA and SABA. Simultaneous Brewster angle microscopy and surface pressure versus area isotherm measurements were performed to evaluate the meso- and macroscopic states of the SABA molecular layer at different temperatures (T) in the aqueous phase. At T = 293 K and 10 ≤ A ≤ 16.8 Ų molecule⁻¹, the BA disk exhibited linear reciprocating motion due to the homogeneously distributed SABA molecular layer. Conversely, the heterogeneous distribution of SABA domains at T = 303 K and 10 ≤ A ≤ 12.6 Ų molecule⁻¹ led to ring-shaped reciprocating motion. The SABA molecular layer, which was irreversibly compressed via BA disk motion, acted as a boundary for the BA disk motion. The findings of this study should advance the programming of self-propulsion at the molecular level via the mesoscopic state.

Time-dependent properties in polymer materials can be achieved through coupling to out-of-equilibrium chemical fuel reactions that mimic biological processes. Through transient changes in bonding in polymers, transient gelation, changes in mechanical stiffness, swelling, self-healing, or self-assembly can be achieved. Recent advances in these categories are discussed. These out-of-equilibrium behaviors enable applications ranging from smart adhesives to actuators for soft robotics. However, challenges remain, including waste accumulation, bio-compatibility, and achieving functionally useful performance. Addressing these issues is essential for advancing the practical use of chemically driven polymer materials and unlocking their full potential for future technologies.

Self-organizing behaviors have long been studied in complex chemical systems involving a nonlinear chemical feedback (e. g. the Belousov-Zhabotinsky and Bray-Liebhafsky reactions). Here we explore the emergence of oscillatory dynamics by coupling simpler chemical processes, in the form of a bimolecular reaction, and natural convection (i. e. flows induced by changes in density and surface tension occurring during the reaction). We study and classify different possible scenarios based on the interplay between chemically-driven Marangoni- (surface tension induced) and buoyancy-driven (density induced) flows. This coupling can either be antagonistic, whereby both generated flows are opposing (e. g. a reaction increasing the surface tension and decreasing the density), or cooperative if both flows act in the same direction (e. g. a reaction increasing both surface tension and density). We further investigate the impact of these oscillations on the mixing and reaction rate.

Research across various disciplines shows the benefits of learning and memory for gaining functionality and improving performance. It is increasingly clear that learning and memory can be found in both physical and virtual systems, from intelligent life forms to machines, simple organisms, and even designed chemical systems. We are interested in understanding to what extent physical embodiments of these processes can be synthesized and engineered from the bottom up by using molecular components. In this perspective, we raise and attempt to answer conceptual questions about supramolecular systems as the smallest units capable of learning. We define learning as a process where a complex system of interacting components modifies itself in response to an applied stress or stimulus, resulting in structural changes and information gain. We highlight the potential of systems chemistry and molecular networks to design systems that meet this definition by encoding, decoding, and storing information as memory within the system′s composition. Understanding the physical basis of molecular memory and learning could inform the development of materials and chemical systems that autonomously acquire new properties in response to their environment. This could also provide insights for next-generation computing and physical, rather than virtual, learning systems.