Molecular Systems Design & Engineering最新文献

Feedback through enzyme reactions creates new possibilities for the temporal programming of material properties in bioinspired applications, such as transient adhesives; however, there have been limited attempts to model such behavior. Here, we used two antagonistic enzymes, urease in watermelon seed powder and esterase, to temporally control the gelation of a poly(vinyl alcohol)–borate hydrogel in a one-pot formulation. Urease produces base (ammonia), and esterase produces acid (acetic acid), generating a pH pulse, which was coupled with reversible complexation of PVA. For improved understanding of the pulse properties and gel lifetime, the pH profile was investigated by comparison of the experiments with kinetic simulations of the enzyme reactions and relevant equilibria. The model reproduced the general trends with the initial concentrations and was used to help identify conditions for pulse-like behaviour as the substrate concentrations were varied.

The bioinspired co-precipitation of magnetite nanoparticles (MNP) using additives to tailor particle shape is an attractive alternative to the currently favoured environmentally unsustainable methods of producing shape-controlled particles. In particular, ethylenediamine based additives are able to produce MNP with high-yield under environmentally friendly conditions, yet with the desired control over particle attributes. The effect of tetraethylenepentamine (TEPA) as an additive in the room-temperature co-precipitation (RTCP) of magnetite has been investigated in an iterative Design of Experiments (DoE) strategy, utilising Full Factorial Designs (FFD) and a Path of Steepest Ascent (PSA) optimisation through three consecutive designs. Considering the ferric ratio (Fe³⁺/Fe²⁺), Fe/additive ratio, and timepoint of additive addition as factors, the percentage of isotropic faceted particles and saturation magnetisation were measured as responses. After an initial scouting FFD, timepoint of additive addition was found to be insignificant as a factor. A second FFD followed by a PSA optimisation found higher Fe³⁺/Fe²⁺ ratios of 0.6, closer to the ideal 2 : 1 stoichiometric ferric ratio produced a higher shape response (an increase in isotropic faceted particles). The interaction between ferric and Fe/additive ratio was found to be significant, as the same level of additive concentration was not as effective at lower ferric ratios. An optimum Fe/additive ratio of 50 : 1 was established, alongside the higher ferric ratio of 0.6 to produce ∼90% isotropic faceted particles with a high magnetism of 77 emu g⁻¹, showing it is possible to synthesise MNP which are both highly magnetic and highly faceted. Since it is a requirement of many industries to use homogeneous particles, the predictive synthesis of these magnetite nanoparticles is a significant step towards the industrial production of green magnetite nanoparticles. These conditions can be utilised for further synthesis or as a basis for further optimisation of shape-tuned magnetite nanoparticle syntheses. This DoE strategy enabled the optimisation of two responses simultaneously to produce high quality MNP.

In recent years, metal–organic frameworks (MOFs) have attracted much attention due to their unique structures. With their low density, high porosity and mechanical flexibility, MOFs have great potential in the field of lubrication. This paper reviews the research progress of MOFs in the field of lubrication, systematically introduces the application of MOFs as lubricant additives and the lubrication mechanism, and also summarizes and discusses the application of MOFs in a non-liquid environment and the research findings of its super-lubrication. This review summarizes the major research of MOFs in the field of lubrication in recent years, with a view to providing assistance to relevant researchers and promoting the development of this field.

Retrosynthesis is the process of designing chemical pathways from a set of reactants to a set of desired products. However, when both the pools of potential reactants and products grow to a substantial size, this becomes infeasible without the aid of computational tools. This work uses Pickaxe, an automated network generation tool, to perform computational retrosynthesis on a pool of 297 bioprivileged candidate molecules as reactants and 44 003 potential corrosion inhibitors that were generated by a variational autoencoder. Unlike typical approaches in computational synthesis planning, the use of automated network generation allows flexibility in pathways and starting material beyond those that are documented. This work starts by replicating known pathways to corrosion inhibitors from a single bioprivileged candidate molecule and applying the constituent reaction families to the entirety of the reactant pool and concludes by generating networks with a more extensive reaction family list and two sets of co-reactants, or “helper molecules”. Network size, both from the perspective of total reactions enacted and total products formed, was analyzed.

Light-activated synthetic organic molecular motors are emerging as an excellent prospect to actuate supramolecular assemblies such as polymersomes with spatiotemporal precision. The influence on these materials depends on the motor's frequency of rotation and concentration. Therefore, we determined the rotation frequency of a motor in a poly(dimethyl siloxane)-b-poly(ethylene glycol) (PDMS₁₃-b-PEG₁₃) polymersome and compared it to the frequency observed in different organic solvents. Using UV-vis spectrophotometry and nuclear magnetic resonance spectroscopy, we measured the rate of the thermal helix inversion step, which is the rate-determining step of the rotary cycle, and obtained the activation parameters. We found that the investigated motor's frequency of rotation did not significantly change in the polymersomes and remains at around 1 mHz. Moreover, dynamic light scattering results indicate that the rotation of the motors does not cause a significant change in the structure of this type of polymersome when used at a diblock copolymer : motor molar ratio of up to 100 : 2. Our findings provide a first insight into the effect of the polymersome on the motor's frequency of rotation and vice versa. Enhancing the polymersome composition with motors can lead to novel concepts, including light-activated nanopharmaceuticals, nanoreactors, and biomimetic artificial organelles and cells.

With increasing concerns over antimicrobial resistance worldwide, antimicrobial peptides (AMPs) can be a potential alternative to conventional antibiotics. Generating new AMPs is challenging as there can be enormous combinations of amino acid residues leading to a vast number of possibilities. To alleviate this hurdle, a computer-aided AMP design framework is proposed in this study. Statistical analysis was performed to identify various physicochemical properties that characterize AMPs and their respective median values were used as design targets. A genetic algorithm (GA)-based optimization approach was formulated to design AMPs with maximum antimicrobial activity for any given peptide length. The peptide sequences generated in each generation of GA were first screened using a support vector machine-based antimicrobial activity classifier. A fitness function that measures the proximity of physicochemical property values to their respective design targets was then evaluated for all sequences classified as AMPs. Based on fitness scores, a new population of peptide sequences was generated by GA. The sequence with the maximum value of fitness function was finally reported as the optimal AMP. The performance of this framework was accessed using several case studies. Results obtained from this framework corroborated well with the findings reported in the literature. Thus, the proposed optimization-based design framework can be used to generate new AMP sequences. We have also developed an easy-to-use executable version of the proposed framework that can be accessed freely.

In this work, we have investigated the sensing ability of four organic semiconductors namely, H₂TPPCOOH and ZnTPPCOOH porphyrins, H₂Pc and FePc phthalocyanines for the detection of 16 different volatile organic compounds (VOCs) through first-principles density functional theory (DFT) calculations. We have calculated various electronic properties of VOCs and organic molecules such as HOMO–LUMO, dipole moment, and global reactivity descriptors. The reactivity of VOCs mainly depends on the LUMO and the orbital energy gap. Similarly, the prime descriptors that are needed for understanding the organic molecules are softness, electrophilicity, and HOMO values. Most of the VOCs are physisorbed on the organic molecules. Few VOCs like ammonia (−1.42 eV) and acetonitrile (−1.21 eV) are chemisorbed on FePc with strong adsorption energies. H₂Pc has better adsorption to diethylene glycol (−0.24 eV). H₂TPPCOOH and ZnTPPCOOH show good binding affinity towards ammonia (−0.42 and −0.50 eV). Furthermore, the chemiresistive sensing properties of the sensors have revealed that H₂Pc is sensitive and selective towards diethylene glycol, a potential pollutant that causes renal failure. FePc is sensitive towards all 16 VOCs and hence, it can be used as a universal sensor. Also, it can be used as a single-time sensor due to its strong chemisorption towards VOCs. H₂TPPCOOH is highly sensitive to triethylamine and ZnTPPCOOH has high sensitivity to ammonia. Both triethylamine and ammonia cause severe respiratory diseases. Being a powerful tool, the DFT investigations have yielded results that are well-matched with the previously reported experimental works. In summary, we believe that our computational investigations will be useful to build sensor devices composed of highly sensitive and selective porphyrins and phthalocyanines for sensing VOCs from various sources in and around us.

Rubber materials possess remarkable properties, rendering them indispensable in numerous sectors including national defense, military industry, healthcare and automotive tire manufacturing. Consequently, they hold significant importance as engineering materials. This study employs all-atom molecular dynamics simulation to comprehensively investigate the static and dynamic characteristics of pure rubber systems, rubber/SiO₂ nanocomposite systems and crosslinked rubber systems, focusing on natural rubber (NR), butadiene rubber (BR) and styrene–butadiene rubber (SBR) under varying pressure and temperature conditions. Our findings reveal a strongly positive correlation between the glass transition temperature (T_g) and pressure. It was observed that with every 100 atm increase in pressure, T_g experienced a rise of approximately 2–3 K. Moreover, the thermal expansion coefficient (TEC) of rubber systems in the glassy state is lower than that in the rubbery state and experiences reduction as pressure intensifies or with the introduction of SiO₂ nanoparticles and crosslinking. Additionally, the study investigates the P–V–T relationship and bulk modulus of diverse rubber systems, establishing that elevated pressure or reduced temperature leads to an enhancement in the isothermal bulk modulus. Further, as temperature escalates or pressure diminishes, the mean square displacement (MSD) of all the rubber systems displays an upward trend, indicative of augmented molecular chain mobility. However, the incorporation of SiO₂ nanoparticles or the implementation of crosslinking serves to impede the mobility of rubber chains. Evaluations of the mechanical properties of the rubber systems indicate that elevated temperature results in a reduction in the tensile strength. Notably, a comparison of the mechanical properties across different rubber systems demonstrates that NR exhibits the highest tensile strength, while BR exhibits the lowest. In conclusion, this work systematically explores the intricate interplay between the structure, dynamics and mechanics of distinct rubber materials induced by pressure and temperature, providing valuable theoretical guidance for the design and fabrication of rubber materials under extreme conditions.

Stimulus-switchable Pickering emulsions have been widely researched in recent years, and the use of CO₂ as an interesting stimulus has been of special interest. However, CO₂-switchable MOF-based Pickering emulsions have rarely been reported, although they are important in applications in interfacial catalysis, the synthesis of nanoparticles, and crude oil transport. In this study, a new class of amidine-modified ZIF-90 was developed through a post-synthesis functionalization, and then employed to build CO₂-switchable Pickering emulsions. The results showed that the amidine-modified ZIF-90 was capable of emulsifying cyclohexane–water mixtures to fabricate stable emulsions at no less than 0.35 wt% content. Once CO₂ was added at a normal pressure and temperature, the Pickering emulsion was found to undergo a switch from the emulsifying to the demulsifying state. Through combining various spectroscopic methods, it was revealed that the mechanism for this phase switching originated from the reaction of amidine and CO₂ on the ZIF-90, as well as the production of hydrophilic salts. When CO₂ was driven out, the Pickering emulsion was reconstructed via a reverse reaction. By applying the emulsion as a micro-reactor, an efficient and controllable Knoevenagel condensation reaction was obtained, wherein amidine-modified ZIF-90 was employed as the catalyst and controller for the reaction.

Amorphous polymers are considered promising materials for separation applications due to their excellent transport properties and low fabrication costs. The separation performance of a polymer membrane is characterized by its permeability and selectivity. Both permeability and selectivity are controlled by the diffusion of penetrants through the matrix, which is strongly influenced by the distribution and morphology of the free volume elements (FVEs). FVEs are void spaces in the polymer matrix that result from the inefficient packing of bulky and rigid groups on the polymer backbone. Thus, FVEs dictate the efficiency of membrane polymers, and it is imperative to understand how processing conditions such as high pressures and temperatures influence their structure. In this work, we apply uniaxial tensile deformation on three polymers, polystyrene (PS), polymethylpentene (PMP), and HAB-6FDA thermally rearranged polymer (TRP), at varying temperatures and strain rates. We characterize the stress strain behavior, tensile modulus, and free volume element evolution at these conditions. We find that PMP and PS with low and moderate glass transition temperature, respectively, exhibit the most change in mechanical properties as a function of strain rate and temperature. The properties of TRP, however, do not vary as much, which we attribute to the rigidity of the chains. We also find that FVEs shift to broader distributions with deformation, and the extent of this change is in line with the overall change of mechanical properties of the material.