Molecular Systems Design & Engineering最新文献

Cholesteric liquid crystals (CLCs) confined in curved geometries exhibit a rich spectrum of defect-mediated morphologies governed by the interplay between chirality, curvature, surface anchoring, and confinement. This study systematically investigates structural transitions in highly chiral CLC shells under asymmetric anchoring conditions, focusing on the effects of shell thickness and curvature on pitch axis reorientation and defect formation. Utilizing microfluidic techniques, we generate core–shell droplets with independently tunable anchoring at inner and outer aqueous interfaces. Transitioning from planar–planar to planar-homeotropic boundary conditions via surfactant-mediated modulation induces profound reorganizations in the director field, giving rise to focal conic domains (FCDs), stripe patterns, and hybrid textures. Optical microscopy reveals that thicker shells favor coherent FCD nucleation, while thinner shells exhibit asymmetric, fragmented domains due to increased spatial frustration and constrained elastic relaxation. In small-diameter shells, high curvature suppresses defect nucleation, promoting the emergence of periodic stripe textures as an energetically favorable alternative. Complementary continuum simulations based on the Landau–de Gennes framework reproduce experimental trends, highlighting anchoring energy thresholds that delineate morphological regimes and confirm the dominance of curvature in stabilizing non-defect-based modulations. The ability to engineer defect architectures and direct pitch axis orientation via geometrical and boundary condition control can open new avenues for designing responsive and reconfigurable optical materials and photonic elements.

A green synthesis method was employed to obtain cobalt ferrite nanoparticles (NPs) from orange extract in three different volumes (100, 150, and 200 mL). This provides an eco-friendly and convenient method to produce nanoparticles. The phytochemicals present in the extract act as reducing and stabilizing agents in the formation of cobalt ferrite nanoparticles. The orange extract has proved to be effective in modifying the crystallite size; a higher extract volume of orange juice produced smaller-sized crystallite nanoparticles. X-ray diffraction (XRD), simultaneous thermal analysis (STA), UV-vis absorption spectroscopy, scanning electron microscopy (SEM), and vibrating sample magnetometry (VSM) were used to characterize the effects of varying amounts of chelating agents on the morphological, structural, and optical characteristics of the produced CoFe₂O₄. FTIR analysis proved the synthesized samples' spinel structure and the force constant for the Fe–O bond was calculated to be 262.398 N m⁻¹ and for the Co–O bond was 156.047 N m⁻¹. The distribution of chemical components among the particles with varying quantities of O, Fe, and Co was determined using energy-dispersive X-ray (EDX) spectroscopy. According to the XRD analysis, the NPs' crystallite sizes range from 17 to 28 nm. The NPs' agglomerated shape and average particle size of 47–74 nm was observed by SEM. VSM studies show that the 100 mL extract-based sample exhibited the highest saturation magnetization of 65.71 emu g⁻¹. The band gap was measured using the Kubelka–Munk technique and increased from 2.261 to 2.475 eV with increasing extract volume. This study confirms that orange fruit extract can effectively synthesize nanoparticles of cobalt ferrite.

Quantum mechanical tunneling effects cannot be neglected when studying the kinetics of chemical reactions involving light atoms at low temperatures. Rate theories such as variational transition state theory with multidimensional tunneling (VTST/MT) can be computationally intensive as they need nuclear Hessian information along the entire minimum energy path (MEP) of the reaction step. We report an improved selection strategy for a small number of points on the MEP that are necessary for a low-cost reconstruction of Hessian eigenvalues via the polynomial variety-based matrix completion (PVMC) algorithm [S. J. Quiton, J. Chae, S. Bac, K. Kron, U. Mitra and S. Mallikarjun Sharada, J. Chem. Theory Comput., 2022, 18, 4327–4341]. We combine chemically informed sampling of points on the MEP that correspond to crossings between critical bond distances with a Euclidean distance-based approach that identifies points on the MEP that are most dissimilar from already sampled ones. We examine the performance of PVMC with the new sampling approach in predicting zero-curvature tunneling transmission coefficients, VTST/MT-based kinetic isotope effects (KIEs), and their trends for two possible CH activation mechanisms catalyzed by dioxo-dicopper complexes. PVMC reduces Hessian evaluations by over 58% while maintaining high predictive fidelity, offering a computationally efficient approach for quantum chemical rate predictions. While the approach is accurate for small KIEs (≤10), the prediction of very large tunneling transmission coefficients and consequently KIEs (between 10 and 60) depends very strongly on the underlying sampling strategy. PVMC also assumes an approximate polynomial structure for Hessian eigenvalues, which cannot always capture sharp changes in eigenspectra in the vicinity of the transition state. Going forward, we aim to (1) identify alternative structures to the quasi-polynomial approximation and (2) MEP characteristics in addition to bond crossings, to develop a universal sampling and matrix completion scheme for inexpensive VTST/MT calculations.

Corrosion inhibitors play a crucial role in mitigating metal degradation, yet their performance varies significantly depending on environmental conditions and application methods. This study employs a high-throughput methodology utilising volume loss measurements via optical profilometry to assess corrosion inhibitor efficiency. A comparative analysis between the droplet-on-plate and full-immersion testing methods is conducted to evaluate their impacts on inhibitor performance using optical profilometry. The research delves into the chemistry of corrosion inhibitors specifically designed for droplet corrosion, where benzothiazole derivatives performed well in both environments, whereas thiazole derivatives exhibited weaker performance under droplet conditions, whilst focusing on how pH gradients evolve within a droplet over time and influence corrosion inhibitor effectiveness. Results indicate that localised pH variations significantly alter the adsorption behaviour and stability of corrosion inhibitors, affecting their protective capabilities. Furthermore, the interactions between corrosion inhibitors and oxide layers are explored, revealing that anodic inhibitors tend to accumulate around corrosion pits, suggesting a selective protection mechanism. Those findings provide critical insights into optimising corrosion inhibitor formulations and testing methodologies for sound corrosion assessments.

Separation of carbon dioxide (CO₂) from acetylene (C₂H₂) represents a significant challenge in the petrochemical industry, primarily due to their similar physicochemical properties. By synergizing molecular simulation (MS) and machine learning (ML), in this study, we aim to discover top-performing metal–organic frameworks (MOFs) for inverse CO₂/C₂H₂ separation. Initially, the adsorption of a CO₂/C₂H₂ mixture in MOFs from the Cambridge Structural Database (CSD) is evaluated through MS, structure–performance relationships are constructed, and top-performing CSD MOFs are shortlisted. Subsequently, ML models are trained by utilizing pore geometry, framework chemistry, as well as adsorption heat and Henry's constant as descriptors. The significance of these descriptors is quantitatively assessed through Gini impurity measures and Shapley additive explanations. Finally, the transferability of the ML models is evaluated through out-of-sample predictions for CO₂/C₂H₂ separation in the computation-ready experimental (CoRE) MOFs. Notably, a handful of CoRE MOFs are found to outperform the best CSD MOFs and their performance is further compared with existing literature. The synergized MS and ML approach in this study is anticipated to accelerate the discovery of MOFs in a large chemical space for CO₂/C₂H₂ separation and other important separation processes.

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With the world swiftly evolving towards technology, the relentless quest for sustainable energy sources has garnered significant attention. Amidst the scientific advancements, triboelectric nanogenerators (TENGs) have emerged as a beacon of hope, providing a promising solution through energy generation from the ambient environment. This paper focuses on the development of a freestanding triboelectric layer (FTL) TENG for increasing output power energy by incorporating a PTFE layer. A comprehensive investigation is performed that involves mathematical modeling and COMSOL simulation of the FTL TENG. Experimentally, the novel FTL TENG is designed and fabricated using fur and PTFE/Cu electrodes. The results show a two-fold enhancement in the performance of the FTL TENG upon incorporating a PTFE layer over copper electrodes. The simulation results accurately predict voltage build up under open-circuit conditions and substantial current flow under short-circuit conditions, closely mirroring experimental results. The study also demonstrates the practicality of the FTL TENG in powering electronic devices through successful capacitor charging. This research underscores the FTL TENG's reliability as a clean and sustainable energy harvesting solution with potential applications across various fields, thereby illuminating the path towards self-powered electronic devices.

In this study, we report an investigation of the impact of molecular engineering through asymmetrical side chain substitution on the semiconducting performance of benzo[1,2-b:5,4-b′]dithiophene (BDT) derivatives in solution-processable organic field-effect transistors (OFETs). Pristine (2-(thiophen-2-yl)benzo[1,2-b:5,4-b′]dithiophene; compound 1), linear octyl-substituted (2-(5-octylthiophen-2-yl)benzo[1,2-b:5,4-b′]dithiophene; compound 2), and branched 2-ethylhexyl-substituted (2-(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:5,4-b′]dithiophene; compound 3) BDT derivatives were synthesized and characterized to evaluate the role of alkyl side chains in modulating thermal, optical, electrochemical, and charge transport properties. Despite the improved solubility and thermal stability observed for the alkylated derivatives, compound 1 without any side chains exhibited the highest field-effect mobility of up to 0.024 cm² V⁻¹ s⁻¹ and superior thin-film crystallinity. Our results demonstrate that excessive steric hindrance induced by bulky side chains can disrupt molecular packing and degrade OFET performance. This work highlights the importance of precise side chain engineering for optimizing the balance between solution-processability and charge transport in organic semiconductors.

Metal–organic frameworks (MOFs) are promising, tunable materials for hydrogen storage. For application under cryogenic operating conditions, past work has run into a ceiling on performance due to a trade-off in the volumetric deliverable capacity (VDC) versus the gravimetric deliverable capacity (GDC). In this study, we computationally constructed and screened 105 230 MOF structures based on 529 nets to explore the effect of underlying topology on the hydrogen storage performance of the resulting materials. A machine learning model was developed based on simulated hydrogen uptake to facilitate screening of the entire dataset, and it successfully identified the top 10% of materials with a root-mean-square error of approximately 1 g L⁻¹ as validated by subsequent grand canonical Monte Carlo simulations. We identified a promising structure based on the tsx topology that exhibits both VDC and GDC higher than the current benchmark material, MOF-5. Our data-driven analysis indicates that nets with higher net density yield MOFs with enhanced volumetric and gravimetric surface areas, thereby improving maximum VDC while shifting the capacity trade-off toward higher GDC.

Boron subphthalocyanines (BsubPcs) are a class of macrocycles that are often stable and straightforward to synthesize. Their optical properties such as high extinction coefficient and strong fluorescence have led to their incorporation into optoelectronic devices including OLEDs. However, the best demonstrated OLEDs using BsubPc emitters were unable to convert triplet excitons generated through applied bias into light. To address this, we fabricated OLEDs incorporating an assistant dopant into the emissive layer, 2-phenyl-4′-carbazole-9H-thioxanthen-9-one-10,10-dioxide (TXO-PhCz), capable of thermally converting triplet excitons into singlets, which are then transferred to the BsubPc emitter, a process referred to as hyperfluorescence. We also varied the axial substituent attached to the BsubPc core to determine its effect on the resulting performance. We found that the use of the TADF assistant dopant increased current efficiency up to 200% while maintaining more than 90% emission from the BsubPc in most cases. The best BsubPcs had short alkoxy axial groups, achieving an average current efficiency of 1.34 cd A⁻¹ across a luminance range of up to ∼10³ cd m⁻² using tert-butoxy BsubPc. These devices are the most efficient, and pure color OLEDs demonstrated using BsubPcs as the primary emitter at reasonable luminance outputs. These findings highlight the promise of BsubPc emitters in high-performance OLEDs when paired with a TADF assistant dopant, offering a viable route to efficient and color-pure devices.