Molecular Systems Design & Engineering最新文献

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.

Responsive shape-changing materials with driven and spontaneous transitions have wide applications in biological systems, soft robots, artificial muscles, and consumer products. Among different shape-morphing materials, liquid crystal elastomers (LCEs) have recently emerged as a promising type of material for their ability to undergo large, reversible strains and to generate programmable deformation modes in response to external stimuli, such as temperature change, light stimulation, or humidity change. Existing research on LCE deformations usually assume a flat or an undeformed shape as the initial configuration, which morphs into a targeted nontrivial shape when external stimuli are applied. Here, we use continuum simulation to explore the deformation of pre-shaped LCE strips to analyze how the initial shape geometry can be used to tune the shape-morphing behaviors of LCEs. We first validate our simulation method by successfully reproducing the deformations of a thin strip of LCE with two well-studied director fields, i.e., a splay–bend director and a twist director along the thickness direction, respectively. We next consider nontrivial combinations of different pre-shapes and different director fields to study the thermo-mechanical response of an LCE strip. Specifically, we pre-bend an otherwise flat LCE strip along its short axis, long axis, and an off-axis direction, and study its deformations assuming a twist director field. We find that pre-bending along the short axis can facilitate the LCE strip to transition from a helicoid into a spiral ribbon, and an off-axis pre-bent LCE strip can form a tubule more easily than its flat counterpart. For a pre-twist LCE strip, we find that its deformed shape preserves the handedness of the initial twist. For a constrained pre-bent LCE strip, it can spontaneously break the symmetry of the initial shape by bending toward one side. Taken together, we have systematically studied the interplay between the initial shape and the director field of an LCE strip, and our work implies that pre-deformation can be an effective parameter to control the shape-morphing behaviors of LCEs.

The three-dimensional microstructures of a dilute suspension of magnetic Janus colloids with a magnetic dipole laterally displaced from their center were studied using Brownian dynamics simulations. The microstructure and aggregation properties were obtained from the temporal evolution of the positions and orientations of the colloidal particles. The mean average cluster size, the nucleation and growth process, the cluster size distribution, the orientational distribution, and the effective radius of the clusters were evaluated for different values of Janus balance, i.e., the lateral dipolar shift (s)—dimensionless with the particle radius and taking values in the range of 0 ≤ s ≤ 1. At small dipolar shifts (s → 0), chain- and ring-shaped structures are formed that are typically observed in particles with a centered dipole (s = 0). However, at intermediate dipolar shifts (0.2 ≤ s ≤ 0.4), structures mainly form vesicles that in some cases coexist with rings and spherical micelles. Finally, for s > 0.4, spherical micelles are observed that progressively decrease in size as s increases until clusters of 2 or 3 particles are reached. For intermediate and high dipolar shifts, the typical power-law aggregation is broken down, and the system saturates to a few particles per cluster. Therefore, the observed structural behavior could allow the better design of drug delivery encapsulation materials or, in turn, suspensions designed with high stability. This study suggests that new magnetic fluids can be designed by controlling the dipolar displacement of their component particles thereby influencing their microstructure and consequent macroscopic properties.

Nanotechnology-enhanced soft materials, ranging from polymers and gels to bio-based composites, offer improved functionality and durability across diverse sectors. As their use grows, assessing their environmental sustainability within the circular economy framework is critical. This study applies life cycle assessment (LCA) to evaluate the environmental impacts of these materials across production, use, and end-of-life stages. Findings reveal that while nanomaterials often incur high production impacts, especially in energy use and toxicity, their enhanced performance can offset these burdens during use. Green synthesis, renewable energy, and design-for-environment strategies show promise in reducing lifecycle impacts. This is the first conceptual review that systematically maps nanomaterial design features, such as synthesis routes, surface properties, and morphologies, to environmental performance metrics including energy use, toxicity, and end-of-life behavior. This study uniquely integrates a keyword co-occurrence analysis using the PRISMA methodology to identify thematic research clusters and underexplored intersections between nanotechnology, life cycle analysis, and circular economy. The network and density visualization maps provide further critical insights into the existing knowledge paving the path towards identification of underexplored keywords. By combining bibliometric analysis with design-performance mapping, this work pioneers a novel framework to guide future interdisciplinary research and sustainability assessments in the field. However, methodological gaps in LCA, such as the lack of nano-specific data and characterization factors, hinder comprehensive assessment. The study emphasizes the need for improved LCA models, stakeholder collaboration, and innovation management to support the sustainable integration of nanotechnology in circular value chains.

Uncontrolled ice formation poses a significant problem in various industries from atmospheric physics to cryobiology. Therefore, ice controlling strategies including regulating ice nucleation and controlling ice recrystallization and growth are highly pursued. In nature, antifreeze proteins (AFPs) exist in many cold-acclimated species, which can effectively control the size and shape of ice crystals, thus minimizing the deleterious effects of ice. Understanding how nature has evolved AFPs to adapt organisms to cold environments is crucial for guiding the design of novel antifreeze materials by human beings. Herein, we critically reviewed the evolutionary models underlying the development of AFPs, including escape from adaptive conflict (EAC) (primarily involving type III AFPs and Antarctic antifreeze glycoproteins, AFGPs), de novo evolution (exemplified by Arctic codfish AFGPs), horizontal gene transfer (HGT) (represented by type II AFPs and the DUF3494 family), and convergent evolution (predominantly involving type I AFPs and AFGPs). Furthermore, strategies for designing and fabricating bio-inspired antifreeze materials that mirror these evolutionary processes are also discussed. We anticipate that the insights presented here will inspire and aid in the identification of material design strategies for the future development of novel antifreeze materials.

Luminol and its derivatives have emerged as powerful chemiluminescent agents with broad applications in biomedical diagnostics, forensic science, and environmental monitoring. Despite their widespread use, luminol's limitations, including poor solubility, short luminescence duration, and sensitivity to environmental conditions, have driven extensive research into the synthesis of more efficient derivatives. This concise review presents recent advances in the molecular engineering of luminol derivatives, focusing on design strategies that employ electronic modulation (e.g., introduction of electron-donating or withdrawing substituents) and steric tuning (e.g., alkylation and ring substitutions) to optimize its chemiluminescence efficiency, kinetics, emission wavelength, solubility, stability, and applicability for specific environments (e.g., biological systems). The review also discusses how these structural modifications impact luminol's performance within integrated systems, including forensics, bioimaging platforms, immunoassay technologies and microfluidic sensors, thereby linking molecular-level design with macroscopic function. Emerging macromolecular and polymer-based luminol systems, such as those incorporating hydrophilic carriers, nanoparticles, enzyme-responsive linkers, surface-immobilized polymer brushes, and multi-functional hybrid platforms, are also highlighted for their potential to overcome solubility and biocompatibility barriers while enabling targeted delivery or signal amplification. Finally, key challenges and future perspectives are outlined, including the development of near-infrared-emitting derivatives, improved storage stability, and interdisciplinary strategies for translating luminol chemistry into next-generation diagnostics and environmental sensing platforms. By summarizing these advancements, this review underscores the evolving role of luminol chemistry in modern analytical science and its potential to revolutionize next-generation detection technologies.

The parameterisation of the force field of a molecular system is essential for accurately describing and predicting macroscopic thermophysical properties. Here, we discuss three approaches to obtain the molecular parameters (σ, ε, and λ_r) of the Mie force field from experimental data for quasi-spherical molecules. The first approach is based on a classical strategy that considers fitting only to vapour–liquid equilibria data. The second approach entails a simultaneous fit to equilibrium properties and liquid shear viscosity. Finally, a third approach incorporates solid–fluid equilibrium data. The fitting procedure is facilitated by the use of recently published machine-learned equations of state for the Mie particle, which allows the prediction of thermophysical properties given a set of molecular parameters. The goodness-of-fit is assessed based on the deviations between calculated and experimental data. We also assess the behaviour of the thermal conductivity and speed of sound of the saturated liquid phase to evaluate the transferability of the molecular parameters to properties not used in the parametrisation. Apart from the singular case of monoatomic molecules, no single set of parameters can simultaneously describe the fluid phase equilibria, transport, and solid transition properties of quasi-spherical molecules. This result highlights the limitations of the Mie potential for modelling the thermophysical properties of small molecules. Therefore, a compromise must be made, either to achieve a good description of a specific set of properties or to attain modest accuracy across all phase space.

Using a modified phase field crystal model that we have recently introduced [Weigel et al., Modelling and Simulation in Materials Science and Engineering, 2022, 30, 074003], we study grain boundaries that occur in two-dimensional structures composed of particles with preferred binding angles like patchy colloids. In the case of structures with a triangular order, we show how particles with a 5-fold rotational symmetry that differs from the usual 6-fold coordination of a particle in bulk affect the energy of the dislocations in the grain boundaries. Furthermore, for quasicrystals we find that the dislocation pairs recombine easily and the grain boundaries disappear. However, the resulting structure usually possesses a lot of phasonic strain. Our results demonstrate that the preferred symmetry of a particle is important for grain boundaries, and that periodic and aperiodic structures may differ in how stable their domain boundaries are.

This work aims at shedding light on the capture mechanisms of toxic atmospheric pollutants by zeolites. A comprehensive computational investigation has been conducted to evaluate the interaction energies of NO, NO₂, CO, CO₂, and H₂O with Fe²⁺ supporting both chabazite and mordenite zeolites using periodic density functional theory calculations. Si/Al ratio sets of {11, 5, 3} and {23, 11, 5} have been respectively chosen for chabazite and mordenite. Our findings show that both systems exhibit a thermodynamic preference for bonding NO and NO₂ over H₂O and CO₂. Moreover, ab initio molecular dynamics simulations at 300 K for the Fe-chabazite system with Si/Al = 3 confirm the adsorption of NO, NO₂ and CO even in the presence of H₂O molecules, and the radial distribution function was employed to understand how steam affects NO, NO₂ and CO bonding. CO₂ co-adsorption was eventually neglected in our study due to its low interaction energy. Finally, Bader charges and charge density differences were calculated to analyze bond elongation after adsorption and account for the regeneration of the substrate. Results show that low Si/Al ratios enhance the affinity for NO and NO₂ and favour the regenerability of the adsorbent. This study demonstrates that the utilization of zeolites containing iron as the compensating cation presents promising potential as effective adsorbents for capturing NO_x and CO in the presence of H₂O and CO₂ originating from diesel engine emissions within confined work environments.