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Metal-organic frameworks (MOFs) have emerged as promising materials for carbon capture applications due to their high CO2 capacities and tunable properties. Amongst the many possible MOFs, metal-substituted compounds based on M-DOBDC and…
Separation of hydrocarbons is one of the most energy demanding processes. The need to develop materials for the selective adsorption of hydrocarbons, under reasonable conditions, is therefore of paramount importance. This work unveils…
Universal machine learning interatomic potentials (uMLIPs) have emerged as powerful tools for accelerating atomistic simulations, offering scalable and efficient modeling with accuracy close to quantum calculations. However, their…
Metal-organic frameworks (MOFs) are promising materials for methane capture due to their high surface area and tunable properties. Metal substitution represents a powerful strategy to enhance MOF performance, yet systematic exploration of…
Metal-organic frameworks (MOFs) can be exceptionally good catalytic materials thanks to the presence of active metal centres and a porous structure that is advantageous for molecular adsorption and confinement. We present here a…
Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generative power of…
A variety of optimization algorithms have been developed to solve engineering design problems in which the solution space is too large to manually determine the optimal solution. The Modular Optimization Framework (MOF) was developed to…
Metal organic framework (MOF) materials have attracted a lot of attention due to their numerous applications in fields such as hydrogen storage, carbon capture, and gas sequestration. In all these applications, van der Waals forces dominate…
Compositionally engineered metal-organic frameworks (MOFs) have been designed and used to fabricate ultrafast scintillating films with emission in both the UV and visible regions. The inclusion of hafnium (Hf) ions in the nodes of the MOF…
Using density functional theory (DFT), we investigate mechanical properties of a few 2D metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs) having Dirac and flat bands. These porous materials have become a subject of…
Metal-organic frameworks (MOFs) provide a versatile and tailorable material platform that embody many desirable attributes for photocatalytic water-splitting. The approach taken in this study was to use Density Functional Theory (DFT) to…
Monolithic metal-organic frameworks (MOFs), which have a continuous structure composed of small primary MOF particles and amorphous networks, are demonstrated to possess larger pore volume and thus better larger gas uptake capacity compared…
The zeolitic imidazolate frameworks (ZIF) have emerged as a promising candidate for catalysis, carbon-dioxide (CO$_{2}$) capture and storage as well as flue gas separation due to their tunable porosity and chemical stability. ZIFs consists…
Physisorption of hydrogen molecules in metal-organic frameworks (MOFs) provides a promising way for hydrogen storage, in which the van der Waals (vdW) interaction plays an important role but cannot described by the density functional theory…
The design of functional materials with desired properties is essential in driving technological advances in areas like energy storage, catalysis, and carbon capture. Generative models provide a new paradigm for materials design by directly…
Even micromachines with tailored functionalities enable targeted therapeutic applications in biological environments, their controlled motion in biological media and drug delivery functions usually require sophisticated designs and complex…
Understanding how gas mixtures diffuse and distribute within porous frameworks is central to designing advanced separation and storage materials. Here, we investigate the transport and spatial distribution of binary gas mixtures in a porous…
This research was focused on the efficient collection of experimental Metal-Organic Framework (MOF) data from scientific literature to address the challenges of accessing hard-to-find data and improving the quality of information available…
Large language models have demonstrated remarkable reasoning capabilities across diverse natural language tasks. However, comparable breakthroughs in scientific discovery are more limited, because understanding complex physical phenomena…
Navigation by scent is a capability in robotic systems that is rising in demand. However, current methods often suffer from ambiguities, particularly when robots misattribute odours to incorrect objects due to limitations in olfactory…