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Glass formation in Zeolitic Imidazolate Frameworks (ZIFs) has garnered significant attention in the field of Metal-Organic Frameworks (MOFs) in recent years. Numerous works have been conducted to investigate the microscopic mechanisms…
Prediction of properties from composition is a fundamental goal of materials science and can greatly accelerate development of functional materials. It is particularly relevant for ferroelectric perovskite solid solutions where…
Metal-organic Frameworks (MOFs) have emerged as potential candidates for direct air capture (DAC) of green house gases and water. Thermal properties of MOFs, such as their heat capacity, are used to determine the energy penalty associated…
Mg-based alloys are industrially used for structural applications, both as solid solutions alloys and as composites containing intermetallic compounds. However, a further development in terms of mechanical properties requires the…
Water absorption in the metal-organic framework (MOF) material Cu-BTC, up to a concentration of 3.5 H$_2$O per Cu ion, is studied via density functional theory at the meta-GGA+U level. The stable arrangements of water molecules show chains…
A number of metal-based nanopowders such kinds as Fe, Co, Fe/Co alloy, Fe/C, Fe/organic shell were successfully produced by aerosol synthesis method. The mechanism of nanoparticles formation and the influence of experimental parameters on…
High-order harmonic generation (HHG) is a powerful tool for probing electronic structure and ultrafast dynamics in matter. Traditionally studied in atomic and molecular gases, HHG has recently been extended to condensed matter, enabling…
Despite the highly porous nature with significantly large surface area, metal organic frameworks (MOFs) can be hardly used in electronic, and optoelectronic devices due to their extremely poor electrical conductivity. Therefore, the study…
Hybrid organic-inorganic materials enable systematic structural tuning through chemical modification of organic ligands. Predictive control, however, requires mechanistic understanding of how ligand chemistry and inorganic frameworks…
Machine learning potentials (MLPs) developed from extensive datasets constructed from density functional theory (DFT) calculations have become increasingly appealing for many researchers. This paper presents a framework of polynomial-based…
Van der Waals (vdW) materials provide a platform to study and control the physical properties of low-dimensional materials. While strategies developed for two-dimensional (2D) crystals are not directly transferable to one-dimensional (1D)…
The removal of leaked radioactive iodine isotopes in humid environments holds significant importance in nuclear waste management and nuclear accident mitigation. In this study, high-throughput computational screening and machine learning…
In metal-organic-framework (MOF) perovskites, both magnetic and ferroelectric orderings can be readily realized by compounding spin and charge degrees of freedom. The hydrogen bonds that bridge the magnetic framework and organic molecules…
Machine Learning (ML) plays an increasingly important role in the discovery and design of new materials. In this paper, we demonstrate the potential of ML for materials research using hard-magnetic phases as an illustrative case. We build…
Metallic structures interacting with electromagnetic fields are known to exhibit properties similar to those found in atoms and molecules, such as multi-photon and tunnel ionization. Developing this similarity beyond the electron emission…
Metal-organic frameworks (MOFs) stand as a promising chemically-active host scaffold for the encapsulation of functional guests, because they could enhance luminescent properties by molecular separation of fluorophores in the nanoscale…
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…
Deep generative models have shown promise for modeling metal-organic frameworks (MOFs), but existing approaches (1) rely on coarse-grained representations that assume fixed bond lengths and angles, and (2) neglect the MOF-adsorbate…
Machines enabled the Industrial Revolution and are central to modern technological progress: A machine's parts transmit forces, motion, and energy to one another in a predetermined manner. Today's engineering frontier, building artificial…
A deep understanding of kinematic structures and movable components is essential for enabling robots to manipulate objects and model their own articulated forms. Such understanding is captured through articulated objects, which are…