Physisorption is an effective route to meet hydrogen gas (H) storage and delivery requirements for transportation because it is fast and fully reversible under mild conditions. However, most current candidates have too small binding enthalpies to H which leads to volumetric capacity less than 10 g/L compared to that of the system target of 40 g/L at 298 K. Accurate quantum mechanical (QM) methods were used to determine the H binding enthalpy of 5 linkers which were chelated with 11 different transition metals (Tm), including abundant first-row Tm (Sc through Cu), totaling 60 molecular compounds with more than 4 configurations related to the different number of H that interact with the molecular compound. It was found that first-row Tm gave similar and sometimes superior van der Waals interactions with H than precious Tm. Based on these linkers, 30 new covalent organic frameworks (COFs) were constructed. The H uptakes of these new COFs were determined using quantum mechanics (QM)-based force fields and grand canonical Monte Carlo (GCMC) simulations. For the first time, the range for the adsorption pressure was explored for 0-700 bar and 298 K. It was determined that Co-, Ni-, and Fe-based COFs can give high H uptake and delivery when compared to bulk H on this unexplored range of pressure.

Usually complex charge ordering phenomena arise due to competing interactions. We have studied how such ordered patterns emerge from the frustration of a long-ranged interaction on a lattice. Using the lattice gas model on a square lattice with fixed particle density, we have identified several interesting phases, such as a generalization of Wigner crystals at low particle densities and stripe phases at densities between ρ=1/3 and 1/2. These stripes act as domain walls in the checkerboard phase present at half-filling. The phases are characterized at zero temperatures using numerical simulations, and mean field theory is used to construct a finite temperature phase diagram.

Mn‐based hexacyanoferrate (Mn‐HCF) cathodes for Na‐ion batteries usually suffer from poor reversibility and capacity decay resulting from unfavorable phase transitions and structural degradation during cycling. To address this issue, the high‐entropy concept is here applied to Mn‐HCF materials, significantly improving the sodium storage capabilities of this system via a solid‐solution mechanism with minor crystallographic changes upon de‐/sodiation. Complementary structural, electrochemical, and computational characterization methods are used to compare the behavior of high‐, medium‐, and low‐entropy multicomponent Mn‐HCFs resolving, to our knowledge for the first time, the link between configurational entropy/compositional disorder (entropy‐mediated suppression of phase transitions, etc.) and cycling performance/stability in this promising class of next‐generation cathode materials.

Graphene is inherently sensitive to vicinal dielectrics and local charge distributions, a property that can be probed by the position of the Dirac point in graphene field‐effect transistors. Exploiting this as a useful sensing principle requires selectivity; however, graphene itself exhibits no molecule‐specific interaction. Complementarily, metal–organic frameworks can be tailored to selective adsorption of specific molecular species. Here, a selective ethanol sensor is demonstrated by growing a surface‐mounted metal–organic framework (SURMOF) directly onto graphene field‐effect transistors (GFETs). Unprecedented shifts of the Dirac point, as large as 15 V, are observed when the SURMOF/GFET is exposed to ethanol, while a vanishingly small response is observed for isopropanol, methanol, and other constituents of the air, including water. The synthesis and conditioning of the hybrid materials sensor with its functional characteristics are described and a model is proposed to explain the origin, magnitude, and direction of the Dirac point voltage shift. Tailoring multiple SURMOFs to adsorb specific gases on an array of such devices thus generates a versatile, selective, and highly sensitive platform for sensing applications.