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The catalytic properties of monometallic and bimetallic Ru and Mo phosphides were evaluated for their ability to selectively hydrogenate furfural to furfuryl alcohol. Monometallic MoP showed high selectivity (98%) towards furfuryl alcohol, while RuP and Ru 2 P exhibited lower selectivity at comparable conversion. Bimetallic promotional effects were observed with Ru 1.0 Mo 1.0 P, as the pseudo-first order reaction rate constant for furfural hydrogenation to furfuryl alcohol, k 1 , was at least 5× higher than MoP, RuP, and Ru 2 P, while maintaining a 99% selectivity. Composition-directed catalytic studies of Ru x Mo 2−x P (0.8 < x < 1.2) provided evidence that Ru rich compositions positively influence k 1 , but not the selectivity. The rate constant ratio k 1 /( k 2 + k 3 ) for furfuryl alcohol production compared to methyl furan ( k 2 ) and tetrahyrofurfuryl alcohol ( k 3 ) followed the trend of Ru 1.0 Mo 1.0 P > Ru 1.2 Mo 0.8 P > MoP > Ru 0.8 Mo 1.2 P > RuP > Ru 2 P. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was used to examine the configuration of adsorbed furfural on the synthesized catalysts, but the results were inconclusive and no correlation could be found with the selectivity due to the possible IR inactive surface modes with furfural adsorption. However, gas phase density functional theory calculations suggested the x = 1.0 material in Ru x Mo 2−x P (0.8 < x < 1.2) had the most favorable furfural adsorption energy. Experimentally, we also observed that the solvent greatly influenced both the conversion and selectivity, where isopropanol provided the highest selectivity to furfuryl alcohol. Finally, recycling experiments showed a 12% decrease in k 1 after 3 cycles without any regeneration, but the activity could be fully recovered through a re-reduction step. 

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures. 

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol⁻¹at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases. 

Catalytic hydrodeoxygenation (HDO) of phenolics is a necessary step for upgrading bio-oils to transportation fuels. Bimetallic catalysts offer the potential of increased activities and selectivities for desired products. Adding non-metallic elements, such as phosphorous, allows for charge distribution between the metal and nonmetal atoms, which improves Lewis acid character of catalytic surfaces. This work utilizes experimental and density functional theory (DFT) based calculations to identify potential C–O bond cleavage pathways and product selectivities for HDO reactions on FeMoP, RuMoP, and NiMoP catalysts. Our work demonstrates that FeMoP catalyst favors direct deoxygenation pathway due to a lower activation energy barrier for C–O bond cleavage whereas RuMoP and NiMoP catalysts promote ring hydrogenation first, followed by the cleavage of C–O bond. The Bader charge analysis indicates that for these catalytic systems Mo δ+ site bears a large positive charge which acts as a Lewis acid site for HDO reactions. Overall, we find that trends in the experimental product selectivities are in good agreement with that predicted with DFT calculations. 

Compositional variation in Fe_XMo_2−XP catalysts alters their Lewis acidities, leading to modulated catalytic performance in the hydrodeoxygenation of phenol.