Enhanced validation of small-molecule ligands and carbohydrates in the Protein Data Bank
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We report a systematic study of small silver clusters, Agn, Agn+, and Agn–, n = 1–7. We studied all possible isomers of clusters with n = 5–7. We tested 42 exchange–correlation functionals, and we assess these functionals for their accuracy in three respects: geometries (quantitative prediction of internuclear distances), structures (the nature of the lowest-energy structure, for example, whether it is planar or nonplanar), and energies. We find that the ingredients of exchange–correlation functionals are indicators of their success in predicting geometries and structures: local exchange–correlation functionals are generally better than hybrid functionals for geometries; functionals depending on kinetic energy density are the best for predicting the lowest-energy isomer correctly, especially for predicting two-dimensional to three-dimenstional transitions correctly. The accuracy for energies is less sensitive to the ingredient list. Our findings could be useful for guiding the selection of methods for computational catalyst design.
We recently proposed the dipole-quadrupole (DQ) method for transforming adiabatic electronic states to diabatic states by using matrix elements of the dipole and quadrupole operators, and we applied the method to 3-state diabatizations of LiH and phenol. Here we extend the method to also include the electrostatic potential, and we call the resulting method the DQΦ method, which denotes the dipole–quadrupole–electrostatic-potential diabatization method. The electrostatic potential provides extra flexibility, and the goal of the present work is to test and illustrate the robustness of the methods for producing diabatic potential energy curves that tend to the adiabatic curves away from crossings and avoided crossings and are smooth in regions of crossings and avoided crossings. We illustrate the generality of the methods by an application to LiH with four states and by two-state diabatizations of HCl, (H{sub 2}){sub 2}, O{sub 3}, and the reaction Li + HF → LiF + H. We find that—if enough states are included—the DQ method does not have a significant dependence on the parameter weighting the quadrupole moment, and a geometry-independent value of 10 a{sub 0}{sup −2} is adequate in all cases tested. We also find that the addition of the electrostatic potential improves the diabatic potentials in some cases and provides an additional property useful for increasing the generality of the method for diabatization.
The electronic structural and phonon properties of Na 2-α M α ZrO 3 (M ¼ Li,K, α = ¼ 0.0,0.5,1.0,1.5,2.0) are investigated by first-principles density-functional theory and phonon dynamics. The thermodynamic properties of CO 2 absorption and desorption in these materials are also analyzed. With increasing doping level α, the binding energies of Na 2-α Li α ZrO 3 are increased while the binding energies of Na 2-α K α ZrO 3 are decreased to destabilize the structures. The calculated band structures and density of states also show that, at the same doping level, the doping sites play a significant role in the electronic properties. The phonon dispersion results show that few soft modes are found in several doped configurations, which indicates that these structures are less stable than other configurations with different doping levels. From the calculated relationships among the chemical-potential change, the CO 2 pressure, and the temperature of the CO 2 capture reactions by Na 2-α M α ZrO 3 , and from thermogravimetric-analysis experimental measurements, the Li- and K-doped mixtures Na 2-α M α ZrO 3 have lower turnover temperatures (T t ) and higher CO 2 capture capacities, compared to pure Na 2 ZrO 3 . The Li-doped systems have a larger T t decrease than the K-doped systems. When increasing the Li-doping level α, the T t of the corresponding mixture Na 2-α Li α ZrO 3 decreases further to a low-temperature range. However, in the case of K-doped systems Na 2-α K α ZrO 3 , although doping K into Na 2 ZrO 3 initially shifts its T t to lower temperatures, further increases of the K-doping level α causes T t to increase. Therefore, doping Li into Na 2 ZrO 3 has a larger influence on its CO 2 capture performance than the K-doped Na 2 ZrO 3 . Compared with pure solidsM 2 ZrO 3 , after doping with other elements, these doped systems’ CO 2 capture performances are improved.
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Penetration of solar photovoltaic (PV) installations into the grid has increased in recent years. In the past, photovoltaic installations have not included grid-support functionality. Grid support functions including Volt-VAR (VVAR), Frequency-Watt (FW), Volt-Watt (VW), frequency/voltage-ride through, as well as other inverter functions such as anti-islanding are recommended by standards such as IEEE 1547 to allow PV inverters to contribute to acceptable operation and stability of distribution systems with high penetrations of PV and to ensure predictable response of the PV inverters. First, low-level and high-level grid support inverter control functions were developed and tested in simulation. The developed controller is able to integrate advanced controller functions in a coordinated approach, avoiding any conflict between the different control objectives. The algorithms were then programmed on an off-the-shelf embedded controller that included a dual-core CPU and FPGA. The details of the high-level grid support function and the lower level switching control will be presented. Second, this programmed controller is tested using a controller-hardware-in-the-loop (CHIL) test bed setup using an FPGA-based real-time simulator. The CHIL setup has the capability to run at a 500 nano-second time-step to accommodate the 20 kHz switching frequency of the developed controller. The advanced control function and CHIL test bed details provided here will aide future researchers to design, implement, and test advanced inverter functions for PV inverters.
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The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.
An experiment was conducted to examine color preference specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied color rendition conditions designed to meet or not meet previously proposed color preference specification criteria using ANSI/IES TM-30-18 Rf, Rcs,h1, and Rg. The color rendition conditions did not meet the criterion for none, one, two, or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects’ color appearance on eight-point scales for saturated-dull, normal-shifted, and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that color preference criteria could be adjusted slightly to improve performance, with Tier A having Rf = 78, Rg = 95, and -1% = Rcs,h1 = 15%, Tier B having Rf = 74, Rg = 92, and -7% = Rcs,h1 = 19%, and Tier C having Rf = 70, Rg = 89, -12% = Rcs,h1 = 23%. A companion regression analysis shows models based on Rf, Rg, and Rcs,h1 were superior in predicting color preference compared to those using other measures of color rendition.
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