Density functional theory embedding for correlated wavefunctions: Improved methods for open-shell systems and transition metal complexes

Density functional theory (DFT) embedding provides a formally exact framework for interfacing correlated wave-function theory (WFT) methods with lower-level descriptions of electronic structure. Here, we report techniques to improve the accuracy and stability of WFT-in-DFT embedding calculations. In particular, we develop spin-dependent embedding potentials in both restricted and unrestricted orbital formulations to enable WFT-in-DFT embedding for open-shell systems, and we develop an orbital-occupation-freezing technique to improve the convergence of optimized effective potential (OEP) calculations that arise in the evaluation of the embedding potential. The new techniques are demonstrated in applications to the van-der-Waals-bound ethylene-propylene dimer and to the hexaaquairon(II) transition-metal cation. Calculation of the dissociation curve for the ethylene-propylene dimer reveals that WFT-in-DFT embedding reproduces full CCSD(T) energies to within 0.1 kcal/mol at all distances, eliminating errors in the dispersion interactions due to conventional exchange-correlation (XC) functionals while simultaneously avoiding errors due to subsystem partitioning across covalent bonds. Application of WFT-in-DFT embedding to the calculation of the low-spin/high-spin splitting energy in the hexaaquairon(II) cation reveals that the majority of the dependence on the DFT XC functional can be eliminated by treating only the single transition-metal atom at the WFT level; furthermore, these calculations demonstrate the substantial effects of open-shell contributions to the embedding potential, and they suggest that restricted open-shell WFT-in-DFT embedding provides better accuracy than unrestricted open-shell WFT-in-DFT embedding due to the removal of spin contamination.Comment: 11 pages, 5 figures, 2 table

Prior Likelihoods and Space-Group Preferences of Solvates

For a range of organic solvents, the likelihood of the solvent forming solvates has been estimated using the recrystallization solvent (RS) data in the Cambridge Structural Database (CSD). Although RS data are viewed with caution by some crystallographers, most of the likelihood estimates are shown to have good precision. Strong trends are apparent in the results. For example, high likelihoods are found for aromatic solvents with electron-withdrawing substituents and low likelihoods for acyclic aliphatic hydrocarbons. Results for different CSD subsets, such as organic and metalloorganic, are highly correlated. The likelihood that a solvent will form solvates is almost always higher when the solvent is part of a mixture than when it is pure. The likelihood of two solvents forming a heterosolvate (i.e., both solvents in the structure) can be well estimated by the product of the likelihoods of the solvents forming normal solvates (i.e., only one solvent in the structure). The space-group preferences of solvates vary significantly with the nature of the cocrystallized solvent. Those of nonsolvates vary significantly with the solvent(s) from which they were crystallized. Solvents with inversion centers favor solvate crystallization in centrosymmetric space groups, and solvents with 2-fold rotational symmetry promote crystallization in space groups with 2-fold proper rotational axes. The inclusion of cyclohexane and carbon tetrachloride in a lattice can facilitate crystallization in trigonal and tetragonal space groups, respectively. Our results can: (a) guide solvent selection when solvates are undesired; (b) assist in predicting solvate formation, e.g., using Bayesian algorithms; (c) assist in the choice of space groups for solvate crystal structure prediction; and (d) suggest ways in which solvent incorporation can be used to influence space groups.</p

Dammed water quality—Longitudinal stream responses below beaver ponds in the Umpqua River Basin, Oregon

Beaver-related restoration (BRR) has gained popularity as a means of improving stream ecosystems, but the effects are not fully understood. Studies of dissolved oxygen (DO) and water temperature, key water quality metrics for salmonids, have demonstrated improved conditions in some cases, but warming and decreased DO have been more commonly reported in meta-analyses. These results point to the contingencies that can influence outcomes from BRR. We examined water quality related to beaver ponds in a diverse coastal watershed (Umpqua River Basin, OR, USA). We monitored water temperature 0–400m above and below beaver ponds and at pond surfaces and bottoms across seven study sites from June through September of 2019. DO was also recorded at two sites at pond surfaces and pond bottoms. Downstream monthly mean daily maximum temperatures were warmer than upstream reference locations by up to 1.9°C at beaver dam outlets but this heating signal attenuated with downstream distance. Downstream warming was greatest in June and July and best predicted by pond bottom temperatures. DO at pond surfaces and bottoms were hypoxic (≤5 mg/L) for more than half of the 32-day monitoring period. Water temperatures increased for short distances below monitored beaver ponds and observed oxygen conditions within ponds were largely unsuitable for salmonid fishes. These findings contrast with some commonly stated expectations of BRR, and we recommend that managers consider these expectations prior to implementation. In some cases, project goals may override water quality concerns but in streams where temperature or DO restoration are objectives, managers may consider using BRR techniques with caution

Knowledge-based vision and simple visual machines

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong

Targeting Extension Programs to Opinion Leaders Guiding Genetic Modification Discussions

Despite communication efforts developed to educate the public about genetic modification (GM) science designed to ensure consumers are making educated purchasing decisions, most consumers do not seek out information about GM science and make emotional purchasing decisions. GM supporters and opponents can also be very vocal about their opinions, having an impact on those within their social realms of influence. Using opinion leadership theory, this study sought to identify GM opinion leaders within the U.S. who consider themselves to be outspoken and a source of information for GM science. An online survey was deployed with the purpose of identifying GM opinion leaders, determining their views on GM science, identifying where they go for information, and determining how they want to learn so that Extension professionals can better serve their needs. The findings imply GM science opinion leaders are younger, white or African American men, with a high average family household income, that are well educated. The GM science opinion leaders have a slightly negative attitude toward GM and want to learn about GM science from universities researching GM science and organizations in support of GM science through online mediums. Recommendations are offered for how Extension professionals can reach this audience

Density functional theory embedding for correlated wavefunctions: Improved methods for open-shell systems and transition metal complexes

Density functional theory (DFT) embedding provides a formally exact framework for interfacing correlated wave-function theory (WFT) methods with lower-level descriptions of electronic structure. Here, we report techniques to improve the accuracy and stability of WFT-in-DFT embedding calculations. In particular, we develop spin-dependent embedding potentials in both restricted and unrestricted orbital formulations to enable WFT-in-DFT embedding for open-shell systems, and develop an orbital-occupation-freezing technique to improve the convergence of optimized effective potential calculations that arise in the evaluation of the embedding potential. The new techniques are demonstrated in applications to the van-der-Waals-bound ethylene-propylene dimer and to the hexa-aquairon(II) transition-metal cation. Calculation of the dissociation curve for the ethylene-propylene dimer reveals that WFT-in-DFT embedding reproduces full CCSD(T) energies to within 0.1 kcal/mol at all distances, eliminating errors in the dispersion interactions due to conventional exchange-correlation (XC) functionals while simultaneously avoiding errors due to subsystem partitioning across covalent bonds. Application of WFT-in-DFT embedding to the calculation of the low-spin/high-spin splitting energy in the hexaaquairon(II) cation reveals that the majority of the dependence on the DFT XC functional can be eliminated by treating only the single transition-metal atom at the WFT level; furthermore, these calculations demonstrate the substantial effects of open-shell contributions to the embedding potential, and they suggest that restricted open-shell WFT-in-DFT embedding provides better accuracy than unrestricted open-shell WFT-in-DFT embedding due to the removal of spin contamination

Accurate basis set truncation for wavefunction embedding

Density functional theory (DFT) provides a formally exact framework for performing embedded subsystem electronic structure calculations, including DFT-in-DFT and wavefunction theory-in-DFT descriptions. In the interest of efficiency, it is desirable to truncate the atomic orbital basis set in which the subsystem calculation is performed, thus avoiding high-order scaling with respect to the size of the MO virtual space. In this study, we extend a recently introduced projection-based embedding method [F. R. Manby, M. Stella, J. D. Goodpaster, and T. F. Miller III, J. Chem. Theory Comput. 8, 2564 (2012)]10.1021/ct300544e to allow for the systematic and accurate truncation of the embedded subsystem basis set. The approach is applied to both covalently and non-covalently bound test cases, including water clusters and polypeptide chains, and it is demonstrated that errors associated with basis set truncation are controllable to well within chemical accuracy. Furthermore, we show that this approach allows for switching between accurate projection-based embedding and DFT embedding with approximate kinetic energy (KE) functionals; in this sense, the approach provides a means of systematically improving upon the use of approximate KE functionals in DFT embedding

The Post-Common Envelope and Pre-Cataclysmic Binary PG 1224+309

We have made extensive spectroscopic and photometric observations of PG 1224+309, a close binary containing a DA white dwarf primary and an M4+ secondary. The H alpha line is in emission due to irradiation of the M-star by the hot white dwarf and is seen to vary around the orbit. From the radial velocities of the H alpha line we derive a period of P = 0.258689 +/- 0.000004 days and a semi-amplitude of K_Halpha = 160 +/- 8 km/s. We estimate a correction Delta_K = 21 +/- 2 km/s, where K_M = K_Halpha + Delta_K. Radial velocity variations of the white dwarf reveal a semi-amplitude of K_WD = 112 +/- 14 km/s. The blue spectrum of the white dwarf is well fit by a synthetic spectrum having T_eff = 29,300 K and log(g) = 7.38. The white dwarf contributes 97% of the light at 4500 Angstroms and virtually all of the light blueward of 3800 Angstroms. No eclipses are observed. The mass inferred for the white dwarf depends on the assumed mass of the thin residual hydrogen envelope: 0.40 < M_WD < 0.45 solar masses for hydrogen envelope masses of 0 < M_H < 4.0E-4 solar masses. We argue that the mass of the white dwarf is closer to 0.45 solar masses, hence it appears that the white dwarf has a relatively large residual hydrogen envelope. The mass of the M-star is then M_M = 0.28 +/- 0.05 solar masses, and the inclination is i = 77 +/- 7 degrees. We discuss briefly how PG 1224+309 may be used to constrain theories of close binary star evolution, and the past and future histories of PG 1224+309 itself. The star is both a ``post-common envelope'' star and a ``pre-cataclysmic binary'' star. Mass transfer by Roche-lobe overflow should commence in about 10 Gyr.Comment: 17 pages, 8 figures, AAS LaTeX, to appear in AJ, March 199

Effects of Stride Length and Running Mileage on a Probabilistic Stress Fracture Model

The fatigue life of bone is inversely related to strain magnitude. Decreasing stride length is a potential mechanism of strain reduction during running. If stride length is decreased, the number of loading cycles will increase for a given mileage. It is unclear if increased loading cycles are detrimental to skeletal health despite reductions in strain. Purpose: To determine the effects of stride length and running mileage on the probability of tibial stress fracture. Methods: Ten male subjects ran overground at their preferred running velocity during two conditions: preferred stride length and 10% reduction in preferred stride length. Force platform and kinematic data were collected concurrently. A combination of experimental and musculoskeletal modeling techniques was used to determine joint contact forces acting on the distal tibia. Peak instantaneous joint contact forces served as inputs to a finite element model to estimate tibial strains during stance. Stress fracture probability for stride length conditions and three running mileages (3, 5, and 7 miles·d−1) were determined using a probabilistic model of bone damage, repair, and adaptation. Differences in stress fracture probability were compared between conditions using a 2 × 3 repeated-measures ANOVA. Results: The main effects of stride length (P = 0.017) and running mileage (P = 0.001) were significant. Reducing stride length decreased the probability of stress fracture by 3% to 6%. Increasing running mileage increased the probability of stress fracture by 4% to 10%. Conclusions: Results suggest that strain magnitude plays a more important role in stress fracture development than the total number of loading cycles. Runners wishing to decrease their probability for tibial stress fracture may benefit from a 10% reduction in stride length