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Dmg Properties
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Dimethylglyoxime (DMG) usually forms thermodynamically stable chelating complexes with selective divalent transition-metal ions. Electronic and spectral properties of metal-DMG complexes are highly dependent on the nature of metal ions. Using range-separated hybrid functional augmented with dispersion corrections within density functional theory (DFT) and time-dependent DFT, we present a detailed and comprehensive study on structural, electronic, and spectral (both IR and UV-vis) properties of M(DMG)2 [M = Ni2+, Cu2+] complexes. Ni(DMG)2 results are thoroughly compared with Cu(DMG)2 and also against available experimental data. Stronger H-bonding leads to greater stability of Ni(DMG)2 with respect to isolated ions (M2+ and DMG-) compared to Cu(DMG)2. In contrast, a relatively larger reaction enthalpy for Cu(DMG)2 formation from chemically relevant species is found than that of Ni(DMG)2 because of the greater binding enthalpy of [Ni(H2O)6]2+ than that of [Cu(H2O)6]2+. In dimers, Ni(DMG)2 is found to be 6 kcal mol-1 more stable than Cu(DMG)2 due to a greater extent of dispersive interactions. Interestingly, a modest ferromagnetic coupling (588 cm-1) is predicted between two spin-1/2 Cu2+ ions present in the Cu(DMG)2 dimer. Additionally, the potential energy curves calculated along the O-H bond coordinate for both complexes suggest asymmetry and symmetry in the H-bonding interactions between the H-bond donor and acceptor O centers in the solid-state and in solution, respectively, well corroborating with early experimental findings. Interestingly, a lower proton transfer barrier is obtained for the Ni(DMG)2 compared to its Cu-analogue due to stronger H-bonding in the former complex. In fact, relatively weaker H-bonding in Cu(DMG)2 results in blue-shifted O-H stretching modes compared to that in Ni(DMG)2. On the other hand, qualitatively similar optical absorption spectra are obtained for both complexes with red-shifted peaks found for the Cu(DMG)2. Finally, computational models for axial mono- and diligand (aqua and ammonia) coordinated M(DMG)2 complexes are predicted to be energetically feasible and stable with relatively greater binding stability obtained for the ammonia-coordination.
Among the properties in the DMG/Noah Properties portfolio are Roselle Station Apartments in Roselle, IL; Bloomingdale Trails Apartments in Bloomingdale, il; and Galewood Flats in Northwest Chicago (pictured). Currently, DMG, led by managing broker Roger Daniel, has a management portfolio of more than 1,500 units.
Under shear stress (e. g. when inserting the tray into the mouth) the viscosity properties change and Honigum-Light overcomes the alleged opposites: the initially stable material flows below the preparation line and thus provides a perfect detail reproduction
Its combination of zirconia filler and DMG patented nanotechnology significantly improves strength, flowability and physical properties, making it ultra-strong and reliable; it's the ultimate in resin technology for excellent fitting, long-lasting restorations and happy patients alike.
The material's outstanding flow properties guarantee optimum adaptation to the shape of cavity walls and posts. The thin film thickness of just 20 μm is ideal when used for post cementation. (According to ISO 4049 the limit for precision cement is 25 μm).
cfgDMG = wlanDMGConfig(Name,Value) sets properties using one or more name-value pairs. Enclose each property name in quotation marks. For example, wlanDMGConfig('MCS','13','TrainingLength',4) specifies a DMG format with these properties:
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We address the problem of verifying timed properties of Markovian models of large populations of interacting agents, modelled as finite state automata. In particular, we focus on time-bounded properties of (random) individual agents specified by Deterministic Timed Automata (DTA) endowed with a single clock. Exploiting ideas from fluid approximation, we estimate the satisfaction probability of the DTA properties by reducing it to the computation of the transient probability of a subclass of Time-Inhomogeneous Markov Renewal Processes with exponentially and deterministically-timed transitions, and a small state space. For this subclass of models, we show how to derive a set of Delay Differential Equations (DDE), whose numerical solution provides a fast and accurate estimate of the satisfaction probability. In the paper, we also prove the asymptotic convergence of the approach, and exemplify the method on a simple epidemic spreading model. Finally, we also show how to construct a system of DDEs to efficiently approximate the average number of agents that satisfy the DTA specification.
For designing reliable and robust engineering systems, designers seek materials with optimal values of properties such as strength and toughness. To achieve such a material, appropriate models should relate deformation to the key microstructures such as particle size, interfacial strength, and spacing[12]. In addition, models can account for the uncertainty of material properties and microstructural characteristics[5]. With the help of such microstructure-property relationship constitutive models, it is possible to relate the mechanical properties of interest, such as stress, strain, and toughness, to key microstructures such as particle size and spacing, interfacial strength, and grain size.
where = ,= , through are the material plasticity parameters related to kinematic hardening and recovery terms, through are the material plasticity parameters related to isotropic hardening and recovery terms, whereas Ca and Cb are the material plasticity parameters related to dynamic recovery and anisotropic hardening terms, respectively. Constants through are determined from macroscale experiments at different temperatures and strain rates. The damage variable, represents the damage fraction of material within a continuum element. The mechanical properties of a material depend upon the amount and type of microdefects within its structure. Deformation changes these microdefects, and when the number of microdefects accumulates, damage is said to have grown. The three components of damage progression mechanism are void nucleation, growth and coalescence from second phase particles and pores. In this regard, the material time derivative of damage, is expressed as
where is a material constant that scales the response as a function of initial conditions; d is the particle size; is the fracture toughness; f is the volume fraction of second-phase particles; is the void nucleation temperature dependent parameter;,, and are the independent stress invariants; m void growth constant; is the initial void radius, whereas material constants a, b, and c are the void-nucleation constants that are determined from different stress states (i.e., a is found from a torsion test, while b and c are determined from tension and compression tests, with all three having units of stress).The time integral form of Eq. 7 is used as the damage state. Based on this ISV model, material failure is assumed to occur when Eq. 7 reaches unity (->1.0 ) within a finite element. For all practical purposes, material failure can be assumed at a much smaller value (safe limit) of as the damage increases very rapidly to 1.0 shortly after reaches a small percentage. The mechanical properties of a material depend upon the amount and type of microdefects within its structure. Deformation changes these microdefects, and when the number of microdefects accumulates, the damage state is said to have grown. By including damage, as an ISV, different forms of damage rules can be incorporated easily into the constitutive framework.In summary, ,R, , ,c , v,and in Eqs. 1 through 9 represent the ISVs in this microstructure-property relationship material model. 2ff7e9595c
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