At present, molecular dynamics with electronic friction (MDEF) is the workhorse model to go beyond the Born–Oppenheimer approximation in modeling dynamics of molecules at metal surfaces. Concomitant ...friction coefficients can be calculated with either the local density friction approximation (LDFA) or orbital-dependent friction (ODF), which, unlike LDFA, accounts for anisotropy while relying on other approximations. Due to the computational cost of ODF, extensive high-dimensional MDEF trajectory calculations of experimentally measurable observables have hitherto only been performed based on LDFA. We overcome this limitation with a continuous neural-network-based representation. In our first application to the scattering of vibrationally excited H2 and D2 from Cu(111), we predict up to three times higher vibrational de-excitation probabilities with ODF than with LDFA. These results indicate that anisotropic electronic friction can be important for specific molecular observables. Future experiments can test for this “fingerprint” of different approximations underlying state-of-the-art MDEF.
Ab initio molecular dynamics (AIMD) simulations enable the accurate description of reactive molecule–surface scattering especially if energy transfer involving surface phonons is important. However, ...presently, the computational expense of AIMD rules out its application to systems where reaction probabilities are smaller than about 1%. Here we show that this problem can be overcome by a high-dimensional neural network fit of the molecule–surface interaction potential, which also incorporates the dependence on phonons by taking into account all degrees of freedom of the surface explicitly. As shown for N2 + Ru(0001), which is a prototypical case for highly activated dissociative chemisorption, the method allows an accurate description of the coupling of molecular and surface atom motion and accurately accounts for vibrational properties of the employed slab model of Ru(0001). The neural network potential allows reaction probabilities as low as 10–5 to be computed, showing good agreement with experimental results.
Electron–hole pair (ehp) excitation is thought to substantially affect the dynamics of molecules on metal surfaces, but it is not clear whether this can be better addressed by orbital-dependent ...friction (ODF) or the local density friction approximation (LDFA). We investigate the effect of ehp excitation on the dissociative chemisorption of N2 on and its inelastic scattering from Ru(0001), which is the benchmark system of highly activated dissociation, with these two different models. ODF is in better agreement with the best experimental estimates for the reaction probabilities than LDFA, yields results for vibrational excitation in better agreement with experiment, but slightly overestimates the translational energy loss during scattering. N2 on Ru(0001) is thus the first system for which the ODF and LDFA approaches are shown to yield substantially different results for easily accessible experimental observables, including reaction probabilities.
At present, molecular dynamics with electronic friction (MDEF) is the workhorse model to go beyond the Born-Oppenheimer approximation in modeling dynamics of molecules at metal surfaces. Concomitant ...friction coefficients can be calculated with either the local density friction approximation (LDFA) or orbital-dependent friction (ODF), which, unlike LDFA, accounts for anisotropy while relying on other approximations. Due to the computational cost of ODF, extensive high-dimensional MDEF trajectory calculations of experimentally measurable observables have hitherto only been performed based on LDFA. We overcome this limitation with a continuous neural-network-based representation. In our first application to the scattering of vibrationally excited H
and D
from Cu(111), we predict up to three times higher vibrational de-excitation probabilities with ODF than with LDFA. These results indicate that anisotropic electronic friction can be important for specific molecular observables. Future experiments can test for this "fingerprint" of different approximations underlying state-of-the-art MDEF.
The efficient generation of white light by phosphor‐converted LEDs (pcLEDs) suffers from a trade‐off between high color rendition, low correlated color temperatures, and luminous efficacy. While this ...is partially an inherent problem, it is also caused by the spectral efficiency of the materials used. The particular challenges for materials research lie, amongst the demanding general requirements, in finding very narrow‐band or line‐emitting materials: excitable with blue light, emitting in the near red. A way to design Mn(IV) activated line emitters is proposed, and methods for high‐throughput combinatorial syntheses are specified.
The generation of white light using blue LEDs and luminescent materials is discussed with respect to the phosphors currently available. The need for efficient red‐emitting phosphors is highlighted and the use of Mn(IV) is proposed as a possible route towards line emitters. Combinatorial approaches to materials synthesis are briefly described.
We investigate the dielectric constant and the dielectric decrement of aqueous NaCl solutions by means of molecular dynamic simulations. We thereby compare the performance of four different force ...fields and focus on disentangling the origin of the dielectric decrement and the influence of scaled ionic charges, as often used in nonpolarizable force fields to account for the missing dynamic polarizability in the shielding of electrostatic ion interactions. Three of the force fields showed excessive contact ion pair formation, which correlates with a reduced dielectric decrement. In spite of the fact that the scaling of charges only weakly influenced the average polarization of water molecules around an ion, the rescaling of ionic charges did influence the dielectric decrement, and a close-to-linear relation of the slope of the dielectric constant as a function of concentration with the ionic charge was found.
Ab initio molecular dynamics (AIMD) simulations enable the accurate description of reactive molecule-surface scattering especially if energy transfer involving surface phonons is important. However, ...presently, the computational expense of AIMD rules out its application to systems where reaction probabilities are smaller than about 1%. Here we show that this problem can be overcome by a high-dimensional neural network fit of the molecule-surface interaction potential, which also incorporates the dependence on phonons by taking into account all degrees of freedom of the surface explicitly. As shown for N
+ Ru(0001), which is a prototypical case for highly activated dissociative chemisorption, the method allows an accurate description of the coupling of molecular and surface atom motion and accurately accounts for vibrational properties of the employed slab model of Ru(0001). The neural network potential allows reaction probabilities as low as 10
to be computed, showing good agreement with experimental results.
In semiconductor devices, hydrogen has traditionally been viewed as a panacea for defects, being adept at neutralizing dangling bonds and consequently purging the related states from the band gap. ...With amorphous silicon nitride (a-Si3N4)a material critical for electronic, optical, and mechanical applicationsthis belief holds true as hydrogen passivates both silicon and nitrogen dangling bonds. However, there is more to the story. Our density functional theory calculations unveil hydrogen’s multifaceted role upon incorporation in a-Si3N4. On the “Jekyll” side, hydrogen atoms are indeed restorative, healing coordination defects in a-Si3N4. However, “Hyde” emerges as hydrogen induces Si–N bond breaking, particularly in strained regions of the amorphous network. Beyond these dual roles, our study reveals an intricate balance between hydrogen defect centers and intrinsic charge traps that already exist in pristine a-Si3N4: the excess charges provided by the H atoms result in charging of the a-Si3N4 dielectric layer.
The rotational dynamics of an organic cation in hybrid halide perovskites is intricately linked to the phase transitions that are known to occur in these materials; however, the exact relation is not ...clear. We have performed detailed model studies on methylammonium lead iodide and formamidinium lead iodide to unravel the relation between rotational dynamics and phase behavior. We show that the occurrence of the phase transitions is due to a subtle interplay between dipole–dipole interactions between the organic cations, specific (hydrogen bonding) interactions between the organic cation and the lead iodide lattice, and deformation of the lead iodide lattice in reaction to the reduced rotational motion of the organic cations. This combination of factors results in phase transitions at specific temperatures, leading to the formation of large organized domains of dipoles. The latter can have significant effects on the electronic structure of these materials.
We present an embedding technique for metallic systems that makes it possible to model energy dissipation into substrate phonons during surface chemical reactions from first principles. The ...separation of chemical and elastic contributions to the interaction potential provides a quantitative description of both electronic and phononic band structure. Application to the dissociation of O2 at Pd(100) predicts translationally “hot” oxygen adsorbates as a consequence of the released adsorption energy (ca. 2.6 eV). This finding questions the instant thermalization of reaction enthalpies generally assumed in models of heterogeneous catalysis.
Hot or not: An embedding technique for metallic systems makes it possible to model energy dissipation into substrate phonons during surface chemical reactions from first principles. Application to O2 dissociation at Pd(100) predicts translationally “hot” oxygen adsorbates as a consequence of the released adsorption energy (ca. 2.6 eV). This calls into question the instant thermalization of reaction enthalpies generally assumed in heterogeneous catalysis modeling.
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