Accelerated design of architectured ceramics with tunable thermal resistance via a hybrid machine learning and finite element approach

Abstract Topologically interlocked architectures can transform brittle ceramics into tougher materials, while making the material design procedure a cumbersome task since modeling the whole architectural design space is not efficient and, to a degree, is not viable. We propose an approach to design architectured ceramics using machine learning (ML), trained by finite element analysis data and together with a self-learning algorithm, to discover high-performance architectured ceramics in thermomechanical environments. First, topologically interlocked panels are parametrically generated. Then, a limited number of designed architectured ceramics subjected to a thermal load is studied. Finally, the multilinear perceptron is employed to train the ML model in order to predict the thermomechanical performance of architectured panels with varied interlocking angles and number of blocks. The developed feed-forward artificial neural network framework can boost the architectured ceramic design efficiency and open up new avenues for controllability of the functionality for various high-temperature applications. This study demonstrates that the architectured ceramic panels with the ML-assisted engineered patterns show improvement up to 30% in frictional energy dissipation and 7% in the sliding distance of the tiles and 80% reduction in the strain energy, leading to a higher safety factor and the structural failure delay compared to the plain ceramics

Derivative Couplings with Built-In Electron-Translation Factors: Application to Benzene

Derivative couplings are the essential quantities at the interface between electronic-structure calculations and nonadiabatic dynamics. Unfortunately, standard approaches for calculating these couplings usually neglect electronic motion, which can lead to spurious electronic transitions. Here we provide a general framework for correcting these anomalies by incorporating perturbative electron-translation factors (ETFs) into the atomic-orbital basis. For a range of representative organic molecules, we find that our ETF correction is often small but can be qualitatively important, especially for few-atom systems or highly symmetric molecules. Our method entails no additional computational cost, such that ETFs are “built-in,” and it is equivalent to a simple rule of thumb: We should set the antisymmetrized version of the nuclear overlap-matrix derivative to zero wherever it appears. Thus, we expect that built-in ETFs will be regularly incorporated into future studies of nonadiabatic dynamics

Analysis of Localized Diabatic States beyond the Condon Approximation for Excitation Energy Transfer Processes

In a previous paper [Fatehi, S.; et al. J. Chem. Phys. 2013, 139, 124112], we demonstrated a practical method by which analytic derivative couplings of Boys-localized CIS states can be obtained. In this paper, we now apply that same method to the analysis of triplet–triplet energy transfer systems studied by Closs and collaborators [Closs, G. L.; et al. J. Am. Chem. Soc.1988, 110, 2652]. For the systems examined, we are able to conclude that (i) the derivative coupling in the BoysOV basis is negligible, and (ii) the diabatic coupling will likely change little over the configuration space explored at room temperature. Furthermore, we propose and evaluate an approximation that allows for the inexpensive calculation of accurate diabatic energy gradients, called the “strictly diabatic” approximation. This work highlights the effectiveness of diabatic state analytic gradient theory in realistic systems and demonstrates that localized diabatic states can serve as an acceptable approximation to strictly diabatic states

TD-DFT spin-adiabats with analytic nonadiabatic derivative couplings

Wepresent an algorithm for efficient calculation of analytic nonadiabatic derivative couplings between spin-adiabatic, time-dependent density functional theory states within the Tamm-Dancoff approximation. Our derivation is based on the direct differentiation of the Kohn-Sham pseudowavefunction using the framework of Ou et al. Our implementation is limited to the case of a system with an even number of electrons in a closed shell ground state, and we validate our algorithm against finite difference at an S1/T2 crossing of benzaldehyde. Through the introduction of a magnetic field spin-coupling operator, we break time-reversal symmetry to generate complex valued nonadiabatic derivative couplings. Although the nonadiabatic derivative couplings are complex valued, we find that a phase rotation can generate an almost entirely real-valued derivative coupling vector for the case of benzaldehyde

TD-DFT spin-adiabats with analytic nonadiabatic derivative couplings

Wepresent an algorithm for efficient calculation of analytic nonadiabatic derivative couplings between spin-adiabatic, time-dependent density functional theory states within the Tamm-Dancoff approximation. Our derivation is based on the direct differentiation of the Kohn-Sham pseudowavefunction using the framework of Ou et al. Our implementation is limited to the case of a system with an even number of electrons in a closed shell ground state, and we validate our algorithm against finite difference at an S1/T2 crossing of benzaldehyde. Through the introduction of a magnetic field spin-coupling operator, we break time-reversal symmetry to generate complex valued nonadiabatic derivative couplings. Although the nonadiabatic derivative couplings are complex valued, we find that a phase rotation can generate an almost entirely real-valued derivative coupling vector for the case of benzaldehyde

The Requisite Electronic Structure Theory To Describe Photoexcited Nonadiabatic Dynamics: Nonadiabatic Derivative Couplings and Diabatic Electronic Couplings

Conspectus Electronically photoexcited dynamics are complicated because there are so many different relaxation pathways: fluorescence, phosphorescence, radiationless decay, electon transfer, etc. In practice, to model photoexcited systems is a very difficult enterprise, requiring accurate and very efficient tools in both electronic structure theory and nonadiabatic chemical dynamics. Moreover, these theoretical tools are not traditional tools. On the one hand, the electronic structure tools involve couplings between electonic states (rather than typical single state energies and gradients). On the other hand, the dynamics tools involve propagating nuclei on multiple potential energy surfaces (rather than the usual ground state dynamics). In this Account, we review recent developments in electronic structure theory as directly applicable for modeling photoexcited systems. In particular, we focus on how one may evaluate the couplings between two different electronic states. These couplings come in two flavors. If we order states energetically, the resulting adiabatic states are coupled via derivative couplings. Derivative couplings capture how electronic wave functions change as a function of nuclear geometry and can usually be calculated with straightforward tools from analytic gradient theory. One nuance arises, however, in the context of time-dependent density functional theory (TD-DFT): how do we evaluate derivative couplings between TD-DFT excited states (which are tricky, because no wave function is available)? This conundrum was recently solved, and we review the solution below. We also discuss the solution to a second, pesky problem of origin dependence, whereby the derivative couplings do not (strictly) satisfy translation variance, which can lead to a lack of momentum conservation. Apart from adiabatic states, if we order states according to their electronic character, the resulting diabatic states are coupled via electronic or diabatic couplings. The couplings between diabatic states |ΞA⟩ and |ΞB⟩ are just the simple matrix elements, ⟨ΞA|H|ΞB⟩. A difficulty arises, however, because constructing exactly diabatic states is formally impossible and constructing quasi-diabatic states is not unique. To that end, we review recent advances in localized diabatization, which is one approach for generating adiabatic-to-diabatic (ATD) transformations. We also highlight outstanding questions in the arena of diabatization, especially how to generate multiple globally stable diabatic surfaces

Gas phase potassium release from a single particle of biomass during high temperature combustion

A notable characteristic of solid biomass fuels as compared to coal is their significantly higher potassium content. Potassium influences ash deposition and corrosion mechanisms in furnaces and boilers, the effects of which may differ depending on phase transformations of potassium species in the gas phase and condensed phase. An understanding of how potassium is released from biomass fuels during the combustion process is therefore useful for plant designers and operators assessing means of avoiding or mitigating these potential problems. An experimental method is used to measure release patterns from single particles of biomass fuels using flame emission spectroscopy and a single-particle combustion rig. The experimental arrangement also allowed simultaneous thermal imaging of the combusting particle in order to determine the surface temperature. A model of the single particle combustion is presented. Using experimental data on devolatilisation and burnout times for different sized particles and the measured surface temperature profiles, the thermal and kinetic sub-models are verified. A model for potassium release is described and this is integrated to the single particle combustion model to allow prediction of the temporal patterns of release of gas-phase potassium. The modelled release patterns were compared with those observed. Good agreement between modelled and measured potassium release patterns was attained confirming that the proposed mechanisms affecting potassium release are valid

Observations on the release of gas-phase potassium during the combustion of single particles of biomass

One of the more significant characteristics of solid biomass fuels as compared to coal is the quantity of potassium that they contain. Potassium content influences ash deposition and corrosion mechanisms in furnaces, the effects of which may differ depending on phase transformations of potassium species in the gas phase and condensed phase. The fate of potassium from the fuel during the combustion process is therefore an important concern. To investigate this, an experimental method is presented in which the release patterns from single particles of various biomass fuels are measured by use of flame emission spectroscopy implemented using a custom-built photo-detector device. Single particles of fuel are combusted in a methane flame with a gas temperature of ∼1800 K. The observed potassium release patterns for thirteen solid biomass materials are presented. The data are analyzed to examine the relationships between: the level of potassium in the fuel particle; the fraction of potassium released at each stage of combustion and the peak rate of release of potassium to gas-phase during combustion. Correlations between these quantities are identified with key trends, patterns and differences highlighted. The analyses provide useful information for the development and validation of modelling of potassium release during combustion of biomass

Description of combined ARHSP/JALS phenotype in some patients with SPG11 mutations

Background: SPG11 mutations can cause autosomal recessive hereditary spastic paraplegia (ARHSP) and juvenile amyotrophic lateral sclerosis (JALS). Because these diseases share some clinical presentations and both can be caused by SPG11 mutations, it was considered that definitive diagnosis may not be straight forward. Methods: The DNAs of referred ARHSP and JALS patients were exome sequenced. Clinical data of patients with SPG11 mutations were gathered by interviews and neurological examinations including electrodiagnosis (EDX) and magnetic resonance imaging (MRI). Results: Eight probands with SPG11 mutations were identified. Two mutations are novel. Among seven Iranian probands, six carried the p.Glu1026Argfs*4-causing mutation. All eight patients had features known to be present in both ARHSP and JALS. Additionally and surprisingly, presence of both thin corpus callosum (TCC) on MRI and motor neuronopathy were also observed in seven patients. These presentations are, respectively, key suggestive features of ARHSP and JALS. Conclusion: We suggest that rather than ARHSP or JALS, combined ARHSP/JALS is the appropriate description of seven patients studied. Criteria for ARHSP, JALS, and combined ARHSP/JALS designations among patients with SPG11 mutations are suggested. The importance of performing both EDX and MRI is emphasized. Initial screening for p.Glu1026Argfs*4 may facilitate SPG11 screenings in Iranian patients. © 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LL