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This study explores the development of a hybrid deep convolutional neural network (DCNN) model enhanced by autoencoders and data augmentation techniques to predict critical heat flux (CHF) with high accuracy. By augmenting the original input features using three different autoencoder configurations, the model's predictive capabilities were significantly improved. The hybrid models were trained and tested on a dataset of 7225 samples, with performance metrics including the coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), mean absolute error (MAE), and normalized root-mean-squared error (NRMSE) used for evaluation. Among the tested models, the DCNN_3F-A2 configuration demonstrated the highest accuracy, achieving an R2 of 0.9908 during training and 0.9826 during testing, outperforming the base model and other augmented versions. These results suggest that the proposed hybrid approach, combining deep learning with feature augmentation, offers a robust solution for CHF prediction, with the potential to generalize across a wider range of conditions., Comment: 11 pages, 6 figures

In some d-electron oxides the measured effective mass m(exptl) has long been known to be significantly larger than the model effective mass m(model) deduced from mean-field band theory, i.e., m(exptl) = beta * m(model), where beta > 1 is the "mass enhancement", or "mass renormalization" factor. Previous applications of density functional theory (DFT), based on the smallest number of possible magnetic, orbital, and structural degrees of freedom, missed such mass enhancement, a fact that was taken as evidence of strong electronic correlation being the exclusive enabling physics. The current paper reports that known modalities of energy-lowering symmetry-broken spin and structural effects included in mean-field DFT show mass enhancement for both electrons and holes in a range of d-electron perovskites SrVO3, SrTiO3, BaTiO3, and LaMnO3 as well as p-electron perovskites CsPbI3 and SrBiO3, including metals (SrVO3) and insulators (the rest). This is revealed only when enlarged unit cells of the same parent global symmetry, which are large enough to allow for symmetry breaking distortions and concomitant variations in spin order, are explored for their ability to lower the total energy. The paper analyzes the contributions of different symmetry-broken modalities to mass enhancement, finds common effects in the range of d- as well as p-electron perovskites. Thus, symmetry breaking in mean-field theory could describe effects that were previously attributed exclusively to complex correlated treatments. Indeed, broken symmetries are often experimentally observed, e.g., octahedral tilting, Jahn-Teller distortions, or bond disproportionation, and often provide intuitive explanations in terms of degeneracy removal due to lowering of structural symmetry, or as shifting of band energies in explainable directions.

Traditional band theory of perfect crystalline solids often uses as input the structure deduced from diffraction experiments; when modeled by the minimal unit cell this often produces a spatially averaged model. The present study illustrates that this is not always a safe practice unless one examines if the intrinsic bonding mechanism is capable of benefiting from the formation of a distribution of lower symmetry local environments that differ from the macroscopically averaged structure. This can happen either due to positional, or due to magnetic symmetry breaking. By removing the constraint of a small crystallographic cell, the energy minimization in the density functional theory finds atomic and spin symmetry breaking, not evident in conventional diffraction experiments but being found by local probes such as pair distribution function analysis. Here we report that large atomic and electronic anomalies in bulk tetragonal FeSe emerge from the existence of distributions of local positional and magnetic moment motifs. The found symmetry-broken motifs obtained by minimization of the internal energy represent what chemical bonding in tetragonal phase prefers as an intrinsic energy lowering static distortions. This explains observations of band renormalization, predicts orbital order and enhanced nematicity, and provides unprecedented close agreement with spectral function measured by photoemission and local atomic environment revealed by pair distribution function. While the symmetry-restricted strong correlation approach has been argued previously to be the exclusive theory needed for describing the main peculiarities of FeSe, we show here that the symmetry-broken mean-field approach addresses numerous aspects of the problem, provides intuitive insight into the electronic structure, and opens the door for large-scale mean-field calculations for similar d-electron quantum materials.

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is essential to the design and safety of a two-phase flow boiling system. Despite the abundance of predictive tools available to the thermal engineering community, the path for an accurate, robust CHF model remains elusive due to lack of consensus on the DNB triggering mechanism. This work aims to apply a physics-informed, machine learning (ML)-aided hybrid framework to achieve superior predictive capabilities. Such a hybrid approach takes advantage of existing understanding in the field of interest (i.e., domain knowledge) and uses ML to capture undiscovered information from the mismatch between the actual and domain knowledge-predicted target. A detailed case study is carried out with an extensive DNB-specific CHF database to demonstrate (1) the improved performance of the hybrid approach as compared to traditional domain knowledge-based models, and (2) the hybrid model's superior generalization capabilities over standalone ML methods across a wide range of flow conditions. The hybrid framework could also readily extend its applicability domain and complexity on the fly, showing an elevated level of flexibility and robustness. Based on the case study conclusions, the window-type extrapolation mapping methodology is further proposed to better inform high-cost experimental work.

It has been long known that numerous halide and oxide perovskites can have non-ideal octahedra, showing tilting, rotation, and metal atom displacements. It has also been known that compounds that have at low temperatures a single structural motif ("monomorphous structures") could become disordered at higher temperatures, resulting in non-ideal octahedra as an entropy effect. What is shown here is that in many cubic halide perovskites and some oxides compounds a distribution of different low-symmetry octahedra ("polymorphous networks") emerge already from the minimization of the systems internal energy, i.e., they represent the intrinsic, preferred low temperature pattern of chemical bonding. Thermal disorder effects build up at elevated temperatures on top of such low temperature polymorphous networks. Compared with the monomorphous counterparts, the polymorphous networks have lower predicted total energies (enhanced stability), larger band gaps and dielectric constants now dominated by the ionic part, and agrees much more closely with the observed pair distribution functions. The nominal cubic perovskites (Pm-3m) structure deduced from X-Ray diffraction is actually a macroscopically averaged, high symmetry configuration, which should not be used to model electronic properties, given that the latter reflect a low symmetry local configuration., Comment: 20 pages; 7 figures; 94 references

Distinct shortcomings of individual halide perovskites for solar applications, such as restricted range of band gaps, propensity of ABX3 to decompose into AX+BX2, or oxidation of 2ABX3 into A2BX6 have led to the need to consider alloys of individual perovskites. This creates a non-trivial material-selection problem, spanning a continuum of three sets of compositions (one for each sub lattice), and requiring control of phase-separation or ordering in each alloyed subfield. Not surprisingly, material and structure choices were made thus far mostly via trial-and-error explorations. We use ideas from solid state theory of semiconductor alloys to analyze the behaviors of the (FA,Cs)(Pb,Sn)I3 alloys system. Density functional calculations utilizing specially constructed supercells (SQS) are used to calculate the composition dependence of band gaps, energy of decomposition and alloy mixing enthalpies. A number of trends are observed for A-site as well as for B-site alloys. To understand the physical reasons that control these trends we decompose the alloy properties into distinct physical terms: (i) the energies associated with removing the octahedral deformations (tilting, rotations, B site displacements), (ii) the energies of compressing the larger component and expanding the smaller one to the alloy volume, (iii) the charge transfer energies associated with placing the alloyed units onto a common lattice, and finally, (iv) structural relaxation of all bonds within the cells., This analysis clarifies the origin of the observed trends in bang gaps, decomposition energies and mixing enthalpies. Unlike a number of previous calculations we find that the a proper description of alloy physics requires that even the pure, non-alloyed end-point compounds be allowed to develop local environment dependent octahedral deformation that lowers significantly the total energy and raises their band gaps., Comment: 11 pages, 9 figures, 2 tables, 42 references

Trove of exotic topoloid structures has recently been predicted by searching for compounds whose calculated band structure crossing points fulfill specific symmetry requirements. Discovery of exciting physical phenomena by experimental studies of such predicted compounds is just around the corner. Yet, the examination of some of these assumed high-symmetry structures suggests that not always will assembly of atoms in a configuration that yields exotic topological properties be protected against energy-lowering symmetry breaking modes. Indeed, although bulk topological characteristics lead to protected surface/edge states, nothing protects bulk states from structural instability. The burden of proof for theoretical predictions of exciting physical phenomena should include some compelling hints that such phenomena can live in thermodynamically stable (or near stable) compounds. Herein, we illustrate how the use of the calculated total (electron + ion) energies of candidate structures can remove false-positive predicted topoloids from the list of likely realizable compounds, to the benefit of the much-cherished iterative process of theory-experiment materials discovery., Comment: 16 pages, 5 figures, 64 references

Lead-free halide double perovskites with the formula of quaternary A$_2^+$B'B'$^{3+}$X$_6^-$ have recently attracted intense interest as alternatives to lead-halide-perovskite-based optoelectronic materials for their non-toxicity and enhanced chemical and thermodynamic stability. However, the understanding of intrinsic defect properties and their effects on carrier transport and Fermi level tuning is still limited. In this paper, we show that, by exploring the phase diagram of a halide double perovskite, one can control the effects of intrinsic defects on carrier trapping and Fermi level pinning. We reveal the ideal growth conditions to grow p-type Cs$_2$AgInCl$_6$ and Cs$_2$AgBiCl$_6$ as well as semi-insulating Cs$_2$AgBiBr$_6$ with low trap density for targeted photovoltaic or visible-light/radiation detection application., Comment: 12 pages, 10 figures

The material class of hybrid organic-inorganic perovskites has risen rapidly from a virtually unknown material in photovoltaic applications a short 7 years ago into a ~20% efficient thin-film solar cell material. As promising as this class of materials is, however, there are limitations associated with its poor long-term stability, non-optimal band gap, presence of environmentally-toxic Pb element, etc. We herein apply a functionality-directed theoretical materials selection approach as a filter for initial screening of the compounds that satisfy the desired intrinsic photovoltaic functionalities and might overcome the above limitations. First-principles calculations are employed to systemically study thermodynamic stability and photovoltaic-related properties of hundred of candidate hybrid perovskites. We have identified in this materials selection process fourteen Ge and Sn-based materials with potential superior bulk-material-intrinsic photovoltaic performance. A distinct class of compounds containing NH3COH$^+$ with the organic molecule derived states intriguingly emerging at band-edges is found. Comparison of various candidate materials offers insights on how composition variation and microscopic structural changes affect key photovoltaic relevant properties in this family of materials., Comment: 17 pages, 10 figures,Supplementary information