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Oxide glasses are intrinsically brittle, lacking sufficient atomic-scale mechanisms that can relax mechanical stresses in the vicinity of a propagating crack. As a result, fracture is typically well-captured by considering local bond rupture at the crack tip. Here we demonstrate that barrier energies related to the low-temperature 𝛾-relaxation mode in alkali-aluminosilicate glasses are inversely related to the fracture toughness measured via standardized three-point bending fracture experiments. This holds true for both a series with varying cations (Li, Na, K) and one with varying Li concentration. The structural rationale for this finding is gained via Raman spectroscopy. The findings suggest that a fundamental structural relaxation mode measured on bulk specimens can serve as an effective guideline for fracture toughness of oxide glasses. Data for additional silicate glasses support this conclusion.
Enhancing the fracture toughness is still one of the major challenges in the field of oxide glasses. To screen different glass systems for promising candidates, a theoretical expression for the fracture surface energy, G, linked to the fracture toughness, KIc, is thus of interest. Extending our earlier work on nucleation and surface energies [1], we present a simple approach for predicting the fracture surface energy of oxide glasses, G using readily available crystallographic structure data and diatomic bond energies. The proposed method assumes that G of glass equals the surface fracture energy of the weakest fracture (cleavage) plane of the isochemical crystal. For non-isochemically crystallizing glasses, an average G is calculated from the weighed fracture energy data of the constitutional crystal phases according to Conradt [2]. Our predictions yield good agreement with the glass density- and chemical bond energy-based prediction model of Rouxel [3] and with experimentally obtained G values known at present.
[1] C. Tielemann, S. Reinsch, R. Maass, J. Deubener, R. Müller, J. Non-Cryst. Solids 2022, 14, 100093
[2] R. Conradt, J. Non-Cryst. Solids 2004, 345-346, 16
[3] R., Tanguy, Scripta Materialia 2017, 109-13, 137
Silicate glass fracture surface energy calculated from crystal structure and bond-energy data
(2023)
We present a novel method to predict the fracture surface energy, γ, of isochemically crystallizing silicate glasses using readily available crystallographic structure data of their crystalline counterpart and tabled diatomic chemical bond energies, D0. The method assumes that γ equals the fracture surface energy of the most likely cleavage plane of the crystal. Calculated values were in excellent agreement with those calculated from glass density, network connectivity and D0 data in earlier work. This finding demonstrates a remarkable equivalence between crystal cleavage planes and glass fracture surfaces.
The search for strong and tough oxide glasses is important for making safer, more environmentally friendly, thinner glass products. However, this task remains generally difficult due to the material’s inherent brittleness. In search for tougher glasses, fracture toughness (KIC) prediction models are helpful tools to screen for promising candidates.
In this work, a novel model to predict KIC via the fracture surface energy, γ, is presented. Our approach uses readily available crystallographic structure data of the glass’s isochemical crystal and tabled diatomic chemical bond energies, D0. The method assumes that γ of a glass equals the fracture surface energy of the most likely cleavage plane of the crystal. Calculated values were not only in excellent agreement with those calculated with a former well-working model, but also demonstrates a remarkable equivalence between crystal cleavage planes and glass fracture surfaces.
Finally, the effectiveness of fracture toughness enhancement by chemical substitution is discussed based on our results and alternative toughening strategies will be suggested.
The search for strong and tough oxide glasses is important for making safer, environment-friendlier, thinner glasses. As fracture toughness experiments in brittle materials are complicated and time-consuming , modelling glass fracture surface energy, G, and fracture toughness, KIc, is of interest for screening promising candidates. Inspired by Rouxel´s idea of preferred crack growth along cutting weakest bonds within a glass structure and a study by Tielemann et al. , which indicates a correlation between crystal fracture surface and glass-crys¬tal interfacial energies, we present a new approach for predicting G. Combining both ideas, we used diatomic bond energies and readily available crystallographic structure data for estimating G. The proposed method assumes that G of the glass equals the surface fracture energy of the cleavage plane in its respective isochemical crystal. We calculated G- values for more than 25 iso-chemical silicate systems and compared them to calculated values from Rouxel’s widely used procedure, which is well working and based on glass densities and chemical bond energies. Not only does our model yields good agreement with [3], but it also enables an estimation for glasses with unknown density and can therefore contribute to broaden the data basis for glass property modelling tools. Most interestingly, however, this agreement indicates an interesting similarity between cleavage planes in a crystal and its corresponding glass state in terms of fracture processes.
Chemically complex materials (CCMats) including high-entropy alloys, oxides, and related multi-principal element systems offer a paradigm shift in materials design by leveraging chemical diversity to simultaneously optimize functional, structural, and sustainability criteria. The vastness of the compositional and structural space in CCMats propels the field into an expanding exploratory state. To reconcile functional and structural performance across this immense parameter space remains an open challenge. This Perspective evaluates the opportunities and challenges associated with harnessing chemical complexity across a broad spectrum of applications, such as hydrogen storage, ionic conductors, catalysis, magnetics, dielectrics, semiconductors, optical materials, and multifunctional structural systems. It is delineated how three central design strategies: targeted substitution (SUB), defect engineering (DEF), and diversity management (DIV) enable the reconciliation of high functional performance with long-term structural stability and environmental responsibility.
Advances in computational thermodynamics, microstructure simulations, machine learning, and multimodal characterization are accelerating the exploration and optimization of CCMats, while robust data infrastructures and automated synthesis workflows are emerging as essential tools for navigating their complex compositional space. By fostering cross-disciplinary knowledge transfer and embracing data-driven design, CCMats are poised to deliver next-generation materials solutions that address urgent technological, energy, and
environmental demands.
