Boundary lubrication is governed by molecular processes at the sliding interface that are inaccessible to classical continuum descriptions. While molecular dynamics (MD) simulations can resolve these processes in atomistic detail, incorporating their output into engineering-scale models through semi-empirical constitutive laws becomes increasingly difficult as confinement approaches the molecular scale. Here, we apply a nonparametric multiscale framework based on Gaussian process (GP) regression to model boundary lubrication of hexadecane confined between gold surfaces under pressures up to 1 GPa and gap heights down to 1.4 nm. The GP surrogates are trained on nonequilibrium MD simulations of the confined fluid and directly provide stress predictions to a continuum thin-film solver, circumventing the need for fixed-form constitutive laws. The framework naturally captures molecular phenomena such as density layering, viscosity changes, and the strongly nonlinear wall slip that dominates the frictional response at high pressures and small gap heights. Our results reproduce the atomistic benchmark data of Codrignani et al., demonstrating that nonparametric surrogate models offer a flexible and physically transparent route toward predictive continuum modeling of boundary lubrication.

Deformation twinning is an important deformation mechanism for low stacking fault energy face-centered cubic (FCC) alloys including multi-principal element alloys, however, its underlying mechanism remains incompletely understood. In this work, we applied in situ scanning electron microscope (SEM) micro-pillar compression combined with microstructural investigations to gain insights into the fundamental mechanism of deformation twinning and its stress and/or strain dependence. Our findings reveal that the morphology of the deformation twins and the controlling mechanism vary with micro-pillar size. In sub-micron pillars, single-slip based twinning models like the three-layer model were predominant as confirmed by in situ deformation and post-mortem microstructural analyses. For pillar diameters above 3 & micro;m, two different twin variants were observed including one formed by the three-layer mechanism, although the secondary twinning mechanism remains unclear. When the pillar diameter increased to 10 & micro;m, the applied stresses was insufficient to activate deformation twinning, and dislocation slip became the dominant deformation mode. A quantitative stress analysis of pillars ranging from 0.14 & micro;m to 10 & micro;m in diameter showed a lower bound for twinning stress of approximately 130 MPa. Finally, size dependence investigations revealed no significant difference between twinning stress and full dislocation slip critical resolved shear stress. This not only proves that dislocation slip is a prerequisite for twinning, but also indicates that, above a threshold stress, twinning could be more strain rather than stress-dependent.

This work presents a physically based probabilistic model for LCF life of the conventional cast (CC) nickel-based superalloy MAR-M247. The model explicitly accounts for the effects of casting defects. Over 100 LCF tests were conducted at 850 °C and 950 °C on specimens with and without defects. Specimens were extracted from turbine blades that had manufacturing-related casting defects. Additionally, artificial defects were introduced into initially defect-free specimens. A multi-stage CT- and μCT-based specimen extraction strategy was developed to precisely position casting defects within specimens. Defects were parameterized orthogonally to the loading direction based on their size, shape and orientation using SEM fractography. For all tested strain ranges, a dominant influence of defect size on fatigue life was found. The effects of defect shape and orientation were small in comparison. Significant scatter of material parameters was observed experimentally. Electron backscatter diffraction (EBSD) revealed significant variations in grain size and orientation depending on the specimen extraction position. The model accounts for this by using individual values for stress ratio Rσ and Young’s modulus E. LCF fatigue life was modeled using an approach based on the cyclic crack tip opening displacement ΔCTOD. Defect size was accounted for as an initial crack length based on the Feret diameter dFeret of each defect. Additionally, an El Haddad-type threshold term was used to account for defect size dependence in the high-cycle regime. Validation against experimental data showed robust prediction accuracy across all defect types, defect sizes, specimen geometries, temperatures, and strain ranges. Model inaccuracies arising from the fracture mechanics based approximation solution were estimated analytically. For defects large compared to the specimen geometry, a tendency towards more conservative fatigue life assessment was shown. A probabilistic framework was established using Monte Carlo simulations. Material scatter was modeled using experimentally derived distributions for E and Rσ. Fatigue life distributions were quantified under realistic operating temperatures and loads. The results support risk-based maintenance and optimized gas turbine operation in modern decarbonized energy systems.

The mechanisms governing wear evolution in multilayer hard coatings remain a key challenge in tool tribology and dry machining. This study investigates the dry sliding behaviour of TiN/AlTiN multilayer-coated (thickness 1 μm/5 μm) as well as uncoated tungsten carbide (WC) cutting tools in a pin-on-disk configuration. Sliding tests were performed in a cylinder-on-line contact using commercial grooving inserts against AISI 1045 steel disks across a load–velocity matrix (20, 30 N; 10, 40, 80 m/min), with extended duration runs at 40 m/min to capture wear progression. The TiN/AlTiN-coated tools exhibited more stable friction coefficients and significantly reduced wear volumes compared to uncoated tools (73–92% lower specific wear rates, corresponding to 4×–12× improvement). The enhanced performance is attributed to the formation of a dense, oxide-rich tribofilm that effectively suppressed both adhesive and abrasive wear. In contrast, uncoated tools exhibited unstable frictional behaviour and severe material loss due to grooving and transfer. Wear evolution analysis using SEM/EDS, FIB cross-sectioning, WLI, and XPS depth profiling indicated gradual layer-by-layer wear progression in the TiN/AlTiN coating system, while uncoated tools showed accelerated nonlinear wear at higher velocities. The quantified wear coefficients together with the tribofilm chemistry provide mechanistic insight into coating wear and define key experimental inputs for future, physics-based tool-life modelling under dry machining conditions.

We present a theoretical study with focus on the transparency of silica glass (a-SiO2) in the ultraviolet light spectrum. All imperfections in the crystal structure can cause electronic subgap levels and thus increase the absorption of light. Therefore, we investigate a wide variety of defects and their respective electronic levels, like intrinsic point defects, defects connected to H2, O2 or H2O, and (inner) surfaces. Our calculations show that most subgap levels originating from stretched bonds, silane (SiH) or silanol (SiOH) groups concentrate in a range of 0–2 eV around the band edges. For an energy of ∼3.5 eV, like that of lasers in the controlled fusion ignition at the National Ignition Facility (NIF), these subgap levels do not cause absorption of such photons due to the large band gap ≥8 eV of a-SiO2. However, E’-centers (≡Si•), non bridging oxygen hole centers (NBOHC, ≡Si–O•) and peroxy linkages (POL, ≡Si–O–O–Si≡) may act as possible source of absorption. The addition of hydrogen can reduce the number of those defect levels in the middle of the band gap by shifting them to the band edges.

Friction is ubiquitous in daily life, from nanoscale machines to large engineering components. By probing the intricate interplay between system parameters and frictional behavior, scientists seek to unveil the underlying mechanisms that enable prediction and control of friction—an essential step toward carbon neutrality. Yet, reproducing frictional behavior in experiments is notoriously difficult. Here, we experimentally show that this challenge stems from the extreme sensitivity of tribological systems to tiny variations, e.g., in surface topography, typically presumed well controlled. Even after meticulous surface preparation to semiconductor industry standards and curtailing misalignment-induced oscillations, subtle variations remain and interact. In turn, such minute initial differences lead to statistically significant variations in friction and wear, giving rise to system-level chaotic behavior. Yet, by leveraging mid-scale features of surface topography and misalignment-induced oscillations—information often filtered out or overlooked—we established a predictive framework for high-friction regions under vastly different lubrication scenarios. While no single identified descriptor robustly predicts high friction, their combined occurrence provides strong predictive ability, which is further enhanced by machine learning.

Lubricated friction is a multiscale problem where molecular processes dictate the macroscopic response of the system. Traditional lubrication models rely on semiempirical constitutive relations, which become unreliable under extreme conditions. Here, we present a simulation framework that seamlessly couples molecular and continuum models for boundary lubrication without fixed-form constitutive laws. We train Gaussian process regression models as surrogates for predicting interfacial shear and normal stress in molecular dynamics simulations. An active learning algorithm ensures that our model adapts in scenarios where common constitutive laws fail, such as at layering transitions. We demonstrate our approach for nanoscale fluid flow over rough and heterogeneous surfaces, paving the way for accurate boundary lubrication simulations at experimental length and timescales.

Lubricated friction is a multiscale problem where molecular processes dictate the macroscopic response of the system. Traditional lubrication models rely on semi-empirical constitutive relations, which become unreliable under extreme conditions. Here, we present a simulation framework that seamlessly couples molecular and continuum models for boundary lubrication without fixed-form constitutive laws. We train Gaussian process regression models as surrogates for predicting interfacial shear and normal stress in molecular dynamics simulations. An active learning algorithm ensures that our model adapts in scenarios where common constitutive laws fail, such as near phase transitions. We demonstrate our approach for nanoscale fluid flow over rough and heterogeneous surfaces, paving the way for accurate boundary lubrication simulations at experimental length and time scales.

Mechanical metamaterials with high recoverable elastic energy density, which we refer to as high-enthalpy elastic metamaterials, can offer many enhanced properties, including efficient mechanical energy storage1,2, load-bearing capability, impact resistance and motion agility. These qualities make them ideal for lightweight, miniaturized and multi-functional structures3–8. However, achieving high enthalpy is challenging, as it requires combining conflicting properties: high stiffness, high strength and large recoverable strain9–11. Here, to address this challenge, we construct high-enthalpy elastic metamaterials from freely rotatable chiral metacells. Compared with existing non-chiral lattices, the non-optimized chiral metamaterials simultaneously maintain high stiffness, sustain larger recoverable strain, offer a wider buckling plateau, improve the buckling strength by 5–10 times, enhance enthalpy by 2–160 times and increase energy per mass by 2–32 times. These improvements arise from torsional buckling deformation that is triggered by chirality and is absent in conventional metamaterials. This deformation mode stores considerable additional energy while having a minimal impact on peak stresses that define material failure. Our findings identify a mechanism and provide insight into the design of metamaterials and structures with high mechanical energy storage capacity, a fundamental and general problem of broad engineering interest. High-enthalpy elastic metamaterials constructed from freely rotatable chiral metacells have high stiffness, large recoverable strain and improved buckling strength.

A gas turbine (GT) operating in a renewable-integrated grid is subjected to repeated start-stop cycles and quick load ramps. Such conditions highlight a risk of potential increase of cyclic damage in its critical rotating components like the turbine blades. A multiyear government-funded project is in progress to evaluate the low cycle fatigue (LCF) behavior of a cast blade material with defects. The aim is to develop a probabilistic fatigue crack nucleation life model. Strain-controlled LCF tests were conducted on defective and defect-free flat and round specimens extracted from cast MAR-M247 GT blades [1, 2]. As the third in a continuum of publications, this paper investigated the use of the so-called IBESS model [3] as a deterministic base for a proposed probabilistic framework. Key fatigue and fracture mechanics concepts were briefly reviewed for a better understanding, followed by a detailed description of the IBESS modification of the NASGRO [4] crack growth equation. The model was applied on the data generated from the LCF tests. While the model overestimated the predictions of cycles to crack nucleation for most specimens, it showed promise for further improvements. Future work is expected to define an appropriate failure criterion and achieve better corrections for the size and geometry of both the crack and the specimen.

A probabilistic model for quantifying the number of load cycles for crack nucleation at forging flaws in turbine rotor disks has been further developed [1]. This new fracture mechanics-based approach adequately describes the crack nucleation life. The model employs the range of plasticity-corrected stress intensity factor (Delta K-J) as the crack driving force correlating with crack nucleation cycles. Two different approaches for the calculation of Delta K-J are implemented and compared: I) The analytical solution calculates the stress intensity factor (K) and the plastic limit load based on flaw morphologies, types, boundary conditions, and material properties. Here, the failure assessment diagram (FAD) is considered to account for plasticity effects. II) The finite-element method is used to derive Delta K-J from the elastic-plastic J-integral. In the elastic-plastic finite element approach, a mesh convergence study was performed to reduce the effect of the element type and sizes on the numerical solution. As expected, it turns out that the numerical approach improves the accuracy of results due to the limited analytical validity ranges. Subsequently, a fracture mechanics-based crack nucleation model is developed by applying the numerically determined Delta K-J correlating with the experimental crack nucleation cycles. The numerical crack nucleation model shows conservative results compared to the analytical model. Furthermore, a probabilistic framework is proposed for both analytical and numerical crack nucleation models. An approach of integrating the crack nucleation models into the existing crack propagation model under the probabilistic framework is introduced.

This study investigates the effects of varying environmental conditions on the interfacial properties of carbon fiber-reinforced polyamide 6 (CF-PA6). The primary focus is the impact of temperature and humidity on the Interfacial Shear Strength (IFSS), debonding fracture toughness, and surface-specific work of friction. The study reveals that caused by polymer swelling both temperature and humidity lead to a relaxation of the radial residual stress within the interface and a subsequent reduction in IFSS. Notably, the effects of these factors appear to be superimposed up to the debonding of the fiber-matrix interface. Furthermore, while the debonding fracture toughness also follows a declining trend with an increase in both environmental factors, it displays non-linear characteristics, implying a coupled effect between temperature and humidity. The study also identifies that humidity alone significantly decreases the surface-specific work of friction, irrespective of the surrounding temperature, so that after debonding a simple superposition is not feasible. To ensure precise results, a microscale climate chamber was developed using the principle of deliquescence to maintain a constant relative humidity during testing. The findings offer valuable insights into the performance of CF-PA6 under varying environmental conditions, informing potential improvements in its design and application.

Metamaterials can be engineered with tunable bandgaps to adapt to dynamic and complex environments, particularly for controlling elastic waves and vibration. However, achieving wide-range, seamless, reversible, in-situ and robust tunability remains challenging and often impractical due to limitations in bandgap mechanisms and design principles. Here, we introduce gear-based metamaterials with unprecedented bandgap tunability. Our approach leverages Taiji planetary gear systems as variable-frequency local resonators, which allows the metamaterial to seamlessly modulate its bandgap's center frequency by 3-7 times (e.g. shifting from 250-430 Hz to 1400-2000 Hz), surpassing existing methods. Notably, this is achieved without pre-deformation or major changes to its static stiffness in the wave propagation direction, ensuring robust in-situ tunability and smooth control even under heavy static loads. This enables adaptable wave manipulation for versatile smart platforms.

The pin-on-disc test is a widely employed method for investigating the friction and wear performance of materials in conformal contact. In a typical pin-on-disc system, self-aligning pin holders are frequently utilized to ensure proper surface contact. This study reveals that in such a setup, pin inclination has a significant impact on test reliability, particularly under oil-lubricated conditions, which may overweight the influence of other parameters such as roughness or texture elements. Utilizing in-situ measurements, we captured the dynamic changes in pin inclination during rotational sliding. Our findings indicate that the pin inclination varies with sliding speed, showing a pitch angle difference of approximately 0.01°as the speed decreases from 2 m/s to 0.04 m/s in our test setup. Importantly, a robust correlation was identified between the friction coefficient and pin inclination, which is supported by the numerical investigation. This study underscores concerns regarding the test reliability of pin-on-disc tribometers, prompting a reconsideration of the assumptions associated with self-aligning pin holders in such experimental configurations.

This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain-specific successes and the development of specialized digital data spaces. There is an evident and increasing need for standardization across various subdomains to support science data exchange across entities. The MaterialDigital Initiative, funded by the German Federal Ministry of Education and Research, takes on a key role in this context, fostering collaborative efforts to establish a unified materials data space. The implementation of digital workflows and Semantic Web technologies, such as ontologies and knowledge graphs, facilitates the semantic integration of heterogeneous data and tools at multiple scales. Central to this effort is the prototyping of a knowledge graph that employs application ontologies tailored to specific data domains, thereby enhancing semantic interoperability. The collaborative approach of the Initiative's community provides significant support infrastructure for understanding and implementing standardized data structures, enhancing the efficiency of data-driven processes in materials development and discovery. Insights and methodologies developed via the MaterialDigital Initiative emphasize the transformative potential of ontology-based approaches in materials science, paving the way toward simplified integration into a unified, consolidated data space of high value.

This study presents a novel approach for investigating the shrinkage dynamics of 3D-printed nanoarchitectures during isothermal pyrolysis, utilizing in situ electron microscopy. For the first time, the temporal evolution of 3D structures is tracked continuously until a quasi-stationary state is reached. By subjecting the 3D objects to different temperatures and atmospheric conditions, significant changes in the resulting kinetic parameters and morphological textures of the 3D objects are observed, particularly those possessing varying surface-to-volume ratios. Its results reveal that the effective activation energy required for pyrolysis-induced morphological shrinkage is approximately four times larger under vacuum conditions than in a nitrogen atmosphere (2.6 eV vs. 0.5-0.9 eV, respectively). Additionally, a subtle enrichment of oxygen on the surfaces of the structures for pyrolysis in nitrogen is found through a postmortem electron energy loss spectroscopy study, differentiating the vacuum pyrolysis. These findings are examined in the context of the underlying process parameters, and a mechanistic model is proposed. As a result, understanding and controlling pyrolysis in 3D structures of different geometrical dimensions not only enables precise modification of shrinkage and the creation of tensegrity structures, but also promotes pyrolytic carbon development with custom architectures and properties, especially in the field of carbon micro- and nano-electromechanical systems.

While in situ experiments are gaining importance for the (mechanical) assessment of metamaterials or materials with complex microstructures, imaging conditions in such experiments are often challenging. The lab-based computed tomography system Xradia 810 Ultra allows for the in situ (time-lapsed) mechanical testing of samples. However, the in situ loading setup of this system limits the image acquisition angle to 140°. For low contrast polymeric materials, this limited acquisition angle leads to regions of low information gain, thus preventing an accurate reconstruction of the data using a filtered back projection algorithm resulting in erroneous microstructures. Here, we demonstrate how the information gain can be improved by selecting an appropriate position of the sample. A low contrast polymeric tetrahedral microlattice sample and a structured sample with specific markers, both scanned over 140° and 180°, demonstrate that the missing structural details in the 140° reconstruction are limited to an angular wedge of about 20°. Depending on the sample geometry and microstructure, applying simple strategies for the in situ experiments allows accurate reconstruction of the data. For the tetrahedral microlattice, a simple rotation of the sample by 90° rotates all relevant surfaces by about 30° to the original illumination direction, creating a more even X-ray illumination for all the projections, thus providing enough X-ray absorption for an accurate reconstruction of the geometry.

Although continuum theories have been proven quite robust to describe confined fluid flow at molecular length scales, molecular dynamics (MD) simulations reveal mechanistic insights into the interfacial dissipation processes. Most MD simulations of confined fluids have used setups in which the lateral box size is not much larger than the gap height, thus breaking thin-film assumptions usually employed in continuum simulations. Here, we explicitly probe the long wavelength hydrodynamic correlations in confined simple fluids with MD and compare to gap-averaged continuum theories as typically applied in e.g. lubrication. Relaxation times obtained from equilibrium fluctuations interpolate between the theoretical limits from bulk hydrodynamics and continuum formulations with increasing wavelength. We show how to exploit this characteristic transition to measure viscosity and slip length in confined systems simultaneously from equilibrium MD simulations. Moreover, the gap-averaged theory describes a geometry-induced dispersion relation that leads to overdamped sound relaxation at large wavelengths, which is confirmed by our MD simulations. Our results add to the understanding of transport processes under strong confinement and might be of technological relevance for the design of nanofluidic devices due to the recent progress in fabrication methods.