SEARCH · Engineering Papers

Results for “small scale”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Analysis of scale-dependent kinetic and potential energy in sheared, stably stratified turbulence

Budgets of turbulent kinetic energy (TKE) and turbulent potential energy (TPE) at different scales $\ell$ in sheared, stably stratified turbulence are analysed using a filtering approach. Competing effects in the flow are considered, along with the physical mechanisms governing the energy fluxes between scales, and the budgets are used to analyse data from direct numerical simulation at buoyancy Reynolds number $Re_b=O(100)$ . The mean TKE exceeds the TPE by an order of magnitude at the large scales, with the difference reducing as $\ell$ is decreased. At larger scales, buoyancy is never observed to be positive, with buoyancy always converting TKE to TPE. As $\ell$ is decreased, the probability of locally convecting regions increases, though it remains small at scales down to the Ozmidov scale. The TKE and TPE fluxes between scales are both downscale on average, and their instantaneous values are correlated positively, but not strongly so, and this occurs due to the different physical mechanisms that govern these fluxes. Moreover, the contributions to these fluxes arising from the sub-grid fields are shown to be significant, in addition to the filtered scale contributions associated with the processes of strain self-amplification, vortex stretching and density gradient amplification. Probability density functions (PDFs) of the $Q,R$ invariants of the filtered velocity gradient are considered and show that as $\ell$ increases, the sheared-drop shape of the PDF becomes less pronounced and the PDF becomes more symmetric about $R=0$ .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Magnetic reconnection in the era of exascale computing and multiscale experiments

Astrophysical plasmas have the remarkable ability to preserve magnetic topology, which inevitably gives rise to the accumulation of magnetic energy within stressed regions including current sheets. This stored energy is often released explosively through the process of magnetic reconnection, which produces a reconfiguration of the magnetic field, along with high-speed flows, thermal heating and nonthermal particle acceleration. Either collisional or kinetic dissipation mechanisms are required to overcome the topological constraints, both of which have been predicted by theory and validated with in situ spacecraft observations or laboratory experiments. However, major challenges remain in understanding magnetic reconnection in large systems, such as the solar corona, where the collisionality is weak and the kinetic scales are vanishingly small in comparison with macroscopic scales. The plasmoid instability or formation of multiple plasmoids in long, reconnecting current sheets is one possible multiscale solution for bridging this vast range of scales, and new laboratory experiments are poised to study these regimes. In conjunction with these efforts, we anticipate that the coming era of exascale computing, together with the next generation of observational capabilities, will enable new progress on a range of challenging problems, including the energy build-up and onset of reconnection, partially ionized regimes, the influence of magnetic turbulence and particle acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Microstructure Scale Lithium-Ion Battery Modeling: Part II. On In-Plane Heterogeneities and the Mechanisms that Regulate Them

Li-ion batteries performance and degradation are typically modeled at the macroscopic scale, that is neglecting in-plane heterogeneities that can arise from non-uniform electrode microstructures. Herein, a microstructure scale electrochemical model is used to quantify the impact of microstructure heterogeneity on cell performance during fast charging. The model predicts the electrolyte and solid concentration in-plane standard deviation can reach, respectively, ≈200 mol·m −3 and 6–7 kmol·m −3 locally. Further, the intercalation current density in-plane relative standard deviation can reach extremely high values, around 100% in the cathode and well above 100% in the anode graphite. These denote highly non-uniform lithiation rates and material utilization within each slice of the microstructure along the cell thickness. Non-uniform curvatures, at the particle scale (surface roughness) and between particles (size distribution), were found to initiate these in-plane heterogeneities, while an OCP-induced mechanism subsequently regulates them. The present model provides new insights into small length scale heterogeneity impact on battery performance not available with standard macro-scale/P2D modeling.

25 ENERGY STORAGE↗

DOE OSTI2021

Strain Gradient Elasticity in SrTiO 3 Membranes: Bending versus Stretching

Young’s modulus determines the mechanical loads required to elastically stretch a material and also the loads required to bend it, given that bending stretches one surface while compressing the opposite one. Flexoelectric materials have the additional property of becoming electrically polarized when bent. The associated energy cost can additionally contribute to elasticity via strain gradients, particularly at small length scales where they are geometrically enhanced. Here, we present nanomechanical measurements of freely suspended SrTiO 3 crystalline membrane drumheads. In this work, we observe an unexpected nonmonotonic thickness dependence of Young’s modulus upon small deflections. Furthermore, the modulus inferred from a predominantly bending deformation is three times larger than that of a predominantly stretching deformation for membranes thinner than 20 nm. In this regime we extract a strain gradient elastic coupling of ~2.2 μN, which could be used in new operational regimes of nanoelectro-mechanics.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Evaluating Lyman- α constraints for general dark-matter velocity distributions: Multiple scales and cautionary tales

One of the most important observational constraints on possible models of dark-matter physics exploits the Lyman-α absorption spectrum associated with photons traversing the intergalactic medium. Because these data allow us to probe the linear matter power spectrum with great accuracy down to relatively small distance scales, finding ways of accurately evaluating such Lyman-α constraints across large classes of candidate models of dark-matter physics is of paramount importance. While such Lyman-α constraints have been evaluated for dark-matter models that give rise to relatively simple dark-matter velocity distributions, more complex models—particularly those whose dark-matter velocity distributions stretch across multiple scales—have recently been receiving increasing attention. In this paper, we undertake a study of the Lyman-α constraints associated with general dark-matter velocity distributions. Although such Lyman-α constraints are difficult to evaluate in principle, in practice there currently exist two classes of methods in the literature through which such constraints can be recast into forms which are easier to evaluate and which therefore allow a more rapid determination of whether a given dark-matter model is ruled in or out. Accordingly, we utilize both of these recasts in order to determine the Lyman-α bounds on different classes of dark-matter velocity distributions. Here we also develop a general method by which the results of these different recasts can be compared. For relatively simple dark-matter velocity distributions, we demonstrate that these two classes of recasts tend to align and give similar results. However, we find that the situation is far more complex for distributions involving multiple velocity scales: while these two classes of recasts continue to yield similar results within certain regions of parameter space, they nevertheless yield dramatically different results within precisely those regions of parameter space which are likely to be phenomenologically relevant. This, then, serves as a cautionary tale regarding the use of such recasts for complex dark-matter velocity distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Response of Extreme Rainfall to Atmospheric Warming and Wetting: Implications for Hydrologic Designs Under a Changing Climate

Understanding the processes of rainfall extremes and their response to anthropogenic climate change is pivotal for improved adaptation of unprecedented flood hazards around the world. Here we take the record-breaking 20 July 2021 storm over central China as an example. We investigate the response of this particular storm to atmospheric warming (i.e., increase in air temperature) and wetting (i.e., increase in atmospheric moisture content) based on a series of convection-permitting model simulations. Our results show non-monotonic changes of the space-time rainfall variability to either increased temperature or atmospheric moisture content. The most extreme rain rate is produced when relative humidity is increased by 20~40 % or temperature is increased by less than 2°C. The non-monotonic rainfall response is more clearly revealed at fine spatial (100-1000 km 2 ) and temporal scales (less than 6 hours) rather than over the entire domain (~10 4 km 2 ) and aggregated over the storm duration (around two days). This is mainly attributable to the distinct feedbacks from atmospheric dynamics (i.e., moisture convergence and interaction with regional topography) rather than regulated by thermodynamic changes alone. Furthermore, atmospheric warming poses notable changes in the vertical structure of storm cells, contributing to reduced areal reduction factors at small spatial scales and short durations, while atmospheric wetting additionally modifies storm evolution properties. Our modeling analyses challenge the existing practices for hydrologic designs under a changing climate, highlighting particular vulnerability for cities or small basins to short-duration rainfall extremes and the resultant flash flood hazards.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering

Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

DOE OSTI2025

Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells

Printed metal halide perovskites can enable rapid, roll-to-roll manufacturing of a broad class of optoelectronics—flexible solar cells and imagers among them—while promising cost and speed advantages over incumbent silicon. However, though current methods offer high throughput and patterning capabilities, perovskite films’ spatial heterogeneity remains a challenge for large-area devices. Here, a spatial-uniformity-driven Bayesian optimization (BO) approach is leveraged to accelerate the development of printed perovskite solar cells and improve large-area device performance. Using a BO surrogate model, a 6D design space of ink chemistry and printing physics is explored via extensive iterative experimentation (≈100) informed by an objective function capturing spatial photoluminescence (PL) variance. It is discovered that optimizing for uniformity drives rapid advances in photovoltaic performance, yielding ≈20% power conversion efficiency (PCE) for small area (0.134 cm 2 ) devices and > 16% for large area (1 cm 2 ) devices. This machine-learning approach simultaneously enables rheological comparison of ink formulations that accelerate the leveling of Saffman-Taylor artifacts and improve film uniformity. Here, this showcases uniformity-driven BO as an efficient approach for uncovering the key printing physics and mitigating spatial heterogeneity to enable device scaling beyond small cell areas.

14 SOLAR ENERGY↗

DOE OSTI2022

Autonomous Energy Management Software System for Small Commercial Buildings in Support of Decarbonization (Abstract)

The primary goal for the project is to develop and validate an autonomous energy management software (AEMS) system that will continuously optimize small commercial building operations by minimizing energy consumption and cost, providing a solution for maximizing decarbonization benefits from electrification of buildings. The work will leverage vast experience of Pacific Northwest National Laboratory (PNNL) research and development staff who have over two decades of experience in developing and successfully transferring software technologies to the private sector. This solution will be jointly developed with Intellimation LLC who plans to use it to scale their building energy efficiency offering. The project plan will include collaboratively working with Intellimation to package a set of solutions into the AEMS system, validate and demonstrate their capability, and value proposition through field demonstrations. If the deployment of the AEMS system optimizes RTUs’ set points, schedules, setbacks and optimal start and results in energy consumption reduction of 20%, the technical potential savings is approximately 675 trillion Btus of site energy savings and 2,000 trillion Btus of source energy. It will also result in carbon reductions of approximately 2.4 MMTCO2 and contribute to the climate change mitigation plans of many cities and states across the United States. Additional cost savings and emissions reduction are possible from management of peak electricity demand. The primary outcome will be an AEMS system that can be deployed at scale on small commercial buildings to improve operating efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Low-Platinum Group (PGM) Metal Catalysts (Final Report)

High catalyst loadings and relatively high over-potential losses have limited the commercial viability of direct methanol fuel cells (DMFCs). Platinum-based catalysts are used in DMFCs with a loading of 4.5 mg cm-2; the catalyst layer is a significant contributor to the membrane electrode assembly (MEA) cost, which accounts for 60% of the system cost. The large-scale commercial viability of DMFCs is dependent on a significant (~50%) cost reduction. If these cost goals can be reached, the current market can be extended from 100's of units to 10,000's of units. Currently, Oorja is using a platinum-ruthenium catalyst for methanol oxidation, but does not have access to a supplier able to develop low-platinum group (PGM) metal catalysts to reach DMFC cost reduction targets. Oorja has recently developed a small lab scale capability in fabrication and testing of DMFC membrane electrode assemblies (MEAs), but does not have access to synthesis and characterization of advanced electrocatalysts. The materials, equipment, and expertise at the National Renewable Energy Laboratory (NREL) are of significant value to Oorja. NREL recently develop platinum-nickel nanowires as catalysts in hydrogen fuel cells. These materials have also shown promise in DMFC applications as a potential replacement for standard platinum-ruthenium catalysts; in ex-situ testing, these materials have shown one order of magnitude higher mass activity and can avoid ruthenium crossover contamination effects. These combined properties are exceptionally appealing to Oorja, and can result in significantly decreasing the capital costs of DMFCs.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

Dark Energy Survey Year 6 results: Galaxy-galaxy lensing

Here, we present galaxy-galaxy lensing measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering 4031 deg 2 and used in the DES Y6 3×2 pt cosmological analysis. We use the Maglim++ lens sample, containing ∼9 million galaxies divided into six redshift bins, and the Metadetection source catalog, including ∼140 million galaxies divided into four redshift bins. The mean tangential shear signal achieves a total signal-to-noise ratio (S/N) of 173, corresponding to a 17% improvement over DES Y3. After applying the scale cuts used in the cosmological analysis, with 𝑅 min =6 Mpc/ℎ (4 Mpc/ℎ) for the linear (nonlinear) galaxy-bias model, the S/N is reduced to 75 (90). A comprehensive suite of validation tests demonstrates that the measurement is robust against observational and astrophysical systematics at the statistical precision required for the DES Y6 analysis. Although not used in the main cosmological analysis, we extract high signal-to-noise geometric shear-ratio measurements from the galaxy-galaxy lensing signal on small angular scales. These measurements provide an internal consistency check on the photometric redshift distributions and shear calibration used in the 3 ×2 pt analysis.

cosmological parameters↗

DOE OSTI2026

Dark Energy Survey Year 6 Results: Galaxy-galaxy lensing

We present galaxy--galaxy lensing (GGL) measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering $4031\,\mathrm{deg}^2$ and used in the DES Y6 $3\times2$pt cosmological analysis. We use the MagLim++ lens sample, containing $\sim 9$ million galaxies divided into six redshift bins, and the Metadetection source catalog, including $\sim 140$ million galaxies divided into four redshift bins. The mean tangential shear signal achieves a total signal-to-noise ratio (S/N) of $173$, corresponding to a $17\%$ improvement over DES Y3. After applying the scale cuts used in the cosmological analysis, with $R_{\min}=6\,\mathrm{Mpc}/h$ ($4\,\mathrm{Mpc}/h$) for the linear (nonlinear) galaxy-bias model, the S/N is reduced to $75$ (90). A comprehensive suite of validation tests demonstrates that the measurement is robust against observational and astrophysical systematics at the statistical precision required for the DES Y6 analysis. Although not used in the main cosmological analysis, we extract high--signal-to-noise geometric shear-ratio measurements from the galaxy--galaxy lensing signal on small angular scales. These measurements provide an internal consistency check on the photometric redshift distributions and shear calibration used in the $3\times2$pt analysis.

Giannini, G. [Barcelona, IEEC; Chicago U., KICP; B↗

DOE OSTI2022

Back-to-back inclusive dijets in DIS at small x : Sudakov suppression and gluon saturation at NLO

Back-to-back dijet cross-sections in deeply inelastic scattering (DIS) at small xBj are suppressed by many-body multiple scattering and screening effects arising from gluon saturation at high parton densities. They are similarly sensitive in these kinematics to large Sudakov logarithms from soft gluon radiation. Uncovering novel physics in this DIS channel therefore requires understanding the interplay of the two phenomena. In this work, we compute the small $x_\text{Bj}$ inclusive dijet DIS cross-section in back-to-back kinematics at next-to-leading order (NLO) in the Color Glass Condensate effective field theory (CGC EFT). Our result includes, for the first time, all real and virtual NLO contributions to the impact factor. These include all Sudakov double and single logarithm contributions, as well as all other finite $\mathcal{O}(α_s)$ terms that contribute at this order. We demonstrate explicitly that resummations of small x and Sudakov logarithms can be performed simultaneously in the CGC EFT. This requires that the JIMWLK kernel for small x evolution of the Weizsäcker-Williams (WW) gluon distribution satisfies a kinematic constraint imposed by lifetime ordering of successive gluon emissions; the corresponding modifications to the kernel, corresponding to resummations of large double transverse logarithms, are precisely of the type required to stabilize JIMWLK evolution beyond leading logarithmicaccuracy. We compute the azimuthal harmonics of the NLO back-to-back distributions and show their sensitivity to both the unpolarized and linearly polarized WW gluon distributions. Finally, we discuss how TMD factorization is broken by an emergent saturation scale at small $x$.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Unconventional Catalytic Approaches to Ammonia Synthesis

Ammonia is a critically important industrial chemical and is largely responsible for sustaining the growing global population. To provide ammonia to underdeveloped regions and/or regions far from industrial production hubs, modular systems have been targeted and often involve unconventional production methodologies. These novel approaches for ammonia production can tap renewable resources at smaller scales located at the point of use, while decreasing the CO 2 footprint. Plasma-assisted catalysis and electrochemical ammonia synthesis have promise owing to their atmospheric pressure and low-temperature operation conditions and the ability to construct units at scales desired for modularization. Fundamental and applied studies are underway to assess these processes, although many unknowns remain. In this review, we discuss recent developments and opportunities for unconventional ammonia synthesis with a focus on plasma-stimulated systems.

42 ENGINEERING↗

DOE OSTI2022

Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed

Abstract Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys , varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140 km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0 gC m −2 yr −1 ) and higher net primary productivity (by 104.9 gC m −2 yr −1 ) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

From individual leaves to forest stands: importance of niche, distance decay, and stochasticity vary by ecosystem type and functional group for fungal community composition

Abstract Community assembly is influenced by environmental niche processes as well as stochastic processes that can be spatially dependent (e.g. dispersal limitation) or independent (e.g. priority effects). Here, we sampled senesced tree leaves as unit habitats to investigate fungal community assembly at two spatial scales: (i) small neighborhoods of overlapping leaves from differing tree species and (ii) forest stands of differing ecosystem types. Among forest stands, ecosystem type explained the most variation in community composition. Among adjacent leaves within stands, variability in fungal composition was surprisingly high. Leaf type was more important in stands with high soil fertility and dominated by differing tree mycorrhizal types (sugar maple vs. basswood or red oak), whereas distance decay was more important in oak-dominated forest stands with low soil fertility. Abundance of functional groups was explained by environmental factors, but predictors of taxonomic composition within differing functional groups were highly variable. These results suggest that fungal community assembly processes are clearest for functional group abundances and large spatial scales. Understanding fungal community assembly at smaller spatial scales will benefit from further study focusing on differences in drivers for different ecosystems and functional groups, as well as the importance of spatially independent factors such as priority effects.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Flaw-insensitive fracture of a micrometer-sized brittle metallic glass

Brittle materials, such as oxide glasses, are usually very sensitive to flaws, giving rise to a macroscopic fracture strength that is much lower than that predicted by theory. The same applies to metallic glasses (MGs), with the important difference that these glasses can exhibit certain plastic strain prior to catastrophic failure. Here we consider the strongest metallic alloy known, a ternary Co 55 Ta10B 35 MG. In this work, we show that this macroscopically brittle glass is flaw-insensitive at the micrometer scale. This discovery emerges when testing pre-cracked specimens with self-similar geometries, where the fracture stress does not decrease with increasing pre-crack size. The fracture toughness of this ultra-strong glassy alloy is further shown to increase with increasing sample size. Both these findings deviate from our classical understanding of fracture mechanics, and are attributed to a transition from toughness-controlled to strength-controlled fracture below a critical sample size.

36 MATERIALS SCIENCE↗