Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “unpredictability”

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.

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

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Active Plasmonics and Active Chiral Plasmonics through Orientation-Dependent Multipolar Interactions

While most active plasmonic efforts focus on responsive metamaterials to modulate optical response, we present a simple alternative based on applied orientation control that can likely be implemented for many passive plasmonic materials. Passive plasmonic motifs are simpler to prepare but cannot be altered postfabrication. Here, we show that such systems can be easily manipulated through substrate orientation control to generate both active plasmonic and active chiral plasmonic responses. Using gold nanocrescents as our model platform, we demonstrate tuning of optical extinction from -21% to +36% at oblique incidence relative to normal incidence. Variation of substrate orientation in relation to incident polarization is also demonstrated to controllably switch chiroptical handedness (e.g., Δg = ± 0.55). These active plasmonic responses arise from the multipolar character of resonant modes. In particular, we correlate magnetoelectric and dipole–quadrupole polarizabilities with different light-matter orientation-dependence in both near- and far-field localized surface plasmon activity. Additionally, the attribution of far-field optical response to higher-order multipoles highlights the sensitivity offered by these orientation-dependent characterization techniques to probe the influence of localized electromagnetic field gradients on a plasmonic response. The sensitivity afforded by orientation-dependent optical characterization is further observed by the manifestation in both plasmon and chiral plasmon responses of unpredicted structural nanocrescent variance (e.g., left- and right-tip asymmetry) not physically resolved through topographical imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks

We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydrox-amate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivi-ty, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our stud-ies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corre-sponding to a 4% volumetric change within ≤1 deg C and a hysteresis window of ~10 deg C. Here, this highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular con-struction strategies in discovering tunable–and unpredictable–material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Active Site Dynamics in Molybdenum-Based Silica-Supported Olefin Metathesis Catalysts: Site Renewal and Decay Beyond the Chauvin Cycle

Heterogeneous olefin metathesis catalysts exhibit low active site densities and unpredictable kinetics due to dynamic active site formation and decay processes. Here, in this study, we establish a quantitative framework that captures active site generation, renewal, and decay in olefin metathesis over silica-supported molybdenum oxide catalysts, enabling a mechanistic explanation of catalytic behavior and strategies to achieve high, stable activity. Steady-state active site titrations reveal that 2,3-dimethyl-butene isomers (4MEs) cofeeding increases active site density by up to 4.3-fold, directly correlating with enhanced metathesis rates. Spectroscopic studies demonstrate that 4MEs facilitate Mo(VI) reduction to Mo(IV) and interact strongly with surface Si–OH groups, generating labile protons that promote active site formation via a 1,2-proton shift mechanism. Kinetic modeling indicates that ethylene acts as a decay promoter, shifting kinetic control away from the Chauvin cycle and suppressing metathesis activity. Comparative studies on catalysts with varying Mo loading reveal that promotion is most effective for dispersed molybdate species, with a decline at higher Mo loadings. These findings provide a unified mechanistic framework for heterogeneous olefin metathesis, offering new strategies to enhance active site accessibility, mitigate deactivation, and optimize catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Medium‐Sized Paleo‐Tsunami Reconstruction by a Deep Neural Network Processing Sedimentary Deposits

Abstract Reconstructing the magnitude and recurrence time of tsunamis, one of the most destructive and unpredictable natural hazards impacting coastal communities, is essential. While major tsunamis are the most studied due to their disastrous impact, small/medium tsunamis (SMTs) are much more frequent and can still significantly impact the coast. Therefore, SMTs potentially provide an extensive archive of information preserved in the geological record. Analyzing the deposits of small/medium paleo‐tsunamis (SMPTs) opens a window into when their direct observation was unavailable. However, deposits of SMPTs are often degraded, traditional sediment deposition inversion models might fail. Recent research has shown that Deep Neural Networks (DNN) can effectively reconstruct the flow conditions of major tsunamis from their deposits. We evaluate the effectiveness of this approach in reconstructing the characteristics of a recent medium size tsunami (2006 Java) and of a medium paleo‐tsunami (1929 Grand Banks). We successfully reconstruct the flow characteristics of the 2006 Java event and show that an inversion of comparable quality is possible for the 1929 Grand Banks tsunami, despite greater uncertainties due to the deposit degradation. Our research shows that Machine Learning has the potential to unseal the meaning of data of thousands SMPTs.

Batubo, P.↗
DOE OSTI2026

Multi‐Sensor Trajectory Reconstruction of the 24 April 2025 Alaska Fireball and Implications for Planetary Defense

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. Here, the unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals, with fragmentation source locations further guiding the identification of Doppler weather radar signatures of a meteorite fall. Incorporation of a radar-derived terminal point yielded a final trajectory solution, which agreed closely with an independent optical trajectory solution from video analysis. The reconstructed entry parameters from seismoacoustic analysis indicate a velocity of 25.3 km/s, an entry angle of 19°, and an energy release of ∼38 t TNT equivalent. Assuming a chondritic composition, the pre-entry object diameter was ∼0.7 m. Using orbital parameters from the optical solution, we estimate meteoroid composition as most likely an L-type ordinary chondrite. The event occurred in the sub-Arctic, where space-based optical systems face challenges in detection, demonstrating the critical role of dense ground-based seismoacoustic networks in characterizing high-latitude atmospheric entries. This uniquely well-recorded event demonstrates the capability of dense seismoacoustic networks to constrain bolide trajectories, energetics, and fragmentation, with radar and optical data providing critical confirmation and complementary perspectives. These results bridge the methodological gap between planetary-defense monitoring of natural impactors and space-traffic analyses of artificial reentries, illustrating how multi-sensor integration can deliver calibration-grade trajectories even for unpredicted events.

Fireball↗
DOE OSTI2020

A joint role for forced and internally-driven variability in the decadal modulation of global warming

Despite the observed monotonic increase in greenhouse-gas concentrations, global mean temperature displays important decadal fluctuations typically attributed to both external forcing and internal variability. Here, we provide a robust quantification of the relative contributions of anthropogenic, natural, and internally-driven decadal variability of global mean sea surface temperature (GMSST) by using a unique dataset consisting of 30-member large initial-condition ensembles with five Earth System Models (ESM-LE). We present evidence that a large fraction (~29–53%) of the simulated decadal-scale variance in individual timeseries of GMSST over 1950–2010 is externally forced and largely linked to the representation of volcanic aerosols. Comparison with the future (2010–2070) period suggests that external forcing provides a source of additional decadal-scale variability in the historical period. Given the unpredictable nature of future volcanic aerosol forcing, it is suggested that a large portion of decadal GMSST variability might not be predictable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Visualization and validation of twin nucleation and early-stage growth in magnesium

The abrupt occurrence of twinning when Mg is deformed leads to a highly anisotropic response, making it too unreliable for structural use and too unpredictable for observation. Here, we describe an in-situ transmission electron microscopy experiment on Mg crystals with strategically designed geometries for visualization of a long-proposed but unverified twinning mechanism. Combining with atomistic simulations and topological analysis, we conclude that twin nucleation occurs through a pure-shuffle mechanism that requires prismatic-basal transformations. Also, we verified a crystal geometry dependent twin growth mechanism, that is the early-stage growth associated with instability of plasticity flow, which can be dominated either by slower movement of prismatic-basal boundary steps, or by faster glide-shuffle along the twinning plane. The fundamental understanding of twinning provides a pathway to understand deformation from a scientific standpoint and the microstructure design principles to engineer metals with enhanced behavior from a technological standpoint.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controlling process instability for defect lean metal additive manufacturing

The process instabilities intrinsic to the localized laser-powder bed interaction cause the formation of various defects in laser powder bed fusion (LPBF) additive manufacturing process. Particularly, the stochastic formation of large spatters leads to unpredictable defects in the as-printed parts. Here we report the elimination of large spatters through controlling laser-powder bed interaction instabilities by using nanoparticles. The elimination of large spatters results in 3D printing of defect lean sample with good consistency and enhanced properties. We reveal that two mechanisms work synergistically to eliminate all types of large spatters: (1) nanoparticle-enabled control of molten pool fluctuation eliminates the liquid breakup induced large spatters; (2) nanoparticle-enabled control of the liquid droplet coalescence eliminates liquid droplet colliding induced large spatters. The nanoparticle-enabled simultaneous stabilization of molten pool fluctuation and prevention of liquid droplet coalescence discovered here provide a potential way to achieve defect lean metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Realizing symmetry-guaranteed pairs of bound states in the continuum in metasurfaces

Abstract Bound states in the continuum (BICs) have received significant attention for their ability to enhance light-matter interactions across a wide range of systems, including lasers, sensors, and frequency mixers. However, many applications require degenerate or nearly degenerate high-quality factor ( Q ) modes, such as spontaneous parametric down conversion, non-linear four-wave mixing, and intra-cavity difference frequency mixing for terahertz generation. Previously, degenerate pairs of bound states in the continuum (BICs) have been created by fine-tuning the structure to engineer the degeneracy, yielding BICs that respond unpredictably to structure imperfections and material variations. Instead, using a group theoretic approach, we present a design paradigm based on six-fold rotational symmetry ( C 6 ) for creating degenerate pairs of symmetry-protected BICs, whose frequency splitting and Q -factors can be independently and predictably controlled, yielding a complete design phase space. Using a combination of resonator and lattice deformations in silicon metasurfaces, we experimentally demonstrate the ability to tune mode spacing from 2 nm to 110 nm while simultaneously controlling Q -factor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Encoding multistate charge order and chirality in endotaxial heterostructures

Abstract High-density phase change memory (PCM) storage is proposed for materials with multiple intermediate resistance states, which have been observed in 1 T -TaS 2 due to charge density wave (CDW) phase transitions. However, the metastability responsible for this behavior makes the presence of multistate switching unpredictable in TaS 2 devices. Here, we demonstrate the fabrication of nanothick verti-lateral H -TaS 2 /1 T -TaS 2 heterostructures in which the number of endotaxial metallic H -TaS 2 monolayers dictates the number of resistance transitions in 1 T -TaS 2 lamellae near room temperature. Further, we also observe optically active heterochirality in the CDW superlattice structure, which is modulated in concert with the resistivity steps, and we show how strain engineering can be used to nucleate these polytype conversions. This work positions the principle of endotaxial heterostructures as a promising conceptual framework for reliable, non-volatile, and multi-level switching of structure, chirality, and resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tunable stochastic memristors for energy-efficient encryption and computing

Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements – security (encryption) requires a source of unpredictability, while computing generally requires predictability. Each of these contrasting requirements presently necessitates distinct conventional Si-based hardware units with power-hungry overheads. This work demonstrates Cu 0.3 Te 0.7 /HfO 2 (‘CuTeHO’) ion-migration-driven memristors that satisfy the contrasting requirements. Under specific operating biases, CuTeHO memristors generate truly random and physically unclonable functions, while under other biases, they perform universal Boolean logic. Using these computing primitives, this work experimentally demonstrates a single system that performs cryptographic key generation, universal Boolean logic operations, and encryption/decryption. Circuit-based calculations reveal the energy and latency advantages of the CuTeHO memristors in these operations. This work illustrates the functional flexibility of memristors in implementing operations with varying component-level requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

True random number generation using the spin crossover in LaCoO 3

While digital computers rely on software-generated pseudo-random number generators, hardware-based true random number generators (TRNGs), which employ the natural physics of the underlying hardware, provide true stochasticity, and power and area efficiency. Research into TRNGs has extensively relied on the unpredictability in phase transitions, but such phase transitions are difficult to control given their often abrupt and narrow parameter ranges (e.g., occurring in a small temperature window). Here we demonstrate a TRNG based on self-oscillations in LaCoO 3 that is electrically biased within its spin crossover regime. The LaCoO 3 TRNG passes all standard tests of true stochasticity and uses only half the number of components compared to prior TRNGs. Assisted by phase field modeling, we show how spin crossovers are fundamentally better in producing true stochasticity compared to traditional phase transitions. As a validation, by probabilistically solving the NP-hard max-cut problem in a memristor crossbar array using our TRNG as a source of the required stochasticity, we demonstrate solution quality exceeding that using software-generated randomness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Abstract Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model. This severely limits the practical application of these models in systems with dynamics governed by important rare events, such as chemical reactions and diffusion. We present an adaptive Bayesian inference method for automating the training of interpretable, low-dimensional, and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations. Within an active learning framework, the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model. The method is applied to a range of single- and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency, while requiring a minimal amount of ab initio training data. We provide a fully open-source implementation of our method, as well as a procedure to map trained models to computationally efficient tabulated force fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins

Abstract Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.

Mathematical & Computational Biology↗
DOE OSTI2023

Increased exposure of coastal cities to sea-level rise due to internal climate variability

Adaptation to future sea-level rise is based on projections of continuously improving climate models. These projections are accompanied by inherent uncertainties, including those due to internal climate variability (ICV). The ICV arises from complex and unpredictable interactions within and between climate-system components, rendering its impact irreducible. Although neglecting this uncertainty can lead to an underestimation of future sea-level rise, its estimation and impacts have not been fully explored. Combining the Community Earth System Model version 1 Large Ensemble experiments with power-law statistics, we show that, by 2100, if the ICV uncertainty reaches its upper limit, new sea-level-rise hotspots would appear in Southeast Asian megacities (Chennai, Kolkata, Yangon, Bangkok, Ho Chi Minh City and Manila), in western tropical Pacific Islands and the Western Indian Ocean. Here, the better the ICV uncertainty is taken into account and correctly estimated, the more effective adaptation strategies can be elaborated with confidence and actions to follow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantifying the impacts of climate change and extreme climate events on energy systems

Climate induced extreme weather events and weather variations will affect both the demand of energy and the resilience of energy supply systems. The specific potential impact of extreme events on energy systems has been difficult to quantify due to the unpredictability of future weather events. In this work, we develop a stochastic-robust optimization method to consider both low impact variations and extreme events. Applications of the method to 30 cities in Sweden, by considering 13 climate change scenarios, reveal that uncertainties in renewable energy potential and demand can lead to a significant performance gap (up to 34% for grid integration) brought by future climate variations and a drop in power supply reliability (up to 16%) due to extreme weather events. Finally, appropriate quantification of the climate change impacts will ensure robust operation of the energy systems and enable renewable energy penetration above 30% for a majority of the cities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accurate computational design of three-dimensional protein crystals

Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here, in this study, we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predator mass mortality events restructure food webs through trophic decoupling

Predators have a key role in structuring ecosystems. However, predator loss is accelerating globally, and predator mass-mortality events (MMEs)—rapid large-scale die-offs—are now emblematic of the Anthropocene epoch. Owing to their rare and unpredictable nature, we lack an understanding of how MMEs immediately impact ecosystems. Past predator-removal studies may be insufficient to understand the ecological consequences of MMEs because, in nature, dead predators decompose in situ and generate a resource pulse, which could alter ensuing ecosystem dynamics by temporarily enhancing productivity. Here we experimentally induce MMEs in tritrophic, freshwater lake food webs and report ecological dynamics that are distinct from predator losses or resource pulses alone, but that can be predicted from theory. MMEs led to the proliferation of diverse consumer and producer communities resulting from weakened top-down predator control and stronger bottom-up effects through predator decomposition. In contrast to predator removals alone, enhanced primary production after MMEs dampened the consumer community response. As a consequence, MMEs generated biomass dynamics that were most similar to those of undisturbed systems, indicating that they may be cryptic disturbances in nature. These biomass dynamics led to trophic decoupling, whereby the indirect beneficial effects of predators on primary producers are lost and later materialize as direct bottom-up effects that stimulate primary production amid intensified herbivory. Furthermore, these results reveal ecological signatures of MMEs and demonstrate the feasibility of forecasting novel ecological dynamics arising with intensifying global change.

Food webs↗