Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “exclusive”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Crimean-Congo hemorrhagic fever survivors elicit protective non-neutralizing antibodies that target 11 overlapping regions on glycoprotein GP38

Crimean-Congo hemorrhagic fever virus can cause lethal disease in humans yet there are no approved medical countermeasures. Viral glycoprotein GP38, exclusive to Nairoviridae , is a target of protective antibodies and is a key antigen in preclinical vaccine candidates. Here, we isolate 188 GP38-specific antibodies from human survivors of infection. Competition experiments show that these antibodies bind across 5 distinct antigenic sites, encompassing 11 overlapping regions. Additionally, we show structures of GP38 bound with 9 of these antibodies targeting different antigenic sites. Although these GP38-specific antibodies are non-neutralizing, several display protective efficacy equal to or better than murine antibody 13G8 in two highly stringent rodent models of infection. Together, these data expand our understanding regarding this important viral protein and may inform the development of broadly effective CCHFV antibody therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Effect of a novel starch-based temperature rise inhibitor on cement hydration and microstructure development: The second peak study

Temperature rise inhibitor (TRI) modifies the exothermic process of cement hydration at early age and mitigates the buildup of cumulative heat, which sheds new light on solving the thermal cracking issue. After the main hydration peak, a broader “second peak” appears and brings the cumulative heat back to normal level within 7 days (for additions less than 0.15%). This study shows that the “second peak” can be attributed, almost exclusively, to C{sub 3}S hydration while triggered by C{sub 3}A hydration. In a pure C{sub 3}S system, the heat flow is depressed by TRI during the main hydration peak but never recovers after. In a monophase system composed of C{sub 3}S, C{sub 3}A and gypsum or a real cement paste, the ongoing precipitation of ettringite helps to pump out TRI polymer from the pore solution and eliminate the restriction on C-S-H nucleation. Afterwards, the precipitation of C-S-H accelerates again to form the “second peak”.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evidence of formation of an amorphous magnesium silicate (AMS) phase during alkali activation of (Na-Mg) aluminosilicate glasses

Highlights: • No hydrotalcite-group phase is formed as Al preferentially incorporates into zeolites. • Mg forms an amorphous Mg silicate (AMS) phase. • AMS is a more depolymerized phase when compared to Mg silicate hydrate (M-S-H). • High charge density of Mg effectively stabilizes depolymerized silicates in AMS phase. • Existence of AMS phase should be considered as possibility in Mg-rich AAMs. There is some ambiguity regarding the fate of Mg during the alkali activation of Mg-rich precursors within the broader field of alkali activated materials (AAMs). The present work addresses this issue by studying the reaction products in AAMs synthesized from (Na-Mg) aluminosilicate glasses. Here, instead of magnesium silicate hydrate (M-S-H) phase, Mg exclusively forms an amorphous magnesium silicate (AMS) phase. Compared to M-S-H, AMS is a more depolymerized phase, which has not previously been well documented. The formation of AMS seems to be driven by the high charge density of the Mg cation which effectively stabilizes the depolymerized silicate species. We also show that the lack of hydrotalcite-group phases is due to aluminum depletion by zeolite formation. This work highlights the need to consider the existence of the AMS phase in Mg-containing AAMs, especially in complex systems, where its identification may be difficult.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Specific molecular design of polycarboxylate polymers exhibiting optimal compatibility with clay contaminants in concrete

Highlights: • Allyl ether-based PCEs with short side chain length and low side chain density presented superior clay resistance. • PCEs with medium side chain density exhibited best clay robustness when compared at the absolute dosed quantities. • The proportion of PCE being intercalated into the layered structure of clay was quantified. It is widely recognized that the dispersing ability of polycarboxylate superplasticizers (PCEs) could be hindered due to the presence of clay contaminants in concrete. In this study, a series of allyl ether-based polycarboxylate superplasticizers possessing short polyethylene glycol side chains was successfully synthesized and probed for their clay tolerance. The resulting PCE polymers were characterized via Size Exclusion Chromatography (SEC) to obtain their molecular properties. Thereafter, their dispersing ability was probed in the absence and presence of sodium bentonite. Allyl ether-based polycarboxylate (APEG) polymers possessing short side chains were found to exhibit enhanced clay resistance as compared to that of conventional MPEG PCEs holding long pendant chains. The mode of interaction between APEG PCEs and bentonite was investigated via sorption and XRD measurements. The data revealed that APEG PCEs possessing a lower side chain density intercalate less into the interlayer space of bentonite than those exhibiting higher side chain density.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bulk Grain-Boundary Materials from Nanocrystals

Grain-boundary engineering is pivotal to fully utilize the mechanical, electrical, and thermal-transport properties of various materials. However, current methods in metallurgy rely almost exclusively on top-down approaches, making precise grain-boundary engineering, especially at nanoscale, difficult to achieve. Herein, we report a method to produce tailored grain-boundary conditions with nanoscale precision from colloidal metal nanocrystals through surface treatment followed by a pressure-sintering process. The resulting bulk grain-boundary materials (which we call “nanocrystal coins”) possess a metal-like appearance and conductivity while inheriting the original domain features of the nanocrystal building blocks. In this work, nanoindentation measurements confirmed the superior mechanical hardness of the obtained materials. Further, we use this method to fabricate, for the first time, a single-component bulk metallic glass from amorphous palladium nanoparticles. Our discovery may spur the development of new materials whose functionality crucially depends on the domain configuration at nanoscale, such as superhard materials, thermoelectric generators, and functional electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A machine-learning framework for the simulation of nuclear deflection of Planet-Killer-Asteroids

Here, as detection capabilities in astronomy have dramatically improved over the last two decades, concerns over Planet-Killer-Asteroids (PKAs) have become widespread, with nuclear weapons being proposed to destroy or deflect asteroids that are on a short-term projected collision course with Earth. Two main mitigation strategies have been proposed: • Case 1: Break up an incoming asteroid into smaller pieces that will disperse widely, resulting in smaller-scale, less detrimental, Earth-impacts or • Case 2: Deflect an incoming asteroid trajectory to avoid collision altogether. While the two strategies are not mutually exclusive, deflection is a safer strategy, ideally by harnessing all of the released energy from a nuclear device to move the asteroid as a rigid body. However, this case may not be always possible, since the strength of the energy release may break up the asteroid. In this work, the dynamical response of a PKA to a series of ultra-high energy impulses, such as those generated by nuclear devices, is formulated. A rapid iterative Discrete Element Method (DEM) method is developed to describe the deflection and potential breakup of the PKA as a function of a material bonding strength parameter within the asteroid and the magnitude of the applied impulse. The use of DEM allows for fragmentation of the PKA and the ability to compute the trajectories and distribution of the resulting debris field. Finally, a machine-learning algorithm is then developed and combined with the DEM approach to optimize the pulsation strategy for maximum possible safety and success.

42 ENGINEERING↗
DOE OSTI2024

Effect of CO 2 on the water slip flow at silica surfaces for nanometer slit pores of talc

In our previous study, Molecular Dynamics (MD) simulated water flow with no dissolved gas in nanometer slit pores of the hydrophobic talc surfaces revealed a slip length of about 0.5 nm, which is close to the size of “water exclusion zone” but much less than experimental slip length. Atomic Force Microscopy (AFM) imaging confirmed the presence of pancake shape nanobubbles at the hydrophobic talc (001) surface (size from tens to hundreds of nanometers). The effect of CO 2 on water slip flow in talc nanopores is reported to reveal the importance of dissolved gas for confined fluid flow. MD simulated 7 nm CO 2 nanobubbles were found to attach and spread at the talc (001) surface, consistent with the AFM observation. Simulated CO 2 saturated water flow in the slit pores of talc (001) surfaces predicted the generation of CO 2 nanobubbles at the end of the slit pore, due to the stabilization of a CO 2 film at the talc (001) surfaces and a water barrier at the edge surfaces of talc. A “critical thickness” of about 1.5 nm was found for CO 2 nanobubbles to be stabilized at the end of the talc (001) surface. With 1.5 nm CO 2 nanobubbles at the talc (001) surface of a 6 nm slit pore, a water slip length of 1.8 nm was determined. Furthermore, the nanometer slit pore simulations with dissolved CO 2 in water revealed an increased slip length. It is expected that an increased slip length value would be found with an increased CO 2 film thickness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A comprehensive experimental and kinetic modeling study of di-isobutylene isomers: Part 1

We report di-isobutylene has received significant attention as a promising fuel blendstock, as it can be synthesized via biological routes and is a short-listed molecule from the Co-Optima initiative. Di-isobutylene is also popularly used as an alkene representative in multi-component surrogate models for engine studies of gasoline fuels. However, there is limited experimental data available in the literature for neat di-isobutylene under engine-like conditions. Hence, most existing di-isobutylene models have not been extensively validated, particularly at lower temperatures (< 1000 K). Most gasoline surrogate models include the di-isobutylene sub-mechanism published by Metcalfe et al. with little or no modification. The current study is undertaken to develop a detailed kinetic model for di-isobutylene and validate the model using a wide range of relevant experimental data. Part 1 of this study exclusively focuses on the low- to intermediate temperature kinetics of di-isobutylene. An upcoming part 2 discusses the high-temperature model development and validation of the relevant experimental targets. Ignition delay time measurements for the di-isobutylene isomers were performed at pressures ranging from 15 - 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 diluted in air and in the temperature range 650 - 900 K using two independent rapid compression machine facilities. In addition, measurements of species identified during the oxidation of these isomers were performed in a jet-stirred reactor and in a rapid compression machine. A detailed kinetic model for the di-isobutylene isomers is developed to capture the wide range of new experimental targets. For the first time, a comprehensive low-temperature chemistry submodel is included. The differences in the important reaction pathways for the accurate prediction of the oxidation of the two DIB isomers are compared using reaction path analysis. In conclusion, the most sensitive reactions controlling the ignition delay times of the DIB isomers under the pressure and temperature conditions necessary for autoignition in engines are identified.

09 BIOMASS FUELS↗
DOE OSTI2024

O 2 -Dependence of reactions of 1,2-dimethoxyethanyl and 1,2-dimethoxyethanylperoxy isomers

Reaction mechanisms of Ṙ and ROȮ radicals derived from low-temperature oxidation of 1,2-dimethoxyethane (CH 3 O(CH 2 ) 2 OCH 3 ) were investigated using speciation from multiplexed photoionization mass spectrometry (MPIMS) measurements via Cl-initiated oxidation, in conjunction with electronic structure calculations. The experiments were conducted at 5 bar, from 450 K – 650 K, and O 2 concentrations from 1 · 10 14 cm –3 – 6 · 10 18 cm –3 to probe the effects on competing reaction channels of 1,2-dimethoxyethanyl (Ṙ) and 1,2-dimethoxyethanylperoxy (ROȮ) isomers. Several species were detected with photoionization spectral fitting – ethene, formaldehyde, methyl vinyl ether, and 2-methoxyacetaldehyde – and, as determined by electronic structure calculations, may form via unimolecular decomposition of 1,2-dimethoxyethanyl or 1,2-dimethoxyethanylperoxy. O 2 -dependent yield ratios show that the formation pathways for all species undergo a competition between O 2 -addition and unimolecular decomposition. Here, adiabatic ionization energies were also calculated and utilized along with exact mass determinations to infer contributions for other species derived exclusively from first- and second-O 2 -addition, including 1,2-dimethoxyethene, cyclic ethers, and dicarbonyls.

1,2-dimethoxyethane↗
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A universal implementation of radiative effects in neutrino event generators

Due to the similarities between electron-nucleus (eA) and neutrino-nucleus scattering (νA), eA data can contribute key information to improve cross-section modeling in eA and hence in νA event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any eA event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the “extended peaking” approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate νA radiative effects. This work facilitates data-event-generator comparisons used to improve νA event generators for the next-generation of neutrino experiments. Program Title: emMCRadCorr CPC Library link to program files:https://doi.org/10.17632/hmsxg82vnf.1 Developer's repository link:https://github.com/e4nu/emMCRadCorr Licensing provisions: AGPLv3 Programming language:C++ Nature of problem: Radiative effects can significantly modify the event kinematics and the resulting cross-sections. Such effects must be accounted for when comparing event generators to eA data. Existing radiative correction codes are tailored to specific processes and topologies, and are limited to a restricted phase space defined by the spectrometer acceptance. Therefore, a more general approach is required to apply radiative corrections to semi-inclusive and exclusive eA measurements. Solution method: Our program incorporates real photon radiation from both the incident and scattered electrons, as well as virtual photon exchange and photon vacuum polarization effects. It employs the “extended peaking” approximation for electron radiation while neglecting contributions from charged hadron radiation. The code is fully decoupled from event generator codes and can be used for all event generators in the market.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Kernel methods for evolution of generalized parton distributions

Generalized parton distributions (GPDs) characterize the 3-dimensional structure of hadrons, combining information about their internal quark and gluon longitudinal momentum distributions and transverse position within the hadron. The dependence of GPDs on the factorization scale Q 2 allows one to connect hard exclusive processes involving GPDs at disparate energy and momentum scales, which is needed in global analyses of experimental data. Here, in this work, we explore how finite element methods can be used to construct fast and differentiable Q 2 evolution codes for GPDs in momentum space, which can be used in a machine learning framework. We show numerical benchmarks of the methods' accuracy, including a comparison to an existing evolution code from PARTONS/APFEL++, and provide a repository where the code can be accessed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Timing and extent of crop damage by wild pigs (Sus scrofa Linnaeus) to corn and peanut fields

The global expansion of wild pigs over the last few decades has resulted in an increase in extent and distribution of damages to crops, placing a growing strain on agricultural producers and land managers. Despite the extent of wild pig damage to agriculture, there is little data regarding timing and spatial variability of damage to corn (Zea mays Linnaeus) and we found no data regarding the effect of these factors on peanuts (Arachis hypogaea Linnaeus). Our objective was to determine the timing and extent of wild pig damage to corn and peanut fields, as well as the extent to which local habitat attributes are useful predictors of damage to these crops. During 2017–2018 we performed ground-based surveys throughout the growing season for 29 corn and 41 peanut fields in South Carolina, USA to determine the most important growth stages for wild pig depredation in both crops. Damage to corn peaked shortly after planting during the seedling stage, fell to nearly zero during V4–V6 stages, and resumed during the silk and mature stages. Peanut damage was almost exclusively limited to the seedling stage. Landscape models for both crops identified the extent of forested and wetland areas surrounding crop fields as the most important attributes positively associated with wild pig damage, while the amount of adjacent agricultural area and paved roads were associated negatively. The number of wild pigs identified by remote cameras also was an important indicator of the extent of damage to peanut fields. Results suggest management efforts to limit crop depredation by wild pigs should be targeted shortly prior to planting. Further, because damage was positively associated with the availability of wetland and forest habitats, our results suggest agricultural damage by wild pigs may be most severe near areas of preferred native habitats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Deciphering the structure of Arabidopsis thaliana 5-enol-pyruvyl-shikimate-3-phosphate synthase: An essential step toward the discovery of novel inhibitors to supersede glyphosate

Glyphosate interferes with plant aromatic metabolism through the inhibition of 5-enol-pyruvyl-shikimate-3-phosphate (EPSP) synthase [EPSPS, EC 2.5.1.19]. For this reason, EPSPS has been extensively studied in a vast array of organisms. This notwithstanding, up to date, the crystal structure of the protein has been solved exclusively in a few prokaryotes, while that of the plant enzyme has been only deduced in silico by similarity. This study aimed at determining the structure of EPSPS from the plant model species Arabidopsis thaliana, which has been cloned, heterologously expressed and affinity-purified. The kinetic properties of the enzyme have been determined, as well as its susceptibility to the inhibition brought about by glyphosate. The crystal structure of the protein has been resolved at high resolution (1.4 Å), showing open conformation of the enzyme, which is the state ready for substrate/inhibitor binding. This provides a framework for the structure-based design of novel EPSPS inhibitors. Surface regions near the active-site cleft entrance or at the interdomain hinge appear promising for inhibitor selectivity, while bound chloride near the active site is a potential placeholder for anionic moieties of future herbicides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Rats use memory confidence to guide decisions

Memory enables access to past experiences to guide future behavior. Humans can determine which memories to trust (high confidence) and which to doubt (low confidence). How memory retrieval, memory confidence, and memory-guided decisions are related, however, is not understood. In particular, how confidence in memories is used in decision making is unknown. We developed a spatial memory task in which rats were incentivized to gamble their time: betting more following a correct choice yielded greater reward. Rat behavior reflected memory confidence, with higher temporal bets following correct choices. We applied machine learning to identify a memory decision variable and built a generative model of memories evolving over time that accurately predicted both choices and confidence reports. Our results reveal in rats an ability thought to exist exclusively in primates and introduce a unified model of memory dynamics, retrieval, choice, and confidence.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Regulation of hair cell and stomatal size by a hair cell-specific peroxidase in the grass Brachypodium distachyon

The leaf epidermis is the outermost cell layer forming the interface between plants and the atmosphere that must both provide a robust barrier against (a)biotic stressors and facilitate carbon dioxide uptake and leaf transpiration. To achieve these opposing requirements, the plant epidermis developed a wide range of specialized cell types such as stomata and hair cells. While factors forming these individual cell types are known, it is poorly understood how their number and size is coordinated. Here, in this study, we identified a role for BdPRX76/BdPOX, a class III peroxidase, in regulating hair cell and stomatal size in the model grass Brachypodium distachyon. In bdpox mutants prickle hair cells were smaller and stomata were longer. Because stomatal density remained unchanged, the negative correlation between stomatal size and density was disrupted in bdpox and resulted in higher stomatal conductance and lower intrinsic water-use efficiency. BdPOX was exclusively expressed in hair cells suggesting that BdPOX cell autonomously promotes hair cell size and indirectly restricts stomatal length. Cell wall autofluorescence and lignin stainings indicated a role for BdPOX in lignification or crosslinking of related phenolic compounds at the hair cell base. Ectopic expression of BdPOX in the stomatal lineage increased phenolic autofluorescence in guard cell walls and restricted stomatal elongation in bdpox. Together, we highlight a developmental interplay between hair cells and stomata that optimizes epidermal functionality. We propose that cell-type-specific changes disrupt this interplay and lead to compensatory developmental defects in other epidermal cell types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗
DOE OSTI2021

Striving to translate shale physics across ten orders of magnitude: What have we learned?

Shales will play an important role in the successful transition of energy from fossil-based resources to renewables in the coming decades. Aside from being a significant source of low-carbon intensity fuels, like natural gas, they also serve as geologic seals of subsurface formations that may be used to isolate nuclear waste, sequester CO 2 , or store intermittent energy (e.g., solar hydrogen). Despite their importance, shales pose significant engineering and environmental challenges due to their nanoporous structure and extreme heterogeneity that spans at least ~10 orders of magnitude in spatial scale. Two challenges inhibit a system-level understanding: (1) the physics of fluid flow and phase behavior in shales are poorly understood due to the dominant molecular interactions between minerals and fluids under confinement, and (2) the apparent lack of scale separation that prevents a reliable (closed) description of the physics at any single scale of observation. In this review, we focus on the latter issue and discuss scale translation, which in its broadest sense is transforming data or simulations from one spatiotemporal scale to another. While effective scale translation is not exclusive to shales, but all geologic porous media, the need for it is especially acute in shales given their high degree of heterogeneity. Classical theories like homogenization, while indispensable, fail when scales are not separated. Other methods, like numerical upscaling, scale-translate in only one direction: small to large, but not the reverse, called downscaling. However, the confluence of advances in three areas are bringing challenging problems such as shales within reach: increased computational power and scalable algorithms; high-resolution imaging and multi-modal data acquisition; and machine learning to process massive amounts of data. While these advances equip geoscientists with a wide array of experimental and computational tools, no individual tool can probe the entire gamut of heterogeneity in shales. Their effective use, therefore, requires an ability to bridge between various data types obtained at different scales. The aim of this review is to present a coherent account of computational and experimental methods that may be used to achieve just that, i.e., to perform scale translation. We provide a broader definition of scale translation, one that transcends classical homogenization and upscaling methods, but is consistent with them and accommodates notions like downscaling and data translation. After a brief introduction to homogenization, we review hybrid methods, numerical upscaling and its recent extensions, multiscale computing, high-resolution imaging, and machine learning. We place particular emphasis on multiscale computing and propose an algorithmic framework to bridge between the pore (micro) and Darcy (macro) scales. Throughout the paper, we draw comparisons between the various methods and highlight their (often hidden) similarities, differences, benefits, and pitfalls. We finally conclude with two case studies on shales that exemplify some of the methods presented.

58 GEOSCIENCES↗