Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Structural Properties”

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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Generalized kinetic model for defect evolution in irradiated materials

A fundamental and open problem in materials science is to determine how the structural properties of irradiated and self-irradiated materials evolve in time. Structural defects generated by irradiation lead to changes in a material’s macroscopic properties, and these macroscopic changes, such as volumetric swelling, can in turn give rise significant alterations of the functionality of a material. Here, we develop a unified analytical model to understand the complex interplay between aggregation, fragmentation, and recombination processes involving mobile clusters of defects such as bubbles, voids, and interstitial atoms in materials subject to radiative sources. Specifically, we employ a mean field approach to derive a system of coupled kinetic equations that describes both the time evolution of the density of each type of defect and how clusters of each defect form and grow as the material ages.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of Mg Substitution on the Structure, Stability, and Properties of the Na 2 Fe 2 F 7 Weberite Cathode

Of the few weberite-type Na-ion cathodes explored to date, Na 2 Fe 2 F 7 exhibits the best performance, with capacities up to 184 mAh/g and energy densities up to 550 Wh/kg reported for this material. However, the development of robust structure–property relationships for this material is complicated by its tendency to form as a mixture of metastable polymorphs, and transform to a lower-energy Na y FeF 3 perovskite compound during electrochemical cycling. Our first-principles-guided exploration of Fe-based weberite solid solutions with redox-inactive Mg 2+ and Al 3+ predicts an enhanced thermodynamic stability of Na 2 Mg x Fe 2–x F 7 as the Mg content is increased, and the x = 0.125 composition is selected for further exploration. We demonstrate that the monoclinic polymorph (space group C2/c) of Na 2 Fe 2 F 7 (Mg0) and of a new Mg-substituted weberite composition, Na 2 Mg 0.125 Fe 1.875 F 7 (Mg0.125), can be isolated using an optimized synthesis protocol. The impact of Mg substitution on the stability of the weberite phase during electrochemical cycling, and on the extent and rate of Na (de)intercalation, is examined. Irrespective of the Mg content, we find that the weberite phase is retained when cycling over a narrow voltage window (2.8–4.0 V vs Na/Na+). Over a wider voltage range (1.9–4.0 V), Mg0 shows steady capacity fade due to its transformation to the NayFeF3 perovskite phase, while Mg0.125 displays more reversible cycling and a reduced phase transformation. Yet, Mg incorporation also leads to kinetically limited Na extraction and a reduced overall capacity. These findings highlight the need for the continued compositional optimization of weberite cathodes to improve their structural stability while maximizing their energy density.

25 ENERGY STORAGE↗
DOE OSTI2025

Generalizable, fast, and accurate DeepQSPR with fastprop

Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.

Burns, Jackson W. (ORCID:0000000206579426)↗
DOE OSTI2021

Interferometric SAR modelling of near surface data to improve geological model in the Surat Basin, Australia

Here we present a study on geophysical inverse modelling for subsurface structural properties of an unconventional hydrocarbon site that was monitored previously by Interferometric Synthetic Aperture Radar (InSAR) technology for surface deformation. A static three-dimensional geomodel along with extracted property maps replicates the depth of each underlying stratigraphic unit and structural feature with the density of each geological layer. We examine the hypothesis that integration of elastic properties of each formation layer with InSAR observations in a stratified elastic medium will lead to a viscoelastic geophysical inverse problem that can be solved to estimate fractional volume change at the reservoir level. Moreover, we examine synthetic scenarios in which the elastic properties of the formations are perturbed before determining the resulting impact on the rate of surface deformation. The results show that although the slope of underlying formations, their density and depth can define the extent and pattern of a deformation signal, their properties have a marginal impact on volumetric change compared to the dense network of shallow depth Coal Seam Gas (CSG) mining wells. Besides, it is also demonstrated that the inversion of InSAR deformation maps can resolve the uncertainties associated with low-resolution seismic interpretation as well as filling the data gaps within seismic acquisitions. A significant contribution of this investigation to the geological basin modelling involves a) introducing a remote and non-invasive technology such as InSAR to improve geophysical mapping of subsurface structures such as faults in areas with sparse or no reflective seismic information, and b) applying a multi-layer viscoelastic geophysical source model for an unconventional hydrocarbon reservoir such as CSG.

58 GEOSCIENCES↗
DOE OSTI2023

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗
DOE OSTI2025

Mixed-Flux Techniques for Rational Synthesis and Structural Control in Silver Chalcogenides

The functionality of materials is intrinsically linked to their structures, an axiom encapsulated in the principle of structure-property relationships. The pinnacle of materials design is the tailoring of its structure for a specific function, which requires the ability of rational synthesis and the development of synthesis science. This idea, however, remains elusive for the synthesis of complex extended solids. A major obstacle is the difficulty in using established chemical principles selectively to control reaction paths and favor certain structural patterns over numerous other possible results. In this context, we are developing a synthesis science approach that facilitates the control of the structure and bonding to create new structures. This is achieved by employing a two-component flux consisting of mixed hydroxides and halides as the reaction medium. This enables reaction conditions that allow better control of the structure dimensionality and composition by manipulating the temperature and solvent basicity (via the flux component ratio). Here, we demonstrate the efficacy of this method in controlling their structural motifs to arrive at 23 unreported compositions and 6 unique structure types. These materials are expected to exhibit a broad range of properties, from metallic to semiconducting, with calculations suggesting the potential for emergent phenomena such as Dirac semimetals. The reaction paths afforded by these mixed fluxes establish a direct correlation between the synthetic variables and properties, providing significant insight into a broadly applicable approach for new materials.

Zhou, Xiuquan [Argonne National Laboratory (ANL), ↗
DOE OSTI2020

Initial development of a method for correlating indentation test results to damage accumulation in high temperature structural materials

This report describes an experimental approach based on microindentation creep or relaxation tests for assessing the remaining creep life of a sample material. The objective for this experimental program is to complement the development of passively loaded in situ surveillance specimens. These surveillance specimens could be placed in future advanced reactors to assess the degradation of structural properties, primary creep and creep-fatigue life, when the material is exposed to actual reactor operating conditions. The specimens and the corresponding indentation test protocol could form the basis of a structural health monitoring program designed to ensure the safe continued operation of the component given the relatively unknown effect of the reactor coolant chemistry, radiation exposure, and other environmental effects on the material properties of the constituent structural materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Computational synthesis of a new generation of 2D-based perovskite quantum materials

Perovskite-based optoelectronic devices have emerged as a promising energy source due to their potential for scalable production. This study introduces “perovskene,” a novel class of 2D materials derived from the ABC3-like perovskites, synthesized via a data-driven, high-throughput computational strategy. We harness machine learning and multitarget deep neural networks to systematically investigate the structure–property relations, paving the way for targeted material design and optimization in fields such as renewable energy, electronics, and catalysis. The characterization of over 1500 synthesized structures shows that more than 500 structures are stable, revealing properties such as ultra-low work function and large magnetic moment, underscoring the potential for advanced technological applications.

2D materials↗
DOE OSTI2021

Nanoscale properties of lead halide perovskites by scanning tunneling microscopy

Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗
DOE OSTI2025

Microstructure-sensitive mechanical behavior of an additively manufactured psuedoelastic shape memory alloy

The additive manufacturing of shape memory alloys into complex geometries enables fabrication of advanced functional systems across a variety of fields and domains. This work presents results focused on the mechanical behavior of additively manufactured shape memory pseudoelastic NiTi. The deformation induced solid state phase transformation from austenite to martensite allows this system to accommodate large recoverable strains. This deformation behavior is fundamentally driven by crystal-scale transformation physics. Laser powder bed fusion processing reveals that the resulting microstructure, both grain morphology and crystallographic texture, is strongly dependent on the manufacturing processing history. Exhaustive mechanical testing demonstrates that these microstructural factors strongly impact both tensile and cyclic stress–strain behavior. Cyclic dissipative behavior, however, is similar across all tested microstructures following an initial transient period. Remarkably, analysis of spatial strain fields during tensile loading reveals two distinctly different localization “modes”. The first is initiation of localized deformation bands which continuously propagate through the tensile bar during loading. In the second mode localization is observed but lacks propagation; instead additional localization cites nucleate during subsequent loading. The latter phenomena is suspected to be driven by grain-scale deformation physics as the localized band morphologies coincide with grain morphologies. These phenomena strongly impact the resulting aggregate stress–strain behavior. Hence, manufacturers and designers of psuedoelastic functional components must at the very least consider the potential variability in properties when considering additive manufacturing processing. More ideally the process–structure–property relations can be used to further tailor and optimize final functional performance.

Additive manufacturing↗
DOE OSTI2024

Effects of Al concentration on the structure and conductivity of lithium lanthanum zirconium oxide

Cubic Li 7-3x Al x La 3 Zr 2 O 12 (LLZO) is a promising, next-generation solid electrolyte due to its stability with Li-metal and high bulk conductivity (~1 mS cm -1 ). However, the source of the high conductivity is not completely understood. In this work, we address this key knowledge gap through the integration of elemental analysis, neutron diffraction sensitive to Li and O atoms, and impedance spectroscopy to understand the structure–property correlations for LLZO. We show the metal–oxygen framework structure remains constant with variation in Al substitution, resulting in a constant activation energy of ~0.35 eV and little effect on the bulk conductivity. Instead, Li concentration, Al blocking and trapping of mobile defects, and Li–Li nearest neighbor interactions largely control the Al substituted LLZO bulk conductivity, resulting in decreases from 0.73 to 0.22 mS cm -1 as the Al concentration increases from 0.17 to 0.32 mol. These results differ from those of Ta substituted LLZO, where the framework structure and Li–Li site distances play large roles in controlling the conductivity. The increased understanding of the controlling factors of conductivity allows for greater ability to tailor the design of and substitution into the LLZO structure for improved conductivity.

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

Cryo neutron crystallography demonstrates influence of RNA 2'-OH orientation on conformation, sugar pucker and water structure

The ribose 2'-hydroxyl is the key chemical difference between RNA and DNA and primary source of their divergent structural and functional characteristics. Macromolecular X-ray diffraction experiments typically do not reveal the positions of hydrogen atoms. Thus, standard crystallography cannot determine 2'-OH orientation (H2'-C2'-O2'-HO2' torsion angle) and its potential roles in sculpting the RNA backbone and the expansive fold space. Here, we report the first neutron crystal structure of an RNA, the Escherichia coli rRNA Sarcin-Ricin Loop (SRL). 2'-OD orientations were established for all 27 residues and revealed O-D bonds pointing toward backbone (O3', 13 observations), nucleobase (11) or sugar (3). Most riboses in the SRL stem region show a 2'-OD backbone-orientation. GAGA-tetraloop riboses display a 2'-OD base-orientation. An atypical C2'-endo sugar pucker is strictly correlated with a 2'-OD sugar-orientation. Neutrons reveal the strong preference of the 2'-OH to donate in H-bonds and that 2'-OH orientation affects both backbone geometry and ribose pucker. We discuss 2'-OH and water molecule orientations in the SRL neutron structure and compare with results from a solution phase 10 μs MD simulation. We demonstrate that joint cryo-neutron/X-ray crystallography offers an all-in-one approach to determine the complete structural properties of RNA, i.e. geometry, conformation, protonation state and hydration structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

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

Structural and antibacterial properties of NSAID-loaded ultra-high molecular weight polyethylene

Peri-articular delivery of pain medication in joint arthroplasty has the potential to address post-operative pain and decrease the use of systemic opioids. Additionally, the sustained release from a delivery vehicle may be especially impactful in the initial post-operative period when pain is most severe. We recently described a novel approach for the sustained intra-articular delivery of an analgesic (bupivacaine) from an ultra-high molecular weight polyethylene (UHMWPE) bearing surface. A secondary but very significant effect of incorporating bupivacaine in UHMWPE was its antibacterial effect against Staphylococcal species, which are associated with the majority of periprosthetic joint infections. Here, we report on the structure, properties, elution characteristics and antibacterial properties of UHMWPE loaded with the non-steroidal anti-inflammatory drug (NSAID) — tolfenamic acid. We showed that 6 wt% drug loading was optimal for eluting clinically relevant intra-articular and systemic concentrations, for maintaining mechanical properties at a clinically relevant level, and for providing anti-colonization potential against low risk (planktonic) and high risk (biofilm forming) Staphylococcal species. We determined the osteoblast response to the tolfenamic acid-loaded UHMWPE to evaluate the cytotoxicity profile of this novel material. Tolfenamic acid-loaded UHMWPE has the potential to be used as a part of multimodal pain management therapy following arthroplasty and may provide prophylaxis for periprosthetic infection.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlating Macro and Atomic Structure with Elastic Properties and Ionic Transport of Glassy Li 2 S‐P 2 S 5 (LPS) Solid Electrolyte for Solid‐State Li Metal Batteries

Abstract A combination of high ionic conductivity and facile processing suggest that sulfide‐based materials are promising solid electrolytes that have the potential to enable Li metal batteries. Although the Li 2 S‐P 2 S 5 (LPS) family of compounds exhibit desirable characteristics, it is known that Li metal preferentially propagates through microstructural defects, such as particle boundaries and/or pores. Herein, it is demonstrated that a near theoretical density (98% relative density) LPS 75‐25 glassy electrolyte exhibiting high ionic conductivity can be achieved by optimizing the molding pressure and temperature. The optimal molding pressure reduces porosity and particle boundaries while preserving the preferred amorphous structure. Moreover, molecular rearrangements and favorable Li coordination environments for conduction are attained. Consequently, the Young's Modulus approximately doubles (30 GPa) and the ionic conductivity increases by a factor of five (1.1 mS cm −1 ) compared to conventional room temperature molding conditions. It is believed that this study can provide mechanistic insight into processing‐structure‐property relationships that can be used as a guide to tune microstructural defects/properties that have been identified to have an effect on the maximum charging current that a solid electrolyte can withstand during cycling without short‐circuiting.

Garcia‐Mendez, Regina↗
DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2022

Bacterial Membranes Are More Perturbed by the Asymmetric Versus Symmetric Loading of Amphiphilic Molecules

Characterizing the biophysical properties of bacterial membranes is critical for understanding the protective nature of the microbial envelope, interaction of biological membranes with exogenous materials, and designing new antibacterial agents. Presented here are molecular dynamics simulations for two cationic quaternary ammonium compounds, and the anionic and nonionic form of a fatty acid molecule interacting with a Staphylococcus aureus bacterial inner membrane. The effect of the tested materials on the properties of the model membranes are evaluated with respect to various structural properties such as the lateral pressure profile, lipid tail order parameter, and the bilayer’s electrostatic potential. Conducting asymmetric loading of molecules in only one leaflet, it was observed that anionic and cationic amphiphiles have a large impact on the Staphylococcus aureus membrane’s electrostatic potential and lateral pressure profile as compared to a symmetric distribution. Nonintuitively, we find that the cationic and anionic molecules induce a similar change in the electrostatic potential, which points to the complexity of membrane interfaces, and how asymmetry can induce biophysical consequences. Finally, we link changes in membrane structure to the rate of electroporation for the membranes, and again find a crucial impact of introducing asymmetry to the system. Understanding these physical mechanisms provides critical insights and viable pathways for the rational design of membrane-active molecules, where controlling the localization is key.

59 BASIC BIOLOGICAL SCIENCES↗