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Results for “mechanical stability”

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.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Facile healing of cracks in organic–inorganic halide perovskite thin films

Organic-inorganic halide perovskite (OIHP) thin films at the heart of the burgeoning thin-film perovskite solar cells (PSCs) technology possess poor mechanical properties, which is likely to limit the long-term reliability of PSCs as they are poised for commercialization. In an effort to address this issue, in this work we demonstrate that through-thickness cracks induced by bending-tension in thin films of the two prototypical OlHPs, methylammonium lead triiodide (MAPbl(3)) and formamidinium lead triiodide (FAPbl(3)), can be healed easily. This is through the application of either a moderate compressive stress (bending-compression) at room temperature or a simple heat-treatment at modest temperatures. The crack-healing process is found to be time-dependent, which indicates that facile mass-transport in OlHPs plays a key role in this phenomenon. An explanation for this phenomenon is provided, one based on the fundamentals of brittle fracture. This discovery has broad implications for the prevention and/or restoration of the overall performance, environmental stability, and mechanical reliability of PSCs, and other devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Spin Superatom Stabilized by Dual Subshell Filling

Quantum confinement in small symmetric clusters leads to the bunching of electronic states into closely packed shells, enabling the classification of clusters with well-defined valences as superatoms. Like atoms, superatomic clusters with filled shells exhibit enhanced electronic stability. Here, we show that octahedral transition-metal chalcogenide clusters can achieve filled shell electronic configurations when they have 100 valence electrons in 50 orbitals or 114 valence electrons in 57 orbitals. While these stable clusters are intrinsically diamagnetic, we use our understanding of their electronic structures to theoretically predict that a cluster with 107 valence electrons would uniquely combine high stability and high-spin magnetic moment, attained by filling a majority subshell of 57 electrons and a minority subshell of 50 electrons. Further, we experimentally demonstrate this predicted stability, high-spin magnetic moment (S = 7/2), and fully delocalized electronic structure in a new cluster, [NEt 4 ] 5 [Fe 6 S 8 (CN) 6 ]. This work presents the first computational and experimental demonstration of the importance of dual subshell filling in transition-metal chalcogenide clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SCF Framework, HF Stability, and RPA Correlation for Jordan–Wigner-Transformed Spin Hamiltonians on Arbitrary Coupling Topologies

Mapping spins to fermions via the Jordan–Wigner (JW) transformation can render mean-field (Hartree–Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is not limited by the nonlocal structure of JW strings or by site ordering because string operators can be absorbed into Thouless rotations of a Slater determinant, and the variational optimization of a unitary Lie-algebraic similarity transformation removes any ordering dependence. Leveraging these ideas, we develop a self-consistent field (SCF) scheme that expresses the mean-field energy as a functional of the single-particle density matrix, providing an alternative to gradient-based optimization of Thouless parameters. We derive the analytical orbital Hessian to diagnose HF stability and compute the ground-state correlation energy through the random-phase approximation (RPA). Benchmark results for the XXZ and J 1 –J 2 model on one- and two-dimensional lattices demonstrate that RPA significantly improves mean-field accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Regioisomeric Engineering for Multicharge and Spin Stabilization in Two-Electron Organic Catholytes

Developing multicharge and spin stabilization strategies is fundamental to enhancing the lifetime of functional organic materials, particularly for long-term energy storage in multiredox organic redox flow batteries. Current approaches are limited to the incorporation of electronic substituents to increase or decrease the overall electron density or bulky substituents to sterically shield reactive sites. With the aim to further expand the molecular toolbox for charge and spin stabilization, we introduce regioisomerism as a scaffold-diversifying design element that considers the collective and cumulative electronic and steric contributions from all of the substituents based on their relative regioisomeric arrangements. Through a systematic study of regioisomers of near-planar aromatic cyclic triindoles and nonplanar nonaromatic cyclic tetraindoles, we demonstrate that this regioisomeric engineering strategy significantly enhances the H-cell cycling stability in the above two new classes of 2e – catholytes, even when current strategies failed to stabilize the multicharged species. Density functional theory calculations reveal that the strategy operates by redistributing the charge and spin densities while highlighting the role of aromaticity in charge stabilization. The most stable 2e – catholyte candidate was paired with a viologen derivative anolyte to achieve a proof-of-concept all-organic flow battery with 1.26–1.49 V, 98% capacity retention, and only 0.0117% fade/h and 0.00563% fade/cycle over 400 cycles (192 h), which is the highest capacity retention ever reported over 400 cycles in a multielectron all-organic flow battery setup. We anticipate regioisomeric engineering to be a promising strategy complementary to conventional electronic and steric approaches for multicharge and spin stabilization in other functional organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Analysis of phase stability and chemical segregation in the Mo-V alloys using a generalized embedded atom method potential

A new interatomic potential for the Mo-V system is introduced to facilitate the study of phase stability and mechanical properties at lower temperatures. This potential is based on a generalization of the embedded atom method and includes contributions from embedding energy, explicit two- and three-body interactions and nonlocal many-body interaction terms. The parameters of the potential are optimized by using data from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, such as elastic constants, equation of states, phonon dispersion curves, point defect properties and melting temperatures for different compositions. Even though our potential is trained on a small dataset, its accuracy is comparable to available machine learning potentials for Mo and V. Furthermore, our results show that an ordered B2 phase is stable at low temperatures in alloys containing 50% V, but the solid solution phase is stable above 800 K. However, such long-range ordering is not observed in V-rich or Mo-rich alloys. In addition, our results show that V segregates to dislocation cores and grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Comprehensive Machine Learning Model for Metal–Ligand Binding Prediction: Applications in Chemistry and Biology

A machine-learning (ML) model that predicts metal–ligand binding constants was developed using the open-source Chemprop software. The model was trained on over 30,000 experimental log K 1 values, which include both protonation and metal–ligand stability constants, comprising over 3500 ligands and 10 2 metal ions from 73 total elements, thus generalizing beyond existing limited approaches, which focus only on specific metals or ligand families. The best-performing model included a combination of SMILES-based molecular representations along with descriptors for the metal ion and experimental conditions. It had an external test R 2 value of 0.942, and MAE value of 0.834. A “SMILES-only” simpler version also produced accurate predictions and preserved the binding trends, serving as a quick and easily accessible alternative for users without computational expertise. The SMILES-only model performed comparably to density functional theory (DFT) calculations but utilized a fraction of the computational resources. The model was successfully applied across diverse domains, including bioinorganic chemistry, heavy metal remediation, and sensor development and demonstrated its effectiveness as a rapid and reliable screening tool for both academic and industrial uses.

Ligands↗
DOE OSTI2021

Role of thermo-mechanical gyrations on the α/β interface stability in a Ti6Al4V AM alloy

Fluctuating energy distributions experienced during Additive Manufacturing yield an evolution of spatial and temporal transients within a part. In general, the in-situ monitoring of these transients is near to impossible during manufacturing. In order to then gain perspective into the impact on these localized thermo-mechanical transients on the interface stability, rapid thermo-mechanical reversals with known boundary conditions are imposed on an AM Ti6Al4V alloy which resulted in a phase transformation leading to an increased β phase stability. Our goal with this study is to comprehend the kinetics of this phase transformation with concepts of stored energy due to plastic strain accumulation and diffusion kinetics. Atom Probe Tomography is employed to study the partitioning of the solute elements across the interface. As expected, the thermo-mechanically cycled samples showed a reduced Vanadium concentration across the β phase. Finally, this concentration profile across the interface, alongside a full-width-half-max analysis, provided insight on the potential phase transformation kinetics involved in the α → β transformation subject to thermo- mechanical gyrations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Phosphorus Modulation in Iron Single‐Atom Catalysts for Peroxidase Mimicking

Abstract Fe–N–C single‐atom catalysts (SACs) exhibit excellent peroxidase (POD)‐like catalytic activity, owing to their well‐defined isolated iron active sites on the carbon substrate, which effectively mimic the structure of natural peroxidase's active center. To further meet the requirements of diverse biosensing applications, SAC POD‐like activity still needs to be continuously enhanced. Herein, a phosphorus (P) heteroatom is introduced to boost the POD‐like activity of Fe–N–C SACs. A 1D carbon nanowire (FeNCP/NW) catalyst with enriched Fe–N 4 active sites is designed and synthesized, and P atoms are doped in the carbon matrix to affect the Fe center through long‐range interaction. The experimental results show that the P‐doping process can boost the POD‐like activity more than the non‐P‐doped one, with excellent selectivity and stability. The mechanism analysis results show that the introduction of P into SAC can greatly enhance POD‐like activity initially, but its effect becomes insignificant with increasing amount of P. As a proof of concept, FeNCP/NW is employed in an enzyme cascade platform for highly sensitive colorimetric detection of the neurotransmitter acetylcholine.

Ding, Shichao↗
DOE OSTI2021

Room Temperature to 150 °C Lithium Metal Batteries Enabled by a Rigid Molecular Ionic Composite Electrolyte

Molecular ionic composites (MICs), made from ionic liquids and a rigid-rod polymer poly(2,2'-disulfonyl-4,4'-benzidine terephthalamide) (PBDT), are a new type of rigid gel electrolyte that combine fast ion transport with high thermal stability and mechanical strength. In this work, a MIC electrolyte membrane is prepared that is composed of PBDT, lithium bis(trifluoromethylsulfonyl)imide (LiTFSI), and 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide (Pyr 14 TFSI) in a mass ratio of 10:10:80. The ionic conductivity at 25 °C is 0.56 mS cm –1 with no added flammable/volatile components. Although the polymer content is only 10 wt%, this MIC membrane is rigid with a tensile modulus of 410 MPa at room temperature. The MIC membrane remains stable and rigid at 200 °C with the shear storage modulus (G') only slightly decreasing by 35%. Li/MIC/LiFePO 4 cells demonstrate stable cycling performance over a wide temperature range from 23 to 150 °C. The specific discharge capacity at 100 and 150 °C at 1 C rate exceeds 160 mAh g –1 . The discharge capacity retention is 99% after 50 cycles at 150 °C. Furthermore, this stable battery performance shows that this low polymer content MIC membrane qualifies for use as a solid electrolyte in lithium metal batteries operating over a wide temperature range.

25 ENERGY STORAGE↗
DOE OSTI2022

Quench and Partitioning Steels

Quench and Partitioning (Q&P) steels are produced by implementing a unique thermal history designed to produce microstructures that contain martensite, and potentially ferrite, along with significant amounts of retained austenite stabilized by high carbon contents. Carbon-stabilized austenite is obtained by carbon transfer from martensite into austenite after a controlled amount of martensite is introduced by judicious selection of a so-called quench temperature at which quenching below the martensite start temperature is interrupted. Following the quench interruption, during the partitioning step, the steel is either held at the quench temperature or brought to a higher temperature and held for a specific time, to stimulate carbon transfer from martensite to austenite, to decrease the carbon supersaturation in martensite and correspondingly stabilize the austenite by carbon enrichment. A final quench to room temperature may be associated with the transformation of a certain fraction of austenite into secondary or “fresh” martensite, which is usually undesirable. A review of the Q&P process is presented, including prediction of austenite retention, alloying effects on its stabilization, a mechanical properties survey, including tensile and local formability relevant to sheet steels for automotive applications, along with perspectives on reactions competing with carbon partitioning that may operate during partitioning.

Kang, Singon↗
DOE OSTI2022

Cost-Efficiency balanced polymer acceptors based on lowly fused Dithienopyrrolo[3, 2b]benzothiadiazole for 16.04% efficiency All-Polymer solar cells

All-polymer solar cells (All-PSCs) attracted increasing attention due to the outstanding thermal stability and mechanical properties. The current prevailing polymer acceptors for most efficient All-PSCs are polymerized high-performance small molecule acceptor of Y6, i.e. the dithienothiopheno[3,2-b]-pyrrolobenzothiadiazole (BTTP) based polymers. However, the BTTP-based polymers often show relatively shallow highest occupied molecular orbital (HOMO) energy level and high figure of merit (FOM), which limit the rational selection of paring donor polymers. Herein, we presented two low-cost polymer acceptors, namely as BTP-T2F and BTP-2T2F, based on lowly fused dithienopyrrolo[3,2b]benzothiadiazole (BTP, removing two thiophene cycles from BTTP). Here the BTP-based polymers exhibited deeper HOMO levels around –5.90 eV, which could match variable donor polymers with low-lying HOMO levels, such as low-cost PTQ10. Additionally, the synthesis was significantly simplified compared to BTTP-based polymers. A power conversion efficiency (PCE) of 14.32% was achieved in binary blend device containing PTQ10:BTP-2T2F. By adding a miscibility-enhancing PBDTCl-TPD as a third component, the top PCE of 16.04% was obtained in ternary blend All-PSCs. Combining the high device performance and low estimated cost, extraordinary cost-efficiency balance was realized within these BTP-based polymer acceptors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Anomalously high elastic modulus of a poly(ethylene oxide)-based composite electrolyte

The practical use of lithium metal anodes in solid-state batteries requires a polymer membrane with high lithium-ion conductivity, thermal/electrochemical stability, and mechanical strength. The primary challenge is to effectively decouple the ionic conductivity and mechanical strength of the polymer electrolytes. We report a remarkably facile single step synthetic strategy based on in-situ crosslinking of poly(ethylene oxide) (xPEO) in the presence of a woven glass fiber (GF). Such a simple method yields composite polymer electrolytes (CPE) of anomalously high elastic modulus up to 2.5 GPa over a broad temperature range (20 °C – 245 °C) that has never been previously documented. An unsupervised machine learning algorithm, K-mean clustering analysis, was implemented on the hyperspectral Raman mapping at the xPEO/GF interface. Using such a unique means, we show for the first time that the promoted mechanical strength originates from xPEO and GF interactions through dynamic hydrogen and ionic bonding. High ionic conductivity is achieved by the addition plasticizer (e.g. tetraglyme), where trifluoromethanesulfonate anions are tethered to the xPEO matrix and Li + cations are favorably transported through coordination with the plasticizer. Further, stringent galvanostatic cycling tests indicates the CPE can be stably cycled for >3000 h in a Li-metal symmetric cell at a moderate temperature (nearly 1500 Coulombs/cm 2 Li equivalents), outperforming most of the PEO-based electrolytes. The GF reinforced CPE reported here has multifunctional uses, such as solid electrolytes for all solid-state batteries and membranes for redox-flow batteries. Although the focus of this study is on lithium-based batteries, the results are equally promising for other alkali metal based batteries such as sodium and potassium.

25 ENERGY STORAGE↗
DOE OSTI2026

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗
DOE OSTI2024

Tandem pyrolysis evolved gas–gas chromatography–mass spectrometry

Analysis of byproducts from thermal degradation of polymer materials provides a wealth of information about a materials’ composition, thermal stability, degradation mechanisms, and kinetics. However, regardless of the instrumentation used, only limited information is obtainable from a single experiment. Microfurnace technology, when interfaced to a gas chromatography-mass spectrometry (GC-MS), can be used to obtain both thermal and chemical information via evolved gas analysis-MS (EGA-MS) and GC-MS analysis modes. While both EGA-MS and Py-GC-MS are valuable when characterizing polymer materials, at least two experiments on distinct samples are required, which can be a liability for clear interpretation of results from inhomogeneous samples. Here, we seek to overcome this limitation by combining EGA-MS and Py-GC-MS modes in a single experimental setup. Further, this was done by developing new gas line modifications to allow for tandem Pyrolysis Evolved Gas-Gas Chromatography-Mass Spectrometry (Py/EG-GC-MS) analysis. Verification of Py/EG-GC-MS analysis was performed using a polystyrene standard. Results demonstrate successful Py/EG-GC-MS analysis for the first-time showing the potential of these modifications for application in areas where sample is limited or direct correlation of products to the thermal profile is desirable such as in forensics or product-specific kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Lithium substituted poly(amic acid) as a water-soluble anode binder for high-temperature pre-lithiation

Multifunctional binders hold great promise in advanced electrode designs for both fundamental research and practical utilization of lithium-ion batteries (LIBs). The reactions between Si/SiO x -dominated anodes with lithium are expected to be exothermic in principle, while the thermal tolerance along with the volume change makes high-temperature binders attractive for large scale roll-to-roll manufacturing. For instance, if a high temperature binder is also water soluble, it can be compatible with the current graphite-based anode manufacturing process. In this work, we present a water-soluble poly(amic acid)-based binder, which can withstand high temperature for industrial pre-lithiation process and effectively hold active materials together during repeated charge and discharge cycles. This lithium substituted poly(amic acid) binder (denoted as Li-Pa) can serve as a drop-in replacement for environmentally friendly electrode fabrication in large scale by providing aqueous solubility, exceptional thermal stability and mechanical flexibility.

25 ENERGY STORAGE↗
DOE OSTI2023

Rechargeable metal-metal alkaline batteries: Recent advances, current issues and future research strategies

Over the past few decades, remarkable advancement has been attained in the field of rechargeable metal–metal alkaline batteries (RABs). In terms of safety, energy density, charge-discharge capacity, and long-term storage capability, metal-metal RABs (e.g., Ni–Zn, Ni–Fe, Ni–Bi, Ni–MH, Ag–Zn, Co–Zn, Cu–Zn, and Bi–Zn systems) are contemplated as the promising energy storage devices for the applications in electric vehicles (EVs), hybrid EVs, grid-scale energy storage, as well as various implantable and wearable electronic devices. Especially, Ni-MH batteries become competitive with Li-ion batteries for EVs and hybrid EVs applications due to their high tolerance against mechanical abuse, stability under wide temperature ranges, and considerable charge/discharge capacity. Meanwhile, earlier works reviewed only specific topics, so, as a rapidly growing research topic, providing a deep understanding on metal–metal RABs is timely and worthwhile. So here, in this work, we discuss the electrochemistry of all metal-metal RABs, then full cell designing with their performance will be discussed thoroughly. Further, issues associated with the existing metal–metal RABs and corresponding improvement approaches will be provided for future advances in high-performance and reliable metal-metal RABs.

25 ENERGY STORAGE↗
DOE OSTI2024

Effect of Si impurities on microstructure and tensile properties of a cast Al-Mg-Fe alloy

Al-Mg alloys are attractive for structural castings owing to their superior strength and ductility in the as-cast state. However, given the tight tolerance for impurities, Al-Mg alloys produced from secondary sources still face multiple challenges. Here, we report the effect of increased Si impurity (0.05–1.6 wt%), which is commonly found in secondary Al sources, on microstructure and tensile properties of a cast Al-4.3Mg-1.6Fe (wt%) alloy, commercially referred to as Castaduct-42 alloy. Microstructural characterization revealed that Si addition increased the volume fraction, size, and aspect ratio of primary Al13Fe4 intermetallic particles as well as the volume fraction of other binary and ternary eutectic phases. Tensile testing results demonstrated that increasing Si impurities from 0.05 to 1.6 wt% reduced ductility from 14.3 ± 1.4 % to 2.2 ± 1.0 %. A particle cracking damage accumulation model coupled with failure analysis indicated primary Al13Fe4 intermetallic particles to be the major contributing factor to the deterioration in ductility with increasing Si content. Additionally, the stabilizing effect of Si on primary Al 13 Fe 4 was inconsistent with the CALPHAD calculation results based on existing CALPHAD databases which predict a slightly decreasing primary Al13Fe4 phase fraction with increasing Si concentration. This work provides new insights into the phase stability and mechanical behavior of the lesser studied Al-Mg-Fe-Si alloy system that will contribute to the development of sustainable cast Al-Mg based alloys.

36 MATERIALS SCIENCE↗