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597 records · Page 25

Gold Quantum Rods: Modulation of Singlet and Triplet Exciton Populations by the Rod Length

Abstract Gold quantum rods (QRs) of Au60, Au78, Au96, and Au114 (protected by thiolate ligands) exhibit exclusive fluorescence, which is different from the shorter Au42 QR with dual emission (fluorescence + phosphorescence). Herein, we report the excitation wavelength-dependent near-infrared-II photoluminescence (PL) and exciton dynamics of this series of QRs. Interestingly, the fluorescence quantum yield (QY) of the QRs is much higher (2–10×) when the lowest singlet excited state (S1) is excited compared to the excitation of high-lying states (Sn). A metastable intermediate singlet state (denoted S′) is identified by transient absorption spectroscopy when Sn is excited, and this S′ state leads to fast “skybridge” intersystem crossing (ISC), which contributes primarily (>60%) to the total triplet population. With increasing aspect ratio (AR) of QRs (from 6.3 to 18.7), nonradiative processes accelerate, leading to fast decay of the S1 state (hence, less QY) and of the T1 state (barely phosphorescent). A detailed energy flow mechanism is determined for the QRs after photoexcitation, which offers a design principle for manipulation of exciton dynamics toward potential utilization of higher excited states in applications.

77 NANOSCIENCE AND NANOTECHNOLOGY

Customizable wave tailoring nonlinear materials enabled by bilevel inverse design

Abstract Passive wave transformation via nonlinearity is ubiquitous in settings from acoustics to optics and electromagnetics. It is well known that different nonlinearities yield different effects on propagating signals, which raises the question of “what precise nonlinearity is the best for a given wave tailoring application?” In this work, considering a one-dimensional spring-mass chain connected by polynomial springs (a variant of the Fermi-Pasta-Ulam-Tsingou system), we introduce a bilevel inverse design method which couples the shape optimization of structures for tailored constitutive responses with reduced-order nonlinear dynamical inverse design. We apply it to two qualitatively distinct problems—minimization of peak transmitted kinetic energy from impact, and pulse shape transformation—demonstrating our method’s breadth of applicability. For the impact problem, we obtain two fundamental insights. First, small differences in nonlinearity can drastically change the dynamic response of the system, from severely under- to outperforming a comparative linear system. Second, the oft-used strategy of impact mitigation via “energy locking” bistability can be significantly outperformed by our optimal nonlinearity. We validate this case with impact experiments and find excellent agreement. This study establishes a framework for broader passive nonlinear mechanical wave tailoring material design, with applications to computing, signal processing, shock mitigation, and autonomous materials.

Science & Technology - Other Topics

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials

Should I stay or should I flow? An exploration of phase‐separated metallosupramolecular liquid crystal polymers

Abstract Dynamic liquid crystalline polymers (dLCPs) incorporate both liquid crystalline mesogens and dynamic bonds into a single polymeric material. These dual functionalities impart order‐dependent thermo‐responsive mechano‐optical properties and enhanced reprocessability/programmability enabling their use as soft actuators, adaptive adhesives, and damping materials. While many previous works studying dynamic LCPs utilize dynamic covalent bonds, metallosupramolecular bonds provide a modular platform where a series of materials can be accessed from a single polymeric feedstock through the variation of the metal ion used. A series of dLCPs were prepared by the addition of metal salts to a telechelic 2,6‐bisbenzimidazolylpyridine (Bip) ligand endcapped LCP to form metallosupramolecular liquid crystal polymers (MSLCPs). The resulting MSLCPs were found to phase separate into hard and soft phases which aids in their mechanical robustness. Variations of the metal salts used to access these materials allowed for control of the thermomechanical, viscoelastic, and adhesive properties with relaxations that can be tailored independently of the mesogenic transition. This work demonstrates that by accessing phase separation through the incorporation of metallosupramolecular moieties, highly processable yet robust MSLCP materials can be realized. This class of materials opens the door to LCPs with bulk flow behavior that can also be utilized as multi‐level adhesives.

Chemistry

PROTECT: Production and Reuse of Thermally Efficient Ceramic Thermal Protection Systems

PROTECT (Production and Reuse Of Thermally Efficient Ceramic TPS) is a NASA Early Career Initiative focused on developing the next generation of reusable ceramic thermal protection systems (TPS). This project addresses key challenges in TPS design, including temperature capability, thermal stability, and refurbishment time, by integrating novel material development with predictive modeling. Leveraging enhanced capabilities in NASA’s Porous Microstructure Analysis (PuMA) software, PROTECT introduces new modeling tools to predict the thermal and mechanical behavior of fibrous ceramic materials. These tools enable accurate prediction of performance metrics such as thermal conductivity and structural integrity, reducing reliance on costly physical testing. Preliminary advances in these areas will be presented. To support model validation, PROTECT is building a comprehensive database of raw material properties using advanced characterization techniques, including micro computed tomography (CT) scanning in collaboration with the University of Illinois Urbana-Champaign (UIUC). The presentation will detail the sampling workflows and analysis methods used to generate this detailed microstructural data and how it is used to develop improved models in PuMA. This multi-center collaboration, spanning NASA (JSC, ARC, KSC, GRC), Oak Ridge National Laboratory, UIUC, and SpaceX, is developing tailored TPS solutions for LEO, lunar, and Martian missions. By bridging heritage systems with the demands of modern spaceflight, PROTECT contributes to the advancement of reusable TPS technologies for future exploration missions.

Propulsion, Refractory, and Coating Materials

Erosion Behavior of Ti-hBN Multifunctional Coatings in A Custom-Made Planetary Test Rig at Extreme Lunar Temperatures

Spacecraft landings and takeoffs on the lunar surface, along with extreme temperature variations between day and night (-196 to 150° C), cause high-velocity dust impacts and erosion, resulting in the premature failure of structures. Ti/2 vol% hBN coatings were deposited using atmospheric (APS) and vacuum plasma spray (VPS) using cryo-milled powder feedstock to protect the structural components. The erosion performance of coatings at extreme lunar temperature regimes (-150 to 150° C) was evaluated in a custom-made planetary erosion test rig (PETR) at low (50 mph) and high impact velocities (250 mph). The mass loss of VPS coatings was reduced by 50% compared to the APS coatings and 40% compared to the Ti6Al4V substrate. The cryogenic temperature induces brittleness in the material, rendering it susceptible to extreme conditions of material loss. The particle impact-deformation behavior was captured using a high-speed camera to study the erosion mechanism. This analysis revealed chipping in substrates and brittle APS coatings, while particles rebounding and embedding were observed in VPS coatings. Energy calculations, aided by particle trajectory tracking from the high-speed camera, have conclusively shown that VPS coatings absorb 5–10% more energy than APS coatings during erosion tests. A modified erosion index was developed incorporating the fracture toughness and temperatures. New erosion models for brittle and ductile target materials are proposed for developing erosion-resistant material systems.

Abhijith Kunneparambil Sukumaran

Development of in-situ polymerized intrinsically conductive resin and low-cost carbon pigments offering high conductivity for sensing, EMI shielding and lighting protection

Electrically conductive composites are emerging across diverse industries such as electronic, automotive, aerospace, advanced air mobility, biomedical, infrastructure, defense and security offering static charge dissipation, electromagnetic interference shielding, lighting protection, sensing, dicing, corrosion monitoring, etc. Conductivity enhanced composites provide several advantages compared to conventional metals including weight reduction, corrosion resistance, energy efficient processability, tunable properties and multifunctionality. Polymers are typically insulating in nature and require conducting filler for electron transport. However, dispersion and polymer-filler interphases are critical and often disrupt conducting pathways. Besides, conductive fillers such as graphene, carbon nanotube, MXene, silver nanowire, etc. are expensive, limiting their wide adoption in composite industry. On the other hand, a limited number of intrinsically conductive polymers are available among which polyaniline (PANI) has been widely studied due to its high conductivity, thermal and chemical stability. However, PANI is difficult to process and exhibits weak mechanical properties. In brief, there is a significant demand for electrically conductive polymer formulation with cost-effective conducting fillers that offer processability in scale to expand the market of conductivity enhanced materials.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)

The Trajectory of Recent Solid State Fusion Results

Both NASA and Google have explored and funded Low Energy Nuclear Reaction (LENR) aka Solid-State Fusion or Lattice Confinement Fusion (LCF) research. NASA has funded efforts since 1989, and Google Research began in 2014. Google, and researchers initially-funded by Google, published significant scientific papers in Nature, Nature Communications and the Journal of Applied Physics. NASA began a significant set of LENR-triggering programs in 2012 resulting in papers in Physical Review C, the Journal of Electroanalytical Chemistry and the Journal of Condensed Matter Nuclear Science. Both NASA and Google engaged researchers across fields of nuclear physics, chemistry, electrochemistry, material science and more. NASA built upon early novel gas pumping experiments then followed the patented work of the US Navy SPAWAR (US8,419,919, “System and Method to Generate Particles”) and experiments with the Naval Surface Warfare Centers. Google supported researchers at Lawrence Berkeley National Laboratory (LBNL), the University of British Columbia (UBC), MIT and others. This resulted in patent applications and two granted patents (US10264661B2, “Target structure for enhanced electron screening” and US10566094B2 “Enhanced electron screening through plasmon oscillations”). These separate efforts, unknown to the researchers at the time, provided the impetus for the DoE ARPA-E LENR program followed by the DARPA DSO “Mechanisms for Amplification of Fusion Reaction Rates in Solids” (MARRS) program. This document briefly describes the overlapping NASA and Google Research efforts in plasma loading and electron screening emphasizing the results of the latest paper in Nature Communications. The papers and patents cited are listed.

electron screening

Battery Failure Databank

The Battery Failure Databank contains thermal runaway results gathered from nearly 300 small format fractional thermal runaway calorimetry (S-FTRC) experiments. A majority of these experiments were conducted at synchrotron facilities where high-speed x-ray videography was conducted of the cell while tested inside of the S-FTRC. The databank is a two-component system which consists of a Microsoft ExcelTM spreadsheet which provides S-FTRC results in tabular format and a radiographic video library containing the high-speed x-ray videos. Overall, the databank provides thermal results from S-FTRC experiments conducted on a mixture of commercially available lithium-ion (Li-ion) cells and specialized Li-ion test cells with varying cell format (18650, 21700, and D-cell) and trigger mechanism (heaters, heaters plus internal short circuiting device, and nail penetration). The radiography video component provides insight into the initiation and propagation of TR in the cells, in addition to consequences of TR measured by the FTRC. Fractions of mass ejected for the cell types are separated into regimes based on the different failure modes of the cells, such as purely venting, partial ejection, and total ejection. With knowledge of the rate and characterization of the internal degradation of the cells during TR, and the amounts of mass ejected and unrecovered, the extent of TR, and therefore the mitigation of TR, is revealed relative to cell types and failure modes.

Lithium-ion battery

Molecular origin of anisotropic shear elastoplasticity in chitin

Chitin nano- and mesoscale structures present in the exoskeleton of crustaceans exhibit exceptional longitudinal stiffness and toughness, rivaling or even exceeding that of many synthetic polymer architectures. Here, we reveal the origin of the asymmetric shear response in chitin multiscale architectures, marked by pronounced anisotropy in deformation. Under shear aligned with the molecular axis, chitin accommodates strain through coherent atomic rearrangements that enable elastic recovery. In contrast, shear applied perpendicular to this axis induces liquid-like plasticity via localized sliding. These results demonstrate the intrinsic mechanical anisotropy of chitin, underpinning a dual function in resisting repetitive loading while dissipating internal stress during high-strain events. Our findings establish the molecular basis of shear elastoplasticity in multiscale chitin structures, wherein axial elasticity supports energy storage in load-bearing regions, whereas transverse plasticity enables controlled energy dissipation. These atomic-scale insights lay a foundation for the predictive design of chitin-based materials with tunable strength-toughness profiles.

Wan, Zhangmin [University of British Columbia, Van

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue

First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks

A Chemist’s Guide to Solid-State Qubits: Diamond Color Centers as Embedded Vacancy-Centered Molecules

Diamond point defects or color centers are at the crux of solid-state quantum technology applications, from computing to sensing. Modeling molecular qubits has advanced by leaps and bounds mainly due to the advanced quantum mechanical (QM) tools in the arsenal of quantum chemists for modeling (isolated) molecular systems, which should be easily translatable for analogous systems in the solid state. Here, we simulate a series of diamond defects: a carbon vacancy (V C ) and second row substitutions that are adjacent to a V C or D C V C , with D = B, N, and O, to evaluate their magnetic and optical properties. We applied molecular orbital principles, an embedded cluster method, and a multiconfigurational QM theory to computationally characterize the above-mentioned defects for a multitude of spin, charge, and excited states. Our computational approach delivered high-quality QM insights that compare well with experiments. Furthermore, with this framework, we confirm the spin-triplets B C V C – and O C V C 0 to be analogous to N C V C – , with calculated bright transitions that respectively correspond to UV (3.80 eV) and blue (2.65 eV) light absorption and emission lifetimes (τ) of 2.3 and 5.6 ns, which are higher in energy and more short-lived (and thus brighter) than that for N C V C – : green (2.26 eV), τ = 9.5 ns.

Martirez, John Mark P. [Princeton Plasma Physics L

Novel additive manufacturing for plasma facing materials ‐ creating a research pathway for minority students

This project addresses two critical and intertwined challenges in fusion energy, namely the shortage of a broadly trained scientific workforce and the lack of scalable manufacturing solutions for plasma-facing components (PFCs). Through a collaboration among Florida International University (FIU), Miami Dade College (MDC), and Purdue University, the project established structured, reproducible educational and research pathways that recruit and advance students from institutions historically outside the fusion energy enterprise, building the human capital that this field urgently needs. The project integrates the complementary research strengths of FIU and Purdue to investigate flash sintering as a transformative processing route for tungsten-based PFCs. Unlike conventional sintering approaches, flash sintering offers rapid densification at significantly reduced thermal budgets, making it a compelling candidate for fabricating complex tungsten geometries that must withstand extreme plasma-facing environments. Systematic experimental and modeling efforts will elucidate the fundamental mechanisms governing microstructure evolution, grain boundary chemistry, and thermomechanical response during flash sintering — knowledge that is presently lacking but essential for translating this technology into reliable manufacturing practice. The convergence of workforce development and cutting-edge manufacturing research positions this project to deliver measurable, durable impact: a pipeline of fusion-ready researchers cultivated through expanded institutional partnerships, and a validated materials processing framework that accelerates domestic readiness for next-generation fusion reactor construction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Role of Amorphous Chains in Nanoplastic Formation from Semicrystalline Polymers

Semicrystalline polymers, e.g., polyethylene terephthalate (PET), release micro- (100 nm to 1 mm) and nanoplastics (up to 100 nm) [MNPL] when they are degraded under quiescent conditions. However, the exact molecular mechanisms leading to material fragmentation into MNPL are unknown. Here, we monitor the evolution of chain molecular weight and the MNPL production kinetics during hydrolysis of PET pellets. We find that only ~0.6% of the amorphous phase ester bonds are hydrolyzed at the onset of MNPL release. Then, by combining a random scission model with measured amorphous spacings, we estimate that only ~15% of the stress transmitters in the amorphous phase, namely, bridges and entangled loops, have failed by this point. Thus, spontaneous fragmentation of the semicrystalline nanostructure occurs despite significant intercrystalline connectivity. We resolve this apparent contradiction by proposing that fragmentation can only occur when progressive tie-chain scission causes the material to undergo the ductile/brittle transition. Mechanistically, we speculate that the internal stresses responsible for material fragmentation are caused by processing (i.e., residual stresses) and/or sample densification induced by chemi-crystallization. We discuss additional factors that may affect our analysis and thus require further investigation, such as skin-core effects, preferential degradation of stress transmitters and/or recrystallization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Field-tailoring quantum materials via magneto-synthesis: metastable metallic and magnetically suppressed phases in a trimer iridate

We demonstrate that applying modest magnetic fields (< 0.1 T) during high-temperature crystal growth can profoundly alter the structure and ground state of a spin-orbit-coupled, antiferromagnetic trimer lattice. Using BaIrO₃ as a model system, whose ground state is intricately dictated by the trimer lattice, we show that magneto-synthesis , a field-assisted synthesis approach, stabilizes a structurally compressed, metastable metallic and magnetically suppressed phases inaccessible via conventional methods. These effects include a 0.85% reduction in unit cell, 4-order-of-magnitude decrease in resistivity, a 10-fold enhancement of the Sommerfeld coefficient, and the collapse of long-range magnetic order -- all intrinsic and bulk in origin. First-principles calculations confirm that the field-stabilized structure lies substantially above the ground state in energy, highlighting its metastable character. These large, coherent and correlated changes across multiple bulk properties, unlike those caused by dilute impurities, defects or off-stoichiometry, point to an intrinsic field-induced mechanism. The findings establish magneto-synthesis as a powerful new pathway for accessing non-equilibrium quantum phases in strongly correlated materials.

magneto-synthesis

Cation-Diffusive Carbon Interlayers Stabilize Na Metal and Double the Current in Na-S Redox-Flow Batteries for Grid-Scale Energy Storage

The sodium-sulfur nonaqueous redox-flow batteries (Na-S NARFBs) using earth-abundant elements are highly attractive due to the low material cost and improved energy density for grid-scale energy storage. However, the low current performance, poor Na0/Na+ redox kinetics, and Na dendrite growth pose severe challenges. We introduce cation-diffusive layers (CDLs): thin and Na+ affinitive interlayers at the Na anode that direct Na+ transport and stabilize Na deposition. Benchmarking three archetypal materials—carbon paper (CP), glass microfiber paper (GF), and foam—across Na-Na and Na-Cu, and Na-S cells identifies CP as the optimum. CP reduces symmetric cell overpotential by more than 70%, achieves 98% Na plating-stripping efficiency, and doubles the Na-S cell current density from 0.5 to 1.0 mA cm−2 without sacrificing capacity or efficiency. Ex situ electrochemical and SEM/XPS analysis, combined with molecular dynamics (MD) studies, reveal that electron-rich carbon fibers disperse supporting salt aggregates, enrich near-surface Na+ density, and create ion transport pathways for fast Na0/Na+ exchange while mitigating membrane degradation. Because of the ion-centric mechanism, CDLs can be generalized to other metal-anode designs. Further, this work establishes CDL design rules—cationic affinity and appropriate micro/nanostructure—as a simple, scalable route to high-current, durable metal-anode flow batteries.

Wu, Wenda [ORNL] (ORCID:000900033307687X)