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DOE OSTI2013

Enhancement of cancer stem-like and epithelial−mesenchymal transdifferentiation property in oral epithelial cells with long-term nicotine exposure: Reversal by targeting SNAIL

Cigarette smoking is one of the major risk factors in the development and further progression of tumorigenesis, including oral squamous cell carcinoma (OSCC). Recent studies suggest that interplay cancer stem-like cells (CSCs) and epithelial−mesenchymal transdifferentiation (EMT) properties are responsible for the tumor maintenance and metastasis in OSCC. The aim of the present study was to investigate the effects of long-term exposure with nicotine, a major component in cigarette, on CSCs and EMT characteristics. The possible reversal regulators were further explored in nicotine-induced CSCs and EMT properties in human oral epithelial (OE) cells. Long-term exposure with nicotine was demonstrated to up-regulate ALDH1 population in normal gingival and primary OSCC OE cells dose-dependently. Moreover, long-term nicotine treatment was found to enhance the self-renewal sphere-forming ability and stemness gene signatures expression and EMT regulators in OE cells. The migration/cell invasiveness/anchorage independent growth and in vivo tumor growth by nude mice xenotransplantation assay was enhanced in long-term nicotine-stimulated OE cells. Knockdown of Snail in long-term nicotine-treated OE cells was found to reduce their CSCs properties. Therapeutic delivery of Si-Snail significantly blocked the xenograft tumorigenesis of long-term nicotine-treated OSCC cells and largely significantly improved the recipient survival. The present study demonstrated that the enrichment of CSCs coupled EMT property in oral epithelial cells induced by nicotine is critical for the development of OSCC tumorigenesis. Targeting Snail might offer a new strategy for the treatment of OSCC patients with smoking habit. -- Highlights: ► Sustained nicotine treatment induced CSCs properties of oral epithelial cells. ► Long-term nicotine treatment enhance EMT properties of oral epithelial cells. ► Long-term nicotine exposure increased tumorigenicity of oral epithelial cells. ► Si-Snail blocked xenograft tumorigenesis of long-term nicotine-treated OSCC cells.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Characterisation of sludge for pyrolysis conversion process based on biomass composition analysis and simulation of pyrolytic properties

Highlights: • Characterisation of different types sewage sludge for pyrolytic properties. • Developed analytical procedure to categorise and quantify composition of sludge. • Observed qualitative similarity and quantitative variation on properties of sludge. • Correlated organic components with thermochemical properties of sludge. • Coupled model compounds selection and composition analysis for simulation study. - Abstract: Pyrolytic behaviour of sludge is highly complex and obscure because of its heterogeneous and diverse composition. Therefore, an analytical procedure is proposed to categorise and quantify the main constituents in sludge. In addition, a simulation study of sludge characteristics is carried out to complement the composition analysis and to improve our understanding on the relationship between composition of sludge and its corresponding properties. Different types of sludge samples were collected at different treatment stages from four Water Reclamation Plants in Singapore in two separate batches. Model compounds are selected to represent components identified and are used in simulation of pyrolytic properties of sludge. Constituents of sludge are adequately categorised, quantified and characterised in this study. Qualitative similarities and quantitative variations on characteristics of different sludge samples were identified. Comparison among the samples collected with the simulation provided insights on how differences in organic composition of sludge affected its properties.

09 BIOMASS FUELS↗

DOE OSTI2018

DNA Templated Metal Nanoclusters: From Emergent Properties to Unique Applications

Metal nanoclusters containing a few to several hundred atoms with sizes ranging from sub-nanometer to ~2 nm occupy an intermediate size regime that bridges larger plasmonic nanoparticles and smaller metal complexes. With strong quantum confinement, metal nanoclusters exhibit molecule-like properties. This paper focuses on noble metal nanoclusters that are synthesized within a single stranded DNA template. Compared to other ligand protected metal nanoclusters, DNA-templated metal nanoclusters manifest intriguing physical and chemical properties that are heavily influenced by the design of DNA templates. For example, DNA-templated silver nanoclusters can show bright fluorescence, tunable emission colors, and enhanced stability by tuning the sequence of the encapsulating DNA template. DNA-templated gold nanoclusters can also serve as excellent cocatalysts, which are integratable with other biocatalysts such as enzymes. In this Account, DNA-templated silver and gold nanoclusters are selected as paradigm systems to showcase their emergent properties and unique applications. We first discuss the DNA-templated silver nanoclusters with a focus on the creation of a complementary palette of emission colors, which has potential applications for multiplex assays. The importance of the DNA template toward enhanced stability of silver nanoclusters is also demonstrated. We then introduce a special class of activable fluorescence probes that are based on the fluorescence turn-on phenomena of DNA-templated silver nanoclusters, which are named nanocluster beacons (NCBs). NCBs have distinct advantages over molecular beacons for nucleic acid detection, and their emission mechanisms are also discussed in detail. We then discuss a universal method of creating novel DNA–silver nanocluster aptamers for protein detection with high specificity. The remainder of the Account is devoted to the DNA-templated gold nanoclusters. We demonstrate that DNA–gold nanoclusters can serve as enhancers for enzymatic reduction of oxygen, which is one of the most important reactions in biofuel cells. Although DNA-templated metal nanoclusters are still in their infancy, we anticipate they will emerge as a new type of functional nanomaterial with wide applications in biology and energy science. Future research will focus on the synthesis of size selected DNA–metal nanoclusters with atomic monodispersity, structural determination of different sized DNA–metal nanoclusters, and establishment of structure–property correlations. Some long-standing mysteries, such as the origin of fluorescence and mechanism for emission color tunability, constitute the central questions regarding the photophysical properties of DNA–metal nanoclusters. On the application side, more studies are required to understand the interaction between nanocluster and biological systems. In the foreseeable future, one can expect that new biosensors, catalysts, and functional devices will be invented based on the intriguing properties of well-designed DNA–metal nanoclusters and their composites. Altogether, DNA–metal nanoclusters can add additional spotlights into the highly vibrant field of ligand protected, quantum sized metal nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Target Configuration Effect on Microstructures and Properties of Vertically Aligned Nanocomposites

Vertically aligned nanocomposites (VANs) are unique thin films with vertical nanostructures embedded in a matrix material, allowing for the integration of two distinct materials. These nanocomposites offer novel combined physical properties, such as nanocomposite-based multiferroics and strongly coupled physical properties, such as magneto-optic coupling. Much work has been conducted in exploring different two-phase combinations and various processing conditions to achieve novel tunable properties that cannot be obtained by any single-phase material alone. Here, in this work, the target configuration effects are explored for the growth of LaFeO 3 –CoNi 2 O 4 VANs. Both mixed and pie-shaped targets are utilized to compare the target configuration effects on the phase separation, morphology tuning, and their resulting physical properties, including optical and magnetic properties. This work suggests that the target configuration is another important parameter for achieving the desired VAN morphology and can be used to design different two-phase VANs with tailorable properties.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Silicene, Siloxene, or Silicane? Revealing the Structure and Optical Properties of Silicon Nanosheets Derived from Calcium Disilicide

Si-nanosheets (Si-NSs) have recently attracted considerable attention due to their potential as next-generation materials for electronic, optoelectronic, spintronic, and catalytic applications. Even though monolayer Si-NSs were first synthesized over 150 years ago via topotactic deintercalation of CaSi 2 , there is a lack of consensus within the literature regarding the structure and optical properties of this material. Herein, we provide conclusive evidence of the structural and chemical properties of Si-NSs produced by the deintercalation of CaSi 2 with cold (~–30 °C) aqueous HCl and characterize their optical properties. We use a wide range of techniques, including XRD, FTIR, Raman, solid-state NMR, SEM, TEM, EDS, XPS, diffuse reflectance absorbance, steady-state photoluminescence, time-resolved photoluminescence, and thermal decomposition; when they are combined together, these techniques enable unique insight into the structural and optical properties of the Si-NSs. Additionally, we support the experimental findings with density functional theory (DFT) calculations to simulate FTIR, Raman, solid-state NMR, interband electronic transitions, and band structures. We determined that the Si-NSs consist of buckled Si monolayers that are primarily monohydride terminated. We characterize the nanosheet optical properties, finding they have a band gap of ~2.5 eV with direct-like behavior and an estimated quantum yield of ~9%. Given the technological importance of Si, these results are encouraging for a variety of optoelectronic technologies, such as phosphors, light-emitting diodes, and CMOS-compatible photonics. Furthermore, our results provide critical structural and optical properties to help guide the research community in integrating Si-NSs into optoelectronic and quantum devices.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Photophysical Properties and Electronic Structure of Hydroporphyrin Dyads Exhibiting Strong Through-Space and Through-Bond Electronic Interactions

Electronic interactions between tetrapyrroles are utilized in natural photosynthetic systems to tune the light-harvesting and energy/charge-transfer processes in these assemblies. Such interactions also can be employed to tailor the electronic properties of tetrapyrrolic dyads and larger arrays for use in materials science and biomedical research. Here we have utilized static and time-resolved optical spectroscopy to characterize the optical absorption and emission properties of a set of chlorin and bacteriochlorin dyads with varied degrees of through-bond (TB) and through-space (TS) interactions between the constituent macrocycles. The dyads consist of two chlorins or two bacteriochlorins joined by a linker that utilizes a triple-double-triple bond (enediyne) motif in which the double bond portion is a ester-substituted ethylene or o-phenylene unit. The photophysical studies are coupled with density functional theory (DFT) calculations to probe the ground-state molecular orbital (MO) characteristics of the dyads and time-dependent calculations (TDDFT) to elucidate excited-state properties. The latter include electronic characteristics of the singlet excited state manifold and the absorption transitions to these states from the electronic ground state. Comparison of the MO and calculated spectral properties of each dyad with the linker present versus disrupted (by eliminating the double-bond portion) gives insight into the relative contributions of TB versus TS interactions to the electronic properties of the dyads. The results show that the TB and TS contributions are additive (constructively interfere), which is not always the case for molecular dyads. Most of the dyads have shorter lifetimes of the lowest singlet excited state compared to the parent monomer, which derives from increased S 1 → S 0 internal conversion. The enhancement is greater for the dyads in benzonitrile than in toluene. Furthermore, the studies provide insights into the nature of the electronic interactions between the constituents in the tetrapyrrole arrays and how these interactions dictate the spectral properties and excited-state decay characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Analysis of the Amorphous and Interphase Influence of Comononomer Loading on Polymer Properties toward Forwarding Bioadvantaged Copolyamides

In this paper we present an approach for selectively modifying the properties of semicrystalline polymers by introducing “bioadvantaged” counits. With this approach, the unique functionality of biomass can be leveraged to tailor the properties of the amorphous phase of semicrystalline polymers with minimal impact on crystallinity and thermomechanical properties. As a model case, PA 6,6 copolyamides were produced using the bioadvantaged monomer trans-3-hexenedioic acid (t3HDA). The analogous structure of t3HDA to adipic acid, a PA 6,6 monomer, allows for seamless integration. Screening over the entire composition range identified the t3HDA loading (20 mol%) beyond which properties deviate appreciably from Nylon 6,6. Once identified, copolyamides of suitable compositions were upgraded to commercial quality and fully characterized to assess the influence of counit loading and polymer structure on thermal and mechanical properties. Samples were characterized using gel permeation chromatography (GPC), proton nuclear magnetic resonance spectroscopy (1H NMR), heteronuclear single quantum coherence spectroscopy (HSQC), wide-angle X-ray scattering (WAXS), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA), tensile testing, flexural testing, and water absorption testing. t3HDA units were shown to hydrate during the harsh polycondensation to 3-hydroxyhexanedioic acid (3HHDA) and fully incorporate into the polymer backbone. Loading levels up to 20% were shown to have comparable thermal and mechanical properties in the dry state, yet moisture absorption—a known method for improving the toughness, yield strain, and elongation of polyamides—was enhanced by over 100% at 20% loading. This case study on bioadvantaged copolymers elucidates the governing structure-function principles that can be leveraged to forward value-added renewable polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Critical Assessment of Electronic Structure Descriptors for Predicting Perovskite Catalytic Properties

The discovery and design of materials which can efficiently catalyze the oxygen reduction and evolution reactions at reduced temperatures is important for facilitating the widespread adoption of fuel cell and electrolyzer technologies. Numerous studies have produced correlations between catalytic properties, such as oxygen surface exchange or electrode area specific resistance (ASR), and properties of the catalyst material. However, correlations have historically been limited in scope (e.g., using only a few materials or at a single temperature) and it has been difficult to provide detailed assessments of their robustness. Here, in this study, we assess the ability of the O p-band center electronic structure descriptor, obtained from density functional theory (DFT) calculations, to correlate with oxygen surface exchange rates, diffusivities, and area specific resistances for a large database of perovskite oxide catalytic properties. By data mining the literature, we obtain 747 catalytic property value data points spanning 299 unique perovskite compositions from 313 studies. We assess linear correlations of each property with the O p-band center and find generally modest correlations that are qualitatively useful (prediction mean absolute errors of about 0.5 log units are typical), where the correlations are improved at higher temperatures (e.g., 800 °C vs. 500 °C) and significantly improve when considering fits to the subset of materials which have multiple independent measurements. These findings suggest that the spread of property data is significantly influenced by experimental uncertainty, and subsequent measurements of additional materials will likely improve the O p-band center correlations.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗

DOE OSTI2019

Measurement of Physicochemical Properties of Lignin

Lignin is an essential cell wall component of lignocellulose. Unlike other major components such as cellulose and hemicellulose, lignin is a noncarbohydrate biopolymer and contributes to cell wall rigidity and hydrophobicity. Lignin’s unique properties contribute to the transportation of water and minerals in plants and protect against microbial attacks, while the latter property hinders the conversion of carbohydrates in lignocellulose. Also, its heterogeneity and structural complexity are major recalcitrance factors in biomass conversion. Various approaches (including genetically engineered plants, pulping, pretreatments, and fractionation processes) have been proposed to reduce and/or remove lignin for effective conversion of lignocellulose. Recently, interest in the biorefinery concept considers lignin as a potential feedstock in many applications; however, the technologies necessary to facilitate the economic production of many lignin-based products is still in its infancy. For the effective utilization of lignocellulose, understanding the physicochemical properties of lignin is the first and last step. It not only provides the key information about lignin structures in the original plant cell wall, conversion products, or residues, but also explains how the modification and/or conversion process affects lignin and biomass in general. Many different lignin characteristics, including physicochemical, morphological, and thermal properties, can be measured by diverse analytical techniques. This chapter introduces analytical methods that measure several essential physicochemical properties of lignin, such as molecular weights by gel permeation chromatography (GPC), quantitative and qualitative information of structural properties (interunit linkages and aromatic subunits) by one-dimensional and two-dimensional nuclear magnetic resonance (NMR), and hydroxyl group content by 31P NMR.

Yoo, Chang Geun↗

DOE OSTI2020

Evolution of Elastic and Mechanical Properties During Fault Shear: The Roles of Clay Content, Fabric Development, and Porosity

Phyllosilicates weaken faults due to the formation of shear fabrics. Although the impacts of clay abundance and fabric on frictional strength, sliding stability, and porosity of faults are well studied, their influence on elastic properties is less known, though they are key factors for fault stiffness. We document the role that fabric and consolidation play in elastic properties and show that smectite content is the most important factor determining whether fabric or porosity controls the elastic response of faults. We conducted a suite of shear experiments on synthetic smectite-quartz fault gouges (10–100 wt% smectite) and sediment incoming to the Sumatra subduction zone. We monitored Vp, Vs, friction, porosity, shear and bulk moduli. We find that mechanical and elastic properties for gouges with abundant smectite are almost entirely controlled by fabric formation (decreasing mechanical and elastic properties with shear). Though fabrics control the elastic response of smectite-poor gouges over intermediate shear strains, porosity is the primary control throughout the majority of shearing. Elastic properties vary systematically with smectite content: High smectite gouges have values of Vp ~ 1,300–1,800 m/s, Vs ~ 900–1,100 m/s, K ~ 1–4 GPa, and G ~ 1–2 GPa, and low smectite gouges have values of Vp ~ 2,300–2,500 m/s, Vs ~ 1,200–1,300 m/s, K ~ 5–8 GPa, and G ~ 2.5–3 GPa. We find that, even in smectite-poor gouges, shear fabric also affects stiffness and elastic moduli, implying that while smectite abundance plays a clear role in controlling gouge properties, other fine-grained and platy clay minerals may produce similar behavior through their control on the development of fabrics and thin shear surfaces.

58 GEOSCIENCES↗

DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗

DOE OSTI2021

Structural and physical properties of 99 complex bulk chalcogenides crystals using first-principles calculations

Chalcogenide semiconductors and glasses have many applications in the civil and military fields, especially in relation to their electronic, optical and mechanical properties for energy conversion and in enviormental materials. However, they are much less systemically studied and their fundamental physical properties for a large class chalcogenide semiconductors are rather scattered and incomplete. Here, we present a detailed study using well defined first-principles calculations on the electronic structure, interatomic bonding, optical, and mechanical properties for 99 bulk chalcogenides including thirteen of these crytals which have never been calculated. Due to their unique composition and structures, these 99 bulk chalcogenides are divided into two main groups. The first group contains 54 quaternary crystals with the structure composition (A2BCQ4) (A = Ag, Cu; B = Zn, Cd, Hg, Mg, Sr, Ba; C = Si, Ge, Sn; Q = S, Se, Te), while the second group contains scattered ternary and quaternary chalcogenide crystals with a more diverse composition (AxByCzQn) (A = Ag, Cu, Ba, Cs, Li, Tl, K, Lu, Sr; B = Zn, Cd, Hg, Al, Ga, In, P, As, La, Lu, Pb, Cu, Ag; C = Si, Ge, Sn, As, Sb, Bi, Zr, Hf, Ga, In; Q = S, Se, Te; x=1, 2, 3; y=0, 1, 2, 5; z=0, 1, 2 and n=3, 4, 5, 6, 9). Moreover, the total bond order density (TBOD) is used as a single quantum mechanical metric to characterize the internal cohesion of these crystals enabling us to correlate them with the calculated properties, especially their mechanical properties. This work provides a very large database for bulk chalcogenides crucial for the future theoretical and experimental studies, opening opportunities for study the properties and potential application of a wide variety of chalcogenides.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Microphysical properties of atmospheric soot and organic particles: measurements, modeling, and impacts

Atmospheric soot and organic particles from fossil fuel combustion and biomass burning modify Earth’s climate through their interactions with solar radiation and through modifications of cloud properties by acting as cloud condensation nuclei and ice nucleating particles. Recent advancements in understanding their individual properties and microscopic composition have led to heightened interest in their microphysical properties. This review article provides an overview of current advanced microscopic measurements and offers insights into future avenues for studying microphysical properties of these particles. To quantify soot morphology and ageing, fractal dimension ( D f ) is a commonly employed quantitative metric which allows to characterize morphologies of soot aggregates and their modifications in relation to ageing factors like internal mixing state, core-shell structures, phase, and composition heterogeneity. Models have been developed to incorporate D f and mixing diversity metrics of aged soot particles, enabling quantitative assessment of their optical absorption and radiative forcing effects. The microphysical properties of soot and organic particles are complex and they are influenced by particle sources, ageing process, and meteorological conditions. Furthermore, soluble organic particles exhibit diverse forms and can engage in liquid–liquid phase separation with sulfate and nitrate components. Primary carbonaceous particles such as tar balls and soot warrant further attention due to their strong light absorbing properties, presence of toxic organic constituents, and small size, which can impact human health. Future research needs include both atmospheric measurements and modeling approaches, focusing on changes in the mixing structures of soot and organic particle ensembles, their effects on climate dynamics and human health.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Designing interchain and intrachain properties of conjugated polymers for latent optical information encoding

Building molecular-design insights for controlling both the intrachain and the interchain properties of conjugated polymers (CPs) is essential to determine their characteristics and to optimize their performance in applications. However, most CP designs have focused on the conjugated main chain to control the intrachain properties, while the design of side chains is usually used to render CPs soluble, even though the side chains critically affect the interchain packing. Here, we present a straightforward and effective design strategy for modifying the optical and electrochemical properties of diketopyrrolopyrrole-based CPs by controlling both the intrachain and interchain properties in a single system. The synthesized polymers, P1, P2 and P3, show almost identical optical absorption spectra in solution, manifesting essentially the same intrachain properties of the three CPs having restricted effective conjugation along the main chain. However, the absorption spectra of CP films are gradually tuned by controlling the interchain packing through the side-chain design. Here, based on the tailored optical properties, we demonstrate the encoding of latent optical information utilizing the CPs as security inks on a silica substrate, which reveals and conceals hidden information upon the reversible aggregation/deaggregation of CPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Enhanced magnetic and optical properties of Y 3 Fe 5 O 12 (YIG) films with Au nanoinclusions

Y 3 Fe 5 O 12 (YIG) thin films are well known for their ferrimagnetic insulating property and low Gilbert damping coefficient (α), allowing them to be used for various spintronic applications and as magneto-optical isolators for photonic devices. Instead of doping, incorporation of plasmonic metals as nanoinclusions could be a promising route for improved magneto-optical coupling properties. In this work, YIG–Au nanocomposites have been deposited with ferrimagnetic insulating YIG as the matrix and Au nanoinclusions which introduce plasmonic absorption, optical anisotropy, and hyperbolic properties. Films with varying Au nanoinclusion densities have been processed and annealed to compare with the as-deposited ones. The films that had low Au nanoinclusion density and were annealed presented a lower magnetic damping coefficient of 2.84 × 10 −4 than the pure YIG film (9.66 × 10 −4 ). The as-deposited film with the highest Au density shows the strongest hyperbolic properties among all samples. These results demonstrate that both magnetic damping and optical properties can be tuned through deposition conditions in YIG–Au nanocomposite thin films, allowing for a balance of both properties. This YIG–Au nanocomposite system presents promising potential in next-generation opto-spintronic devices.

Quigley, Lizabeth [Purdue Univ., West Lafayette, I↗

DOE OSTI2013

Interplay between chemical state, electric properties, and ferromagnetism in Fe-doped ZnO films

Valence state of Fe ions plays an important role in the physical properties of Fe doped ZnO films. Here, a series of Zn{sub 1-x}Fe{sub x}O films with different Fe concentrations (x = 0, 2.3, 5.4, 7.1, and 9.3 at. %) were prepared to investigate their structural, piezoelectric, ferroelectric, bipolar resistive switching properties, and electrical-control of ferromagnetism at room temperature. The structure characterizations indicate that the chemical state of Fe ions substituting Zn{sup 2+} site changes from Fe{sup 3+} to Fe{sup 2+} with the increase of Fe dopant concentration. We found enhanced piezoelectric and ferroelectric properties in Zn{sub 0.977}Fe{sub 0.023}O films with more Fe{sup 3+} due to the smaller Fe{sup 3+} ionic size in comparison with Zn{sup 2+} while the increase of Fe{sup 2+} concentration by a larger amount of Fe dopant results in the worse ferroelectric and piezoelectric performance. All Pt/Zn{sub 1-x}Fe{sub x}O/Pt devices show bipolar resistive switching properties. Especially, devices with lower Fe dopant concentration exhibit better endurance properties due to their higher crystalline quality. The variation of oxygen vacancies during resistive switching provides an opportunity to tune ferromagnetism of Fe-doped ZnO films, giving rise to the integration of charge and spin into a simple Pt/Zn{sub 1-x}Fe{sub x}O/Pt devices. The multifunctional properties of Fe-doped ZnO films are promising for communication systems and information storage devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗