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DOE OSTI2026

Self-Assembly Interactions in Magnetite-Coated Cellulose Nanocrystals: Implications for Magnetic Hyperthermia Applications

Magnetic cellulose nanocrystal (MCNC) nanocomposites are promising sustainable and biocompatible platforms for magnetic hyperthermia; however, the molecular mechanisms governing Fe 3 O 4 adsorption and deposition onto CNCs remain poorly understood. Here, sulfated (S-CNC) and TEMPO-oxidized CNCs (T-CNC) were used to prepare nanocomposites at 1:2 and 1:4 CNC:Fe 3 O 4 mass ratios, enabling a systematic evaluation of how surface chemistry and nanoparticle loading dictate interfacial interactions and magneto-colloidal behavior. Bare magnetite nanoparticles were 21 ± 5 nm by TEM but grew to 144 ± 18 in the DLS measurement at pH 7. The S-CNC nanocomposites had hydrodynamic sizes between 144 and 210 nm, not much larger than the 140 nm long CNC rods, suggesting an enhanced dispersion stability compared to Fe3O4 alone. X-ray photoelectron spectroscopy combined with density functional theory revealed that −OH and −COOH groups drive electrostatic adsorption with charge transfer from Fe 3 O 4 to the CNC surface, while T-CNCs showed more favorable adsorption energies and evidence of covalent Fe−O bonding. Vibrating sample magnetometry demonstrated superparamagnetic behavior for all samples, with S-CNC/Fe 3 O 4 1:4 and 1:2 displaying saturation magnetizations of 78 and 77 emu/g-Fe 3 O 4 , close to the 83 emu/g of bare magnetite. The T-CNC composites showed lower (60 and 66 emu/g-Fe3O4) saturation magnetizations. Zero-field-cooled/field-cooled measurements resulted in a blocking temperature of 112 K for all samples, except T-CNC/Fe 3 O 4 1:2 (100 K). Magnetic hyperthermia studies revealed that specific absorption rate (SAR) increased with field strength and Fe 3 O 4 content; however, S-CNC/Fe 3 O 4 (1:2) achieved the highest intrinsic SAR per gram of Fe 3 O 4 (649 W/g-Fe 3 O 4 ) likely due to its anisotropy and fast magnetic relaxation. Cytotoxicity assays confirmed that all nanocomposites were nontoxic toward mammalian cells. These results establish quantitative structure−property relationships between CNC surface chemistry, interfacial bonding mechanisms, and magnetic heating performance, providing a foundation for rational design of biocompatible magnetic nanocomposites for hyperthermia and related applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Ternary Phosphides Ba M 2 P 2 : Tailoring Crystal and Electronic Structures Enables Highly Efficient HER Electrocatalysis

Binary transition metal phosphides and their solid solutions have emerged as promising hydrogen evolution reaction (HER) catalysts. Although many research endeavors have adopted strategies to vary compositions to optimize catalytic performance, they mainly focus on binary structures, which represent only a small fraction of the abundant phase space of structure types among transition metal phosphides. Here, the largely unexplored class of ternary and multinary ordered phosphides in catalysis comprises two or more metals with quite different chemical nature, concealing the structure–property relationships essential for advancing catalyst design. Here, we explored phosphides crystallizing in one of the most abundant ordered intermetallic structure types, —the ThCr 2 Si 2 type, —where square nets of 3d transition metal M and P atoms are separated by layers of electropositive Ba cations. Four ternary BaM 2 P 2 (M = Fe, Fe/Cu, Fe/Ni, Ni) catalysts were synthesized and characterized. BaNi 2 P 2 showed high HER activity in acidic electrolyte, which required an overpotential, η 10 , of only 62 mV to drive current density j = –10 mA/cm 2 and high stability with a potential drop rate of 0.25 mV/h. BaNi 2 P 2 outperformed other Ni-based catalysts, such as Ni 2 P and Ni 5 P 4 . Notably, at current densities above –170 mA/cm 2 , BaNi 2 P 2 outperformed the standard Pt electrode measured under identical conditions. Electronic structure analysis revealed a volcano-type activity trend among the four BaM 2 P 2 catalysts based on their d-band center positions, highlighting the role of electropositive Ba cations in shifting the Ni-3d orbitals into an optimal position.

BaNi2P2↗

DOE OSTI2026

Oligoether-Functionalized PEDOT: Combining an EDOT Backbone with Polar Side Chains for Solution Processability and High Electrical Conductivity

Conjugated polymers functionalized with oligoether (OE)-based side chains are a key class of materials for various organic electronic applications, including transparent electrodes, thermoelectrics, electrochromic displays, and electrochemical transistors. Herein, we report a highly soluble OE-functionalized poly(3,4-ethylenedioxythiophene) (PEDOT) homopolymer, prepared by direct (hetero)arylation polymerization, which allows solution processing to yield films with comparable redox properties to oxidatively polymerized PEDOT. This polymer, PEDOT(OE3), when optimally oxidatively doped, reaches among the highest electrical conductivities of any OE-functionalized polymer and is comparable to more synthetically complex OE-functionalized polymers. X-ray scattering and spectroscopy were utilized to rationalize the transport properties resulting from varying the doping level. Comparison of PEDOT(OE3) to a series of OE-functionalized dioxythiophenes with varying amounts of 3,4-ethylenedioxythiophene units allows for a deeper understanding of structure–property relationships through charge-transport models. Ultimately, PEDOT(OE3) is shown to be a material with exceptional charge-transport properties and is promising for various applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Synergistic Evolution of Segmental Motion and Cooperative Relaxation within the Amorphous Phase of Organic Mixed Ionic-Electronic Conductors

Organic mixed ionic-electronic conductors (OMIECs) facilitate a variety of electrochemical processes and feature a heterogeneous microstructure composed of both crystalline and amorphous phases. However, structural evolution in amorphous regions during electrochemical doping remains poorly understood, limiting our understanding of mixed conduction mechanisms. Here, in this work, we develop operando chip calorimetry to probe amorphous phase evolution in poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) under swelling and electrochemical (de)doping. Our results reveal that amorphous regions providing ionic transport pathways and those within electronic transport channels undergo heterogeneous, yet synergistic, evolution during electrochemical modulation. The cooperative interplay between segmental motion and relaxation maintains ionic conductivity and intergrain electronic transport upon electrowetting and doping, while facilitating efficient ion hopping and adaptable chain conformations during dedoping. Such synergies are more pronounced in loose structures featuring a fibrillar morphology, which exhibit lower glass transition temperatures (T g ) and higher fragility (m). High-throughput robotic screening further establishes a strong correlation between elevated m/T g ratios and enhanced mixed conduction. These findings elucidate the role of the amorphous phase in the synthesis of OMIECs and underscore the potential of operando chip calorimetry in uncovering structure–property relationships in electroactive polymers.

amorphous phase↗

DOE OSTI2026

Polymer-Grafted Nanoparticles as All-in-One Nanoplatforms

Polymer-grafted nanoparticles (PGNPs) represent a versatile class of hybrid nanomaterials, in which nanoparticle cores and tethered polymer coronas are integrated into structurally programmable building blocks. Rapid advances in nanoparticle surface functionalization and surface-initiated polymerization have enabled increasingly precise control over the nanoparticle core composition and brush architecture, greatly expanding the accessible structural and functional landscape of PGNPs. This review summarizes recent progress in the modular design and structural regulation of PGNPs, with an emphasis on nanoparticle platforms and associated surface functionalization strategies, polymer brush synthesis and architectural control, and the structure−property relationships that govern PGNP behavior. Emerging applications are further highlighted, including additive manufacturing, self-healing materials, membrane-based gas separations, and battery-related systems, where PGNPs provide unique opportunities to couple nanoscale interfacial design with macroscopic performance. Finally, future opportunities are discussed for extending PGNP concepts to increasingly complex, multifunctional, and application-oriented hybrid materials.

functional nanocomposites↗

DOE OSTI2026

Framework Short-Range Order Observed in a Spinel-Type Li Superionic Conductor

Solid-state superionic conductors are characterized by rich structural disorders. Though structural complexities are central to their functionalities, they often give rise to short-range order that eludes detection by conventional diffraction-based techniques and is thus overlooked in establishing precise structure-property relationships. In this work, we synthesized single crystals of a recently discovered lithium (Li) superionic conductor Li16.2(1)In9.00(2)Sn1.10(1)O23.8 (LISO) for in-depth characterizations of structural subtleties. LISO exhibits an unusual spinel-like phase with significant Li overstoichiometry and a face-sharing Li network. Single-crystal neutron diffraction confirms significant Li disorder, as manifested in Li site splitting and partial occupancy. More importantly, synchrotron diffuse scattering combined with 3D-ΔPDF analysis and Monte Carlo simulations reveal short-range order in the nonalkali framework that might contribute to the phase stability and ionic conductivity. This work showcases an example in which subtle local energetics can be directly visualized in structurally disordered ionic conductors.

Chen, Yu↗

DOE OSTI2026

Hierarchal structures tuned electrocaloric and electromechanical performance in PVDF-based tetrapolymers

Ferroelectrics with multifunctionalities are gaining increased interest in self-actuated electrocaloric effect (ECE) refrigerators. However, achieving high ECE and electromechanical (EM) coupling concomitantly for maximum heat transfer remains challenging. Here we present the structure-property relationship for poly(vinylidene fluoride-co-trifluoroethylene-co-chlorofluoroethylene-co-double bond), P(VDF-TrFE-CFE-DB), tetrapolymer, which exhibited a high ECE entropy change of 66.5 J Kg −1 K −1 and EM strain of −6.1%. We show that thermal treatment can be a key factor influencing multifunctional properties. High-temperature annealing incorporates DB and CFE units into crystalline grains to form extended-chain crystals, enabling CFE units to induce relaxor behavior and DB units to induce large structural changes at low electric fields. This synergy leads to an enhancement in both ECE and EM performances. Furthermore, at an optimized temperature of 50 °C, the annealed films exhibit giant cross-energy coupling, achieving ECE and EM performances of 100.8 J Kg −1 K −1 and −7.6%. This study provides insights into developing new ferroelectric polymers with electroactive multifunctionalities.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Vibrational and electronic properties of Np 2 O 5 from experimental spectroscopy and first principles calculations

High-valence actinide oxides are critical to understanding the behavior of 5f-electrons, yet their structural and electronic properties remain poorly understood due to challenges in synthesis and handling. We report the first Raman spectroscopic study of single-crystalline Np 2 O 5 and the first scanning tunneling spectroscopy (STS) measurement on any neptunium-containing material. Hydrothermally synthesized crystals were structurally verified by X-ray diffraction. Raman spectra revealed sharply resolved vibrational features, including previously unreported low-frequency modes. STS measurements revealed a band gap of 1.5 eV. Density functional theory (DFT) enables vibrational mode assignments, reveals neptunium-dominated low-frequency phonons, oxygen-dominated high-frequency modes, and predicts an indirect band gap of 1.68 eV. This predicted value is in excellent agreement with the experimentally measured STS gap. This combined Raman, DFT, and STS approach provides a robust framework for correlating lattice dynamics and electronic structure in actinide materials, providing benchmark data for Np 2 O 5 , and opening new avenues for probing structure–property relationships in complex f-electron materials.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Integrated machine learning-molecular dynamics framework for electrolyte property prediction

Electrochemical stability windows determine the operating range of battery electrolytes, yet accurate prediction remains challenging because stability emerges from statistical ensembles of local solvation environments rather than single ground-state molecular structures. Traditional density functional theory calculations on energy-minimized clusters cannot capture the thermal variations in local coordination environments and geometries that govern decomposition, while SMILES-based machine learning methods lack explicit representation of three-dimensional solvation structure and ion pairing. Here, we introduce a structure-aware machine learning framework that predicts frontier orbital energies (HOMO and LUMO) directly from molecular dynamics-sampled solvation configurations, achieving sub-0.6 eV accuracy at computational costs 3–4 orders of magnitude lower than first-principles methods. Across twelve representative battery electrolytes, we demonstrate that solvent-separated and contact ion pairs exhibit strong size- and local chemistry dependent electronic stability, with variations in coordination shifts of HOMO or LUMO level by 2–3 eV, and that extended solvation structure and partially desolvated environment further modulate stability by up to 3 eV. By encoding the statistical nature of electrochemical failure through ensemble sampling of explicit solvation geometries, our approach enables high-throughput screening and rational design of next-generation battery electrolytes with mechanistic understanding of structure–property relationships.

Energy - Storage↗

DOE OSTI2026

Single-particle detection of enhanced polarizability in Au-decorated semiconducting nanorods via scanning dielectric microscopy

Hybrid nanostructures that combine semiconducting and metallic components offer great potential for photothermal therapy, optoelectronics, and sensing, by integrating tunable optical properties with enhanced light absorption and charge transport. Boosting the integrated performance of these hybrid systems demands techniques capable of probing local variations of the physical properties inaccessible to bulk analysis. Here, we report the single-particle dielectric characterization of hybrid, semiconducting bismuth sulfide (Bi 2 S 3 ) nanorods (NR) decorated with metallic Au nanoparticles (NP), employing scanning dielectric microscopy, which uses electrostatic force microscopy in combination with finite-element numerical simulations. We reveal a pronounced enhancement in the local dielectric response of Bi2S3 upon Au decoration, attributed to interfacial polarization and electron transfer from Au to the Bi 2 S 3 matrix, thus suggesting a enhanced metallic-like polarizability at the single-particle level. Numerical simulations show that the response is dominated by the vertical component of the permittivity and that the decorating metallic Au NP produce only moderate shielding of the semiconductor Bi 2 S 3 NR core, indicating that the large increase in the dielectric response originates primarily from intrinsic modifications within the NR. Overall, these findings provide direct insight into structure–property relationships at the single-particle level, supporting the rational design of advanced hybrid nanostructures with tailored electronic functionalities.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A density-based continuous local symmetry measure

Although continuous symmetry theory has attracted increasing attention in modern chemistry, local symmetry remains under-investigated. As a consequence, the relationship between symmetry and chemical behavior is often obscured, limiting the practical use of fuzzy symmetry measures. Here, in this study, we introduce a novel framework for evaluating local symmetry based on electron density localization and present continuous symmetry representations for several representative molecules. Our approach not only quantitatively captures global symmetry but also reveals distinctive features of symmetry in a local chemical environment. The related concept, local chirality or chirotopicity, is also discussed. Overall, the proposed local symmetry and chirality measures provide valuable insights into molecular structure and structure–property relationships.

Lai, Duc Anh [Southern Methodist Univ., Dallas, TX↗

DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗

DOE OSTI2026

The Influence of Shielding Gas on the Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Wire-arc additive manufacturing (WAAM) enables building large near-net-shaped parts using fast deposition rates and is attractive due to the potential cost and schedule savings. Haynes® 282® is a Ni-based superalloy with wide application in advanced power generation systems for its superior high temperature mechanical properties. High-quality WAAM H282 parts are achieved through careful process optimization, hence, we have focused on systematically characterizing the processing-structure-properties relationships over a wide range of wire-feed and travel speeds using a standard Ar30He shielding gas. Here the influence of adding 0.25-3% of H2 and CO2 to Ar-30He standard on our findings is examined. Multi-bead tracks were used to screen 20+ gas combinations to examine impact on wettability, porosity, oxidation, and grain structures. Improved multi-tracks are observed for gases with up to 1% H2 and 0.25% CO2. WAAM H282 builds within this range are examined to reveal differences in microstructure as evaluated with CT, SEM-EDS, and EBSD.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗

DOE OSTI2026

High entropy oxides prediction and discovery by the Mixed Enthalpy-Entropy Descriptor

The vast, high-dimensional composition space of high-entropy oxides (HEOs) offers exceptional opportunities for functional materials discovery, yet it also poses a fundamental challenge: the rational and efficient prediction of stable, synthesizable compositions and the corresponding structure–property relationships. Despite growing interest, the field still lacks broadly applicable, physically grounded descriptors capable of navigating various large chemical spaces. Here, we introduce a Mixed Enthalpy–Entropy Descriptor (MEED) that enables rapid, first-principles–based prediction of HEOs synthesizability across diverse chemistries. Using MEED, we perform high-throughput screening of two distinct HEO families: rocksalt oxides and perovskite oxides. The predicted top candidates in each family were experimentally validated. MEED reveals unifying thermodynamic and structural principles governing stability across both chemical compositions and polymorphs, providing mechanistic insight into the formation of high-entropy phases. This work significantly broadens the accessible chemical design space for HEOs and establishes a data-efficient framework for accelerating the discovery of next-generation functional materials.

Yu, Liping [University of Central Florida]↗

DOE OSTI2026

Thermoelectric Behavior of Structurally Disordered Lanthanide and Actinide Silicides

Lanthanide and actinide intermetallic materials exhibit intriguing electronic, structural, and magnetic properties arising from their partially filled f orbitals. Strong f-electron correlations can significantly modify the electronic density of states, carrier scattering, and transport behavior, making these systems promising candidates for unconventional thermoelectric materials. In previous studies, single crystals of A1.33T4Al8Si2 (A = Ce, Th, U, Np; T = Co, Ni) were synthesized. This structure consists of ordered TAl2 corrugated double layers separated by disordered An–Si monolayers. The inherent disorder within the An–Si layers has been linked to unusual magnetic behavior, such as spin-glass phenomena, and is expected to strongly influence phonon scattering and charge-carrier transport relevant to thermoelectric performance. However, the thermoelectric properties of this material family have not previously been explored. In this work, DFT calculations were performed to evaluate the electronic density of states, band structures, and thermoelectric properties, including the effects of doping. To validate these predictions, Ce1.33Co4Al8Si2 single crystals were grown and experimentally characterized. Additionally, a new Yb1.33Co4Al8Si2 phase was synthesized and characterized using single-crystal XRD, SEM-EDS, magnetization measurements, and thermoelectric measurements. These results provide insight into structure–property relationships governing thermoelectric behavior in f-electron intermetallics and offer guidance for future thermoelectric materials.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

DOE OSTI2026

Establishing an acoustic-property relationship in laser powder bed fusion with machine learning

Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.

Acoustic emission↗