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DOE OSTI2022

Naturally Self-Tuned Low Mass Composite Scalars

Scalar bosons composed of a pair of chiral fermions in a non-confining potential have an effective Yukawa coupling, $g$, to free external chiral fermions. At large distance a Feynman loop of external fermions generates a scale invariant potential, $V_{loop}\propto -g^2/{\rho^{2}}$, for separation $\rho$, which acts on valence fermions. This generally forces the $s$-wave ground state to deform to a static, zero mass, configuration, and for slowly running, perturbative $g$, a large external "shroud" wave function forms. This is related to old results of Landau and Lifshitz in quantum mechanics. The massless composite scalar boson ground state is then an extended object. Infra-red effects can generate a small mass for the system. This points to a perturbative BEH-boson composed of top and anti-top quarks and a novel dynamical mechanism for spontaneous electroweak symmetry breaking.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Structural coherence model for predicting molten salt thermal conductivity informed by the pair distribution function

To enable thermal behavior prediction and design optimization of molten salt reactors, thermal conductivity of molten salts must be characterized in terms of salt composition and temperature. Current theoretical models fail to provide consistent approximations for all halide mixtures, particularly actinide-bearing melts. This study aims to link the short-range order structure of molten salts to the mean free path of energy carriers through a simple structural coherence model informed by the partial pair distribution function. The proposed method is used to predict the thermal conductivity of 33 alkali and alkaline earth halide salts. Predictions approximate experimental measurements with a mean absolute error of 15.7% for dissociating, complexing, and actinide salts, including unary LiCl, NaCl, and MgCl 2 as well as mixtures LiF–NaF–KF (FLiNaK), LiF–BeF 2 (FLiBe), and NaCl–UCl 3 . The work provides evidence for the validity of energy carrier descriptions of molecular-level heat transfer in molten salts, with implications for improved theories of liquid energy transport in general.

Actinide mixtures↗

DOE OSTI2020

Environmental remediation with functional aerogels and xerogels

Several different types of aerogel and/or xerogel scaffolds have been demonstrated as effective sorbents for the capture and immobilization of radionuclides in gaseous form [e.g., iodine gas or I2(g), Xe] as well as ionic form (e.g., Ce4+, Cs+, I–, IO3-, Rb+, Sr2+, 99Tc7+, and U6+). These scaffolds have unique properties, which include high specific surface areas, high pore volumes, varieties of pore sizes, and functionalities that provide methods for binding radionuclides through physisorption, chemisorption, or a combination thereof. This combination of properties and functionalities make these types of materials ideal scaffolds for use as sorbents for capturing radionuclides. The primary base materials that will be discussed in this chapter include Ag0-functionalized silica aerogels, Ag+-impregnated aluminosilicate aerogels, Ag0-functionalized aluminosilicate aerogels, metal-impregnated (non-Ag) aluminosilicate aerogels and xerogels, sulfide-based aerogels, and carbon-based aerogel composites. For the capture of I2(g), the materials reported herein show some of the highest iodine loadings ever reported for inorganic sorbents. For the capture of ionic species, these materials also show promise to be some of the next generations of materials for active radionuclide remediation. This progress report will describe how these materials are fabricated, the general properties of these materials, as well as an overview of how they have been used for different applications in environmental remediation of radionuclides.

aerogel, xerogel, iodine, radionuclide remediation↗

DOE OSTI2026

MoNbTi-based Refractory Multi-principal Element Alloy System: A Review of the Thermodynamic Phase Predictions, Formed Microstructures, and Mechanical Properties as a Function of the Fabrication Methods (AM versus SPS versus VAM)

Abstract Multi-principal element alloys, particularly of refractory compositions, are an increasingly popular candidate for extreme-environment applications, including for next-generation nuclear reactors and in other industries, such as biomedical and aerospace, due to their high strength. The ability to achieve solid-solution microstructures provides these alloys with improved mechanical properties; however, these microstructures are heavily composition- and processing-dependent. In this review, the multi-principal element alloy MoNbTi-based system (with Zr, V, and Cr additions) was selected to compare the effects of elemental composition and processing route on the resulting microstructures and mechanical properties. The review provides insight into identifying the optimal alloy composition and processing route for a balance of desired microstructure and mechanical properties.

Krogh, Kara↗

DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗

DOE OSTI2022

Determining the Role of Synthesis and Reaction Conditions on the Exposed Surface and Shape of ..beta..-Mo2C Catalysts

The production of drop-in quality biofuels typically can be achieved through catalytic fast pyrolysis (CFP) of biomass, followed by hydrodeoxygenation (HDO) of the vapor-phase product to reduce the oxygen content and stabilize the bio-oil product. To favor selectivity toward desired deoxygenation products, bifunctional catalysts with both acidic and hydrogenation sites are often employed. Due to both its oxophilicity and its ability to promote hydrogenation reactions, molybdenum carbide catalysts have shown promise for promoting the HDO of CFP vapors. However, the surface structure and composition of carbide catalyst particles are not well understood, precluding the establishment of fundamental structure-function relationships needed for the rational development of molybdedum carbide for HDO, as well as other reactions. For orthorhombic ..beta..-Mo2C, the (100) facet is largely studied for computational surface-reaction analyses, possibly due to its similarities with the close-packed (111) facet of noble-metal catalysts. However, it has previously been postulated through ab initio thermodynamic studies that the (111), (110), and (011) facets are most stable, though there is no consensus. Furthermore, while a majority of previous surface stability analyses of ..beta..-Mo2C focus on bulk terminations, the highly carburizing synthesis conditions and the use of ..beta..-Mo2C in carbon-containing reaction applications could introduce non-stoichiometric coverages of surface carbon. As such, this study uses ab initio thermodynamics calculations to assess the relative surface stability of the low-index facets of ..beta..-Mo2C, including consideration of varying the coverage of surface carbon. From this information, Wulff constructions are utilized to predict the synthesis and reaction condition-dependent shape and surface carbon composition of ..beta..-Mo2C catalyst particles.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

DOE OSTI2021

Colloidal synthesis and charge carrier dynamics of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) layered double perovskite nanocrystals

The toxicity and instability of lead-based metal halide perovskites are the two main obstacles that prevent perovskite materials from implementation in applications. Recently, layered double perovskites (LDPs) emerge as a new family of perovskite materials which provide a new route to solve these problems by lead-component replacement and reduction of crystal structure dimensionality. However, LDP nanocrystals (NCs) have been rarely studied, limiting the further property exploration and application realization. In this work, we report the colloidal synthesis of a series of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) LDP NCs by tuning the stoichiometry of metal precursors. The composition-structure-property relationships of the resulting LDP NCs are studied through materials characterizations, density functional theory calculations, and transient-absorption spectroscopy. In addition, we demonstrate that high-performance high-speed photodetectors can be fabricated using the colloidal LDP NCs through solution-processing. This work premises further expansion of such LDP-based materials for both fundamental studies and application integrations.

25 ENERGY STORAGE↗

DOE OSTI2022

Oxygen diffusion in garnet: Experimental calibration and implications for timescales of metamorphic processes and retention of primary O isotopic signatures

Knowledge of oxygen diffusion in garnet is crucial for a correct interpretation of oxygen isotope signatures in natural samples. A series of experiments was undertaken to determine the diffusivity of oxygen in garnet, which remains poorly constrained. The first suite included high-pressure (HP), nominally dry experiments performed in piston-cylinder apparatus at: (1) T = 1050–1600 °C and P = 1.5 GPa and (2) T = 1500 °C and P = 2.5 GPa using yttrium aluminum garnet (YAG; Y3Al5O12) cubes. Second, HP H2O-saturated experiments were conducted at T = 900 °C and P = 1.0–1.5 GPa, wherein YAG crystals were packed into a YAG + Corundum powder, along with 18O-enriched H2O. Third, 1 atm experiments with YAG cubes were performed in a gas-mixing furnace at T = 1500–1600 °C under Ar flux. Finally, an experiment at T = 900 °C and P = 1.0 GPa was done using a pyrope cube embedded into pyrope powder and 18O-enriched H2O. Experiments using grossular were not successful. Profiles of 18O/(18O+16O) in the experimental charges were analyzed with three different secondary ion mass spectrometers (SIMS): sensitive high-resolution ion microprobe (SHRIMP II and SI), CAMECA IMS-1280, and NanoSIMS. Considering only the measured length of 18O diffusion profiles, similar results were obtained for YAG and pyrope annealed at 900 °C, suggesting limited effects of chemical composition on oxygen diffusivity. However, in both garnet types, several profiles deviate from the error function geometry, suggesting that the behavior of O in garnet cannot be fully described as simple concentration-independent diffusion, certainly in YAG and likely in natural pyrope as well. The experimental results are better described by invoking O diffusion via two distinct pathways with an inter-site reaction allowing O to move between these pathways. Modeling this process yields two diffusion coefficients (D values) for O, one of which is approximately two orders of magnitude higher than the other. Taken together, Arrhenius relationships are:logDm2s-1=-7.2(±1.3)+(-321(±32)kJmol-12.303RT) for the slow pathway, andlogDm2s-1=-5.4(±0.7)+(-321(±20)kJmol-12.303RT) for the fast pathway. We interpret the two pathways as representing diffusion following vacancy and inter-stitial mechanisms, respectively. Regardless, our new data suggest that the slow mechanism is prevalent in garnet with natural compositions, and thus is likely to control the retentivity of oxygen isotopic signatures in natural samples. The diffusivity of oxygen is similar to Fe-Mn diffusivity in garnet at 1000–1100 °C and Ca diffusivity at 850 °C. However, the activation energy for O diffusion is larger, leading to lower diffusivities at P-T conditions characterizing crustal metamorphism. Therefore, original O isotopic signatures can be retained in garnets showing major element zoning partially re-equilibrated by diffusion, with the uncertainty caveat of extrapolating the experimental data to lower temperature conditions.

Geochemistry & Geophysics↗

DOE OSTI2021

Extending a 10‐node composite tetrahedral finite element for solid mechanics

Abstract We propose to extend the composite tetrahedral finite element first introduced by Thoutireddy et al. (2002) and recently reformulated by Ostien et al. (2016). We generalize the gradient operator and mass matrix to curved domains through analytical expressions weighted by subtetrahedra Jacobians. Optimal integration weights are constructed to increase the accuracy of Gaussian quadrature. We preserve the variational structure of the formulation through a new five‐field functional with additional, independent fields for the Jacobian and the pressure. This approach not only obviates volumetric locking but also yields symmetry. A deleterious soft mode, common to both the quadratic and composite tetrahedral element with constant pressure formulations is effectively stabilized through a novel convex energy penalty function. Numerous numerical examples spanning a patch test to the impact of a Taylor bar demonstrate the accuracy, robustness, and convergence of the extended composite tetrahedral element for application to structural metals.

Foulk III, James W.↗

DOE OSTI2023

Enhanced Iodine Capture Using a Postsynthetically Modified Thione–Silver Zeolitic Imidazole Framework

Efficient management of radionuclides that are released from various processes in the nuclear fuel cycle is of significant importance. Among these nuclides, radioactive iodine (mainly 129 I and 131 I) is a major concern due to the risk it poses to the environment and to human health; thus, the development of materials that can capture and safely store radioactive iodine is crucial. Herein, a novel silver-thione-functionalized zeolitic imidazole framework (ZIF) was synthesized via post-synthetic modification and assessed for its iodine uptake capabilities alongside the parent ZIF-8 and intermediate materials. A solvent-assisted ligand exchange procedure was used to replace the 2-methylimidazole linkers in ZIF-8 with 2-mercaptoimidazole, forming the intermediate compound ZIF-8=S, which was reacted with AgNO 3 to yield the ZIF-8=S-Ag + composite for iodine uptake. Despite possessing the lowest BET surface area of the derivatives, the Ag-functionalized material demonstrated superior I 2 adsorption in terms of both maximum capacity (550 g I 2 /mol) and rapid kinetics (50% loading achieved in 5 hrs, saturation in 50 hrs) compared to our pristine ZIF-8, which reached 450 g I 2 /mol after 150 hours and 50% loading in 25 hours. This improvement is attributed to the presence of the Ag + ions, which provide a strong chemical driving force to form stable Ag-I species. In conclusion, the results of this study contribute to a broader understanding of the strategies that can be employed to engineer adsorbents with robust iodine uptake behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Conversion Kinetics and Ionic Conductivity in Na-β”-Alumina + YSZ (Naβ”AY) Sodium Solid Electrolyte via Vapor Phase Conversion Process

Sodium ion batteries have been receiving increasing attention and may see potential revival in the near future, particularly in large-scale grid energy storage coupling with wind and solar power generation, due to the abundant sodium resources, low cost, and sufficiently high energy density. Among the known sodium ion conductors, the Na-β”-alumina electrolyte remains highly attractive because of its high ionic conductivity. This study focuses on the vapor phase synthesis of a Na-β”-Alumina + YSZ (Naβ”AY) composite sodium electrolyte, which has higher mechanical strength and stability than conventional single phase β”-Alumina. The objectives are the measurement of conversion kinetics through a newly developed weight-gain based model and the determination of sodium ionic conductivity in the composite electrolyte. Starting samples contained ~70 vol% α-Alumina and ~30 vol% YSZ (3 mol% Y 2 O 3 stabilized Zirconia) with and without a thin alumina surface layer made by sintering in air at 1600 °C. The sintered samples were placed in a powder of Na-β”-alumina and heat-treated at 1250 °C for various periods. Sample dimensions and weight were measured as a function of heat treatment time. The conversion of α-Alumina in the α-Alumina + YSZ composite into Naβ”AY occurred by coupled diffusion of sodium ions through Na-β”-alumina and of oxygen ions through YSZ, effectively diffusing Na2O. From the analysis of the time dependence of sample mass and dimensions, the effective diffusion coefficient of Na 2 O through the sample, D eff , was estimated to be 1.74 x 10 -7 cm2 s -1 , and the effective interface transfer parameter, k eff , was estimated as 2.33 x 10 -6 cm s -1 . By depositing a thin alumina coating layer on top of the bulk composite, the chemical diffusion coefficient of oxygen through single phase Na-β”-alumina was estimated as 4.35 x 10 -10 cm 2 s -1 . An AC impedance measurement was performed on a fully converted Naβ”AY composite, and the conductivity of the composite electrolyte was 1.3 x 10 -1 S cm -1 at 300 °C and 1.6 x 10 -3 S cm -1 at 25 °C, indicating promising applications in solid state or molten salt batteries at low to intermediate temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A machine learning framework for elastic constants predictions in multi-principal element alloys

On the one hand, multi-principal element alloys (MPEAs) have created a paradigm shift in alloy design due to large compositional space, whereas on the other, they have presented enormous computational challenges for theory-based materials design, especially density functional theory (DFT), which is inherently computationally expensive even for traditional dilute alloys. In this paper, we present a machine learning framework, namely PREDICT (PRedict properties from Existing Database In Complex alloys Territory), that opens a pathway to predict elastic constants in large compositional space with little computational expense. The framework only relies on the DFT database of binary alloys and predicts Voigt–Reuss–Hill Young’s modulus, shear modulus, bulk modulus, elastic constants, and Poisson’s ratio in MPEAs. We show that the key descriptors of elastic constants are the A–B bond length and cohesive energy. The framework can predict elastic constants in hypothetical compositions as long as the constituent elements are present in the database, thereby enabling property exploration in multi-compositional systems. We illustrate predictions in a FCC Ni-Cu-Au-Pd-Pt system.

Linton, Nathan (ORCID:0000000315485613)↗

DOE OSTI2020

Composite Structured Surfaces for Durable Dropwise Condensation

Dropwise condensation of steam on hydrophobic substrates has a 10X higher heat transfer coefficient compared to filmwise condensation. To promote dropwise condensation, low surface energy hydrophobic coatings (polymers) are typically utilized. The low intrinsic thermal conductivity (k < 1 W/(m · K)) of polymers, coupled with high heat transfer coefficient of dropwise condensation (100 kW/(m 2 · K)), necessitates that the coating be thin (< 1µm) in order to avoid reducing the overall heat exchanger conductance. However, thin polymeric films easily degrade. The two opposing requirements result in the need for optimization between the durability (thick coating) and the heat transfer (thin coating). To enable high thermal conductivity in thicker coatings, we develop metal-polymer structured surfaces. By using porous structures as inter-connected heat-conducting backbones that are filled with hydrophobic materials, we enable tuning of the coating effective thermal conductivity and surface energy. Three metal structures were studied; micro/nanowires, inverse opals, and sintered spheres. Heat transfer performance was calculated using three-dimensional finite element method simulations with two distinct boundary conditions; convection at the walls and isothermal walls. Interestingly, the overall conductance shows up to 40% difference depending on the boundary condition used in calculating the composite coating effective thermal conductivity. We use our model to predict the heat transfer performance as a function of metal fraction by volume and by surface area for condensation. By coupling our thermal simulations with a previously verified analytical model for predicting wetting behavior on heterogeneous surfaces, we propose a regime map to predict dropwise-to-filmwise transition. Furthermore, our work not only forms a starting point for the development of durable dropwise condensing surfaces, it identifies important considerations needed for computing effective thermal conductivity of composites.

42 ENGINEERING↗

DOE OSTI2025

HfTa_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys hafnium-tantalum (Hf-Ta). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Hf and Ta. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect BCC lattice sites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,040 randomized atomic structures over 31 chemical compositions. Further methodological and structural information is contained in the dataset README.txt file.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Decoupling the effects of texture and composition on magnetic properties of Fe-Si sheet processed by shear deformation

Soft magnetic Fe-Si alloys (electrical steels) possess exceptional functional properties such as high permeability, low coercivity, and low core loss, which generally improve with increasing Si content in the alloy. However, Fe-Si alloys containing > 3.5 wt% Si are also characterized by prohibitively low workability and poor ductility that have prevented their efficient commercial production in sheet form by rolling. This has limited their use for improving efficiency of motors and transformers. In this study, hybrid cutting-extrusion (HCE) is used as a single-step thermomechanical processing method to produce continuous Fe-Si alloy sheet with high Si compositions of 4 wt% to 6.5 wt%. HCE sheet is shown to have a homogeneous annealed grain structure and simple-shear crystallographic textures. By controlling the HCE deformation path, varied crystallographic shear textures are created in the sheet. Quasi-static magnetic properties of the HCE sheet are evaluated to decouple the effects of sheet texture and Si composition on resultant permeability and coercivity properties. The results suggest that HCE, with suitable process scaling, is a viable route for production of high-Si content electrical steel sheet for next-generation motors and transformers.

36 MATERIALS SCIENCE↗

DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗

DOE OSTI2025

Structure–Function Relationships in Sequence-Controlled Copolymers for Rare Earth Element Chelation

The ability to tune material function through primary sequence is a defining feature of biological macromolecules, allowing precise control over structure and target interactions in complex aqueous environments. However, translating sequence–structure–function relationships to synthetic macromolecules is challenging due to their dispersity in sequence, conformation, and composition. Here, we report systematic studies of amphiphilic polymer chelators designed to probe how composition and patterning influence binding affinity and selectivity for rare earth elements (REEs), a series of technologically relevant metals with challenging separation profiles. A library of copolymers varying hydrophobic monomer composition and patterning was synthesized via reversible addition–fragmentation chain transfer (RAFT) polymerization, spanning statistical, gradient, and block architectures. REE binding was quantified using a high-throughput colorimetric assay, and reconstruction of polymer ensembles using kinetic stochastic simulations enabled quantitative comparisons of sequence heterogeneity, linking local monomer colocalization to emergent REE binding. Further, we investigated the role of different hydrophobic comonomers in tuning metal coordination, with binding trends linked to structural features that influence binding site desolvation. Complementary dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS) measurements showed that both polymer and monomer architecture modulate metal-induced conformational changes, and that multichain assembly behavior emerges beyond critical hydrophobic thresholds. Sequence control also altered REE selectivity, with nonmonotonic differences observed across compositionally identical polymers with different sequence architectures. Together, these findings establish design principles that connect polymer sequence and structure to binding performance, guiding the design of macromolecular chelators with enhanced affinity and selectivity for applications in separations, sensing, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Dielectric Engineering of ZnO@ZIF‐8 for High‐Performance Triboelectric Nanogenerators and Self‐Powered Humidity Sensors

Porous metal oxide–metal-organic framework (MO x @MOF) hybrids offer synergistic effects that enhance surface charge density, electronic structure, and textural properties, making them ideal for self-powered sensing applications. Here, uniform, and pinhole-free ternary porous ZnO–PTFE@ZIF-8 hybrid films are developed on room-temperature co-sputtered ZnO–polytetrafluoroethylene (PTFE) composite films, where ZnO serves as a self-sacrificial precursor to precisely regulate ZIF-8 (Zn-MeIm 2 ) growth through solvothermal methods. The resulting TENG achieves a high output power density of 0.67 mW cm −2 , attributed to the synergistic effects of fluorine-rich PTFE and methyl-functionalized ZIF-8, which enhance surface charge density and dielectric response. By tuning PTFE content in the ZnO–PTFE composite, the dielectric constant and triboelectric output is optimized. The ZP60@ZIF-8-based device also demonstrates excellent humidity sensing performance, with a wide detection range (20–99% RH) and ultrahigh sensitivity (R V % of 19 900%, R I % of 19 325% at 99% RH). These results position ZP@ZIF-8-based TENGs as promising platforms for next-generation self-powered sensors and smart wearable electronics.

42 ENGINEERING↗