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683 records · Page 16

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization

Hydrogen Production and Li-Ion Battery Performance with MoS2-SiNWs-SWNTs@ZnONPs Nanocomposites

This study explores the hydrogen generation potential via water-splitting reactions under UV-vis radiation by using a synergistic assembly of ZnO nanoparticles integrated with MoS2, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS2-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS2 synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS2 exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m2 g−1. Notably, the hydrogen production rate achieved by a composite comprising 5% MoS2, 1.7% SiNWs, and 13.3% SWNTs at an 80% ZnONPs base was approximately 3909 µmol h−1g−1 under 500 nm wavelength radiation, marking a significant improvement of over 40-fold relative to pristine ZnONPs. This enhancement underscores the remarkable photocatalytic efficiency of the composites, maintaining high hydrogen production rates above 1500 µmol h−1g−1 even under radiation wavelengths exceeding 600 nm. Furthermore, the potential of these composites for energy storage and conversion applications, specifically within rechargeable lithium-ion batteries, was investigated. Composites, similar to those utilized for hydrogen production but excluding ZnONPs to address its limited theoretical capacity and electrical conductivity, were developed. The focus was on utilizing MoS2, SiNWs, and SWNTs as anode materials for Li-ion batteries. This strategic combination significantly improved the electronic conductivity and mechanical stability of the composite. Specifically, the composite with 56% MoS2, 24% SiNWs, and 20% SWNTs offered remarkable cyclic performance with high specific capacity values, achieving a complete stability of 1000 mA h g−1 after 100 cycles at 1 A g−1. These results illuminate the dual utility of the composites, not only as innovative catalysts for hydrogen production but also as advanced materials for energy storage technologies, showcasing their potential in contributing to sustainable energy solutions.

Chemistry

Beyond Melting: Amorphous Bonding for Joining and Consolidation

Crystallization may be the hidden constraint in thermoplastic composite manufacturing. It requires tightly controlled cooling, induces residual stresses through shrinkage, and introduces path-dependent behavior that complicates predictive modeling yet remains essential for structural performance. This work asks: can bonding be achieved without relying on melt-driven crystallization? To address this, thin (5–20 μm) polyetherimide (PEI) interlayers are pre-healed to slow-cooled polyaryletherketone (PAEK) in two contexts. The first, Thermabond®, is sub-melt joining of low melt-PAEK laminates. Results show that bond quality is governed primarily by processing (i.e., adequate healing and film handling) rather than modest changes in interlayer thickness. This concept is then extended to laminate-scale manufacturing through an architecture known as OATMEAL (Out-of-autoclave Amorphous/semicrystalline Thermoplastic Material for Energy-efficient Aerospace-grade Laminates). PEI is healed to carbon fiber reinforced polyetheretherketone (PEEK) at the prepreg and excess PEI is then ablated from the surface. Crystallinity is developed off-line during prepreg fabrication, while subsequent consolidation occurs below the melt temperature to preserve it. Cross-ply warpage experiments show that, contrary to intuition, repeated amorphous interfaces reduce global curvature by lowering the effective stress lock-in temperature and eliminating crystallization shrinkage from the lamina response. Correspondingly, laminate behavior is accurately predicted using classical laminate theory (CLT) with a single effective stress-free temperature, whereas conventional CF/PEEK requires accounting for crystallization-driven effects. By decoupling interfacial healing from crystallization, OATMEAL enables sub-melt consolidation, reduces energy consumption by up to 75%, and increases manufacturing throughput by fivefold. These results demonstrate that amorphous bonding is not only a joining strategy, but a pathway to more predictable and scalable thermoplastic composite manufacturing.

solidification

Phase stability in the Hf-N and Zr-N systems

Hf and Zr nitrides are promising compounds for many technologically important areas, including high-temperature structural applications, quantum computing, and solar and optical applications. Here, this article reports on a comprehensive first-principles statistical mechanics study of phase stability in the Hf-N and Zr-N binary systems. A high solubility of nitrogen in the hcp forms of Hf and Zr is predicted. The rocksalt forms of HfN and ZrN can also tolerate a high degree of off-stoichiometry through the introduction of nitrogen and metal vacancies. The Hf-N binary favors a family of stacking faulted parent crystal structures at intermediate nitrogen concentrations that host a unique form of short-range order among nitrogen interstitials and vacancies. These phases can accommodate some degree of configurational entropy and remain ordered to temperatures as high as 1200 K.

Monte Carlo methods

Erosion Results of the MISSE 9-15 Polymers and Composites Experiment 1-4 (PCE 1-4)

Polymers and other oxidizable materials on the exterior of spacecraft in the low Earth orbit (LEO) space environment can be eroded from reaction with atomic oxygen (AO). Therefore, in order to design durable spacecraft it is important to know the extent of erosion that will occur during a mission. This can be determined by knowing the LEO AO erosion yield, E y (volume loss per incident oxygen atom), of materials susceptible to AO reaction. In addition, recent flight experiments have shown that the AO E y can vary with the AO fluence and/or solar exposure. Therefore, obtaining AO E y data for materials flown on various spaceflight missions is important. NASA Glenn Research Center has flown numerous experiments as part of the Materials International Space Station Experiment (MISSE) missions on the exterior of the International Space Station (ISS) to characterize the LEO E y of polymers, composites, protective coatings, and other spacecraft materials. Recently, four Glenn experiments with 365 flight (F) samples were flown on ISS’s MISSE-Flight Facility (MISSE-FF). These experiments are the Polymers and Composites Experiment-1 (PCE-1) flown as part of the MISSE-9 mission, the PCE-2 flown as part of the MISSE-10 mission, the PCE-3 flown as part of the MISSE-12 and MISSE-15 missions, and the PCE-4 flown as part of the MISSE-13 mission. Although each experiment had numerous sample objectives, the primary objective was to determine the LEO AO E y of various spacecraft materials as a function of solar irradiation and AO fluence. This paper provides a summary of the erosion data for the PCE 1-4 AO E y samples. The AO E y for 150 samples flown in either the LEO ram, wake, zenith or nadir directions are provided. The AO ram fluence varied from 2.97×10 20 atoms/cm 2 after 0.89 years of direct space exposure (with relatively high levels of Si contamination) on MISSE 12 to 3.93×10 20 atoms/cm 2 after 1.17 years of direct space exposure on MISSE-10. The ram AO E y values for uncoated polymers range from 3.81×10 –25 cm 3 /atom for polytetrafluoroethylene (M9R-C20 F) exposed to an AO fluence of 3.44×10 20 atoms/cm 2 on MISSE-9 to 4.43×10 –23 cm 3 /atom for AO etched low density polyimide aerogel (M12R-C21 F) exposed to an AO fluence of 2.97×10 21 atoms/cm 2 on MISSE-12. Because of the low AO fluence and relatively high Si contamination, a number of PCE-3 wake samples experienced mass gain. Thus, AO E y values are not provided for these samples. Although there are calculated AO E y values for the zenith, wake and nadir samples, the ram AO E y for a particular material is a more reliable value in terms of AO exposure because the zenith, wake and nadir directions were exposed to either no or very little AO fluence and thus other space environmental factors (i.e. vacuum, thermal extremes and thermal cycling, and/or various types of radiation) are responsible for the mass loss.

Erosion yield

Interwoven magnetic kagome metal overcomes geometric frustration

Magnetic kagome materials provide a platform for exploring magneto-transport phenomena, symmetry breaking and charge ordering driven by the intricate interplay among electronic structure, topology and magnetism. Yet geometric frustration in conventional kagome magnets limits their tunability. Here we propose a design strategy for interweaving quasi-one-dimensional magnetic Tb zigzag chains with non-magnetic Ti-based kagome bilayers in TbTi 3 Bi 4 . Comprehensive spectroscopic analyses reveal coexisting elliptical-spiral magnetic and spin-density-wave orders accompanied by a large ~90 meV band-folding gap. The combined magnetic and electronic state leads to a giant anomalous Hall conductivity of 10 5 Ω −1 cm −1 , which exceeds that observed in frustrated kagome analogues. These results establish TbTi 3 Bi 4 as a model system of magnetic kagome metals with strong electron–magnetism interactions and underscore the necessity of interweaving designed magnetic and charge layers separately to achieve tunable transport properties. This design strategy will enable the discovery of emergent quantum states and next-generation electronic materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Deriving the Landauer Principle From the Quantum Shannon Entropy

We derive an expression to determine the equilibrium probability distribution of a quantum state in contact with a noisy thermal environment that formally separates contributions from quantum and classical forms of probabilistic uncertainty. A statistical mechanical interpretation of this probability distribution enables us to derive an expression for the minimum free energy costs for arbitrary (reversible or irreversible) quantum state changes. In conclusion, based on this derivation, we demonstrate that–in contrast to classical systems–the free energy required to erase or reset a qubit depends sensitively on both the fidelity of the target state and on the physical properties of the environment, such as the number of quantum bath states, due primarily to the entropic effects of system-bath entanglement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Recyclable Materials for Resource Constrained Environments

In-space manufacturing exhibits severe limitations in resources as astronauts are only afforded with the materials that are brought on-board the space craft. Consequently, the use of recyclable and re-usable materials is paramount. Researchers at NLR leverage their expertise in polymer and recycling chemistry to develop material systems capable of high performance applications with intentional consideration on multi-life use through chemical recycling, mechanical recycling, bio-degradation, and thermoforming. Disclosed within this poster presentation are highlighted projects that illustrate several recyclable by design material systems that have been developed.

09 BIOMASS FUELS

Probing the fatigue enhancement in a thermally aged cast duplex stainless steel by in situ neutron diffraction

After long-term thermal aging at 400 °C for 3000 h and 10,000 h, a cast duplex stainless steel exhibits promoted fatigue performance, including enhanced three-stage cyclic hardening and prolonged fatigue life. Utilizing in situ neutron diffraction, the phase-specific stresses are resolved, and their evolutions over entire fatigue cycling reveal the underlying mechanisms of the fatigue enhancement. It is found that the ferrite phase bears a much higher stress than the austenite matrix under both as-received and aged conditions. The enhanced cyclic hardening in Stage I is attributed to the strengthening of both phases due to thermal aging, while the enhancement in Stage III results from the martensitic transformation induced strengthening. The fatigue life is prolonged thanks to the cyclic hardening and the delay of martensitic transformation in the austenite phase after thermal aging.

Yu, Dunji [ORNL] (ORCID:0000000189467851)

Thermal Cycling and Isothermal Deformation Response of Polycrystalline NiTi: Simulations vs. Experiment

A recent microstructure-based FEM model that couples crystal-based plasticity, the B2<-> MB190 phase transformation and anisotropic elasticity at the grain scale is calibrated to recent data for polycrystalline NiTi (49.9 at.% Ni). Inputs include anisotropic elastic properties, texture and differential scanning calorimetry data, as well as a subset of recent isothermal deformation and load-biased thermal cycling data. The model is assessed against additional experimental data. Several experimental trends are captured - in particular, the transformation strain during thermal cycling monotonically increases and reaches a peak with increasing bias stress. This is achieved, in part, by modifying the martensite hardening matrix proposed by Patoor et al. [Patoor E, Eberhardt A, Berveiller M. J Phys IV 1996;6:277]. Some experimental trends are underestimated - in particular, the ratcheting of macrostrain during thermal cycling. This may reflect a model limitation that transformation-plasticity coupling is captured on a coarse (grain) scale but not on a fine (martensitic plate) scale.

Phase Transformations

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials

A Case Study of View-Factor Rectification Procedures for Diffuse-Gray Radiation Enclosure Computations

The view factors which are used in diffuse-gray radiation enclosure calculations are often computed by approximate numerical integrations. These approximately calculated view factors will usually not satisfy the important physical constraints of reciprocity and closure. In this paper several view-factor rectification algorithms are reviewed and a rectification algorithm based on a least-squares numerical filtering scheme is proposed with both weighted and unweighted classes. A Monte-Carlo investigation is undertaken to study the propagation of view-factor and surface-area uncertainties into the heat transfer results of the diffuse-gray enclosure calculations. It is found that the weighted least-squares algorithm is vastly superior to the other rectification schemes for the reduction of the heat-flux sensitivities to view-factor uncertainties. In a sample problem, which has proven to be very sensitive to uncertainties in view factor, the heat transfer calculations with weighted least-squares rectified view factors are very good with an original view-factor matrix computed to only one-digit accuracy. All of the algorithms had roughly equivalent effects on the reduction in sensitivity to area uncertainty in this case study.

Robert P Taylor

Triggerable adhesives with infinite working life for large area application

Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF) entered a User Proposal with Perseus Materials in Knoxville, TN. By reinventing how composites are made, we unlock a new era of structural materials: faster to produce, easier to assemble, and strong enough for real-world scale. Perseus Materials was targeting the wind turbine industry to make large adhesive joints for composite turbine blades without the limitations of cure time and room temperature cure without the needs to have work times. The triggerable aspect would increase manufacturing rates for composite wind turbine blades.

36 MATERIALS SCIENCE

Flame retardant biogenic building insulation materials from hemp fiber

Biogenic thermal insulation materials are in high demand because of its carbon-sequestration nature. However, high flammability, moisture condensation, and relatively high thermal conductivity of biogenic material are major concerns for sustainable building applications. In this study, we report the fire-retardant cellulose xerogel insulation nanocomposites derived from hemp fiber recycling and silica xerogel, in which the boric acid treatment improves its fire retardancy. The as-prepared materials show a low thermal conductivity of 31.3 mW/m K, high flexural modulus of 665 MPa, hydrophobicity with the water contact angle of 115°, and fire retardancy with 30% weight loss over a period of burning time 10 min. Overall, this work provides an effective method for the synthesis of fire-retardant biogenic thermal insulation materials and shows a promising way for next-generation bio-based insulation materials.

36 MATERIALS SCIENCE

Cooperative and bifunctional Ga-Ca-Cr 2 O 3 @CaO structured monoliths as versatile platform for reactive capture of CO 2 and its subsequent conversion to ethylene

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO 2 to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr 2 O 3 metal oxides as the catalyst for the reactive capture of CO 2 and its subsequent conversion to C 2 H 4 via the oxidative dehydrogenation of C 2 H 6 (CO 2 -ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C 2 H 4 selectivity. In these formulations, Ga ions stabilize the oxygen lattice of the BFM, while Ca ions interact strongly with Cr to form CaCrO 4 , thereby altering the oxygen species and enhancing the material’s basic properties. Under adsorption–reaction conditions at 600–650 °C, the optimal BFM achieved an excellent C 2 H 4 selectivity of 96.4 %, attributed to a balanced redox process and improved basicity that facilitate efficient C 2 H 6 conversion and rapid desorption of C 2 H 4 without excessive oxidation. Overall, this work provides new insights into the formulation of BFMs monoliths and highlights the critical role of catalytic surface modification in enhancing C 2 H 4 selectivity in the CO 2 -ODHE reactive capture process.

C2H4 production

Li Stripping Behavior of Anode‐Free Solid‐State Batteries Under Intermittent‐Current Discharge Conditions

Anode‐free manufacturing holds promise to enable high energy densities and lower Lithium (Li)‐metal solid‐state batteries (LMSSBs). Nevertheless, in contrast to thick Li foil (>50 µm), the stripping capacity of in situ‐formed Li (10–30 µm) is limited due to diminished creep flow, resulting in reduced accessible capacity. This study explores the correlation between stripping capacity and surface roughness of garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte. The results reveal that stripping capacity can be enhanced through the surface modification of solid electrolytes. Additionally, this study scrutinizes the stripping behavior of in situ Li under intermittent‐current discharge conditions, which are more relevant to the operational conditions of electric vehicles (EVs). It is demonstrated that, when compared to constant‐current stripping, intermittent‐current stripping effectively suppresses void formation and enhances the stripping capacity of in situ Li by 40%. It is considered that the intermittent current inhibits the accumulation of Li vacancies, thereby delaying the void formation. These findings provide valuable insights into the development of high‐performance anode‐free LMSSBs for EVs.

25 ENERGY STORAGE

Analysis of Liquids Using the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER)

We developed a sensor called the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER) probe, which uses an atmospheric pressure glow discharge below the surface of liquids to excite species in the liquid. Through emission spectroscopy of molten salts, liquid metals, and heavy water, we demonstrated the SPIDER probe’s high resolution, accuracy, and versatility. We successfully identified trace concentrations of transition and rare-earth metals in molten salts and detected the isotopic shift of the H β → D β emission line. Our analysis revealed unconventional spectral alkali line shapes, indicating two competing excitation modes: film explosion and droplet vaporization. The film explosion mode, characterized by dense plasma, exhibited self-reversal and broadband continuum emission, while the droplet vaporization mode, associated with diffusive plasma, produced narrow-line emissions. Furthermore, by analyzing circuit transients alongside individual plasma events, we observed that film explosions generate higher currents, likely due to a shorter plasma length as the current preferentially flows through the thin liquid layer. Altogether, our results highlight the SPIDER probe’s efficacy and flexibility, making it well-suited for online material quantification of liquids in extreme environments.

AES

Crystal Growth Scale-Up and Stability of RbSr 2 X 5 :Eu Scintillators

The discovery and development of new scintillation materials support national security needs. In these applications, large volumes of scintillator crystals are needed to achieve efficient screening for contraband. Therefore, one important step in the discovery of new scintillator compositions is testing their feasibility for scale-up and their stability. In this work, high-quality Ø22 mm crystals of two new scintillators RbSr 2 Br 5 :Eu and RbSr 2 I 5 :Eu were grown via the Vertical Bridgman method, and their scintillation properties were characterized. Here, the Ø22 mm RbSr 2 I 5 :Eu crystals could be grown with fast translation rates up to 3.5 mm/h. Both RbSr 2 Br 5 :Eu and RbSr 2 I 5 :Eu had high scintillation performance, including light yields of 46,000 and 61,000 ph/MeV, respectively, for Ø22 × 35 mm crystals. Additionally, properties related to physical stability were investigated, including the coefficients of thermal expansion via high-temperature X-ray diffraction (HTXRD) as well as moisture sensitivity. HTXRD confirmed the absence of solid–solid phase transitions and showed that RbSr 2 Br 5 had minimal thermal expansion anisotropy compared to RbSr 2 I 5 and some other inorganic metal halide scintillators, which favors the growth of large-sized crystals.

36 MATERIALS SCIENCE