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At least 109 records · Page 6

A pathway to synthesizing single-crystal Fe and FeCr films

Nuclear reactor environments provide a unique scientific and engineering challenge wherein materials must tolerate prolonged exposure to concurrent irradiation, elevated temperatures, and corrosive media. However, uncontrolled variability in material composition and structure often prohibits truly single-variable experiments that can reveal basic aspects of environmental damage. Here, Magnetron sputtering is used to provide a more controlled model system for these fundamental studies, yielding reproducible single-crystal Fe and FeCr thin films containing 8 and 18 at.% Cr. Electron microscopy is used to determine the systematic correlations between growth conditions and the resulting film microstructure and surface morphology. It is found that the substrate temperature and applied radio frequency (RF) bias can be tuned to obtain consistent homogeneous and single crystal films with a minimal amount of Ar impurities from the RF bias process. Epitaxial, single-crystal Fe films are obtained on MgO substrates at 500 °C with 10 Watt (W) RF bias deposition. However, when Cr is alloyed with Fe, higher substrate temperatures (600 °C) and applied RF biases (15 W) are required to achieve a similar epitaxial single-crystal FeCr film. Accelerated molecular dynamics simulations reveal that Cr impedes surface transport, explaining the need for higher temperature and bias during the growth of the Cr-bearing films.

36 MATERIALS SCIENCE↗

Competing Interactions between Mesoscale Length-Scales, Order-Disorder, and Martensitic Transformation in Ferromagnetic Shape Memory Alloys

In the present study, the effects of composition and heat treatments and the resulting microstructural changes on the martensitic transformation and ferromagnetic transition have been investigated in NiCoMnIn metamagnetic shape memory alloys. In this shape memory alloy system, it is observed that upon heat treatments at a wide temperature range, the onset temperature of the martensitic transformation follows a non-monotonic behavior with respect to heat treatment time, and the nature of the non-monotonic behavior is also a function of composition. This behavior cannot be attributed to well-known factors such as precipitation, change in local composition due to the precipitation and/or global degree of order. In this work, a systematic investigation through synthesis, thermal processing and characterization via thermo-physical measurements, transmission electron microscopy and in-situ synchrotron x-ray diffraction experiments has been used to correlate the non-monotonic dependence of the martensitic transformation and ferromagnetic transition temperatures to the evolution of L2 1 domains arising from a order/disorder phase transition. A thermodynamic model for the magneto-structural transition is combined with classical nucleation theory to further ascertain the role of microstructural length-scales on the onset of the martensitic transformation. This work thus provides understanding of the thermodynamic and kinetic factors that can be controlled to tune the coupled magneto-structural transformations in NiCoMnIn metamagnetic shape memory alloys.

36 MATERIALS SCIENCE↗

Tuning the spontaneous exchange bias effect in La 1.5 Sr 0.5 CoMnO 6 with sintering temperature

Here, in this study, we present a study of the influence of microstructure on the magnetic properties of polycrystalline samples of the La 1.5 Sr 0.5 CoMnO 6 double perovskite, with primary attention to the spontaneous exchange bias effect, a fascinating recently discovered phenomena for which some materials exhibit unidirectional magnetic anisotropy after being cooled in zero magnetic fields. By sintering La 1.5 Sr 0.5 CoMnO 6 at different temperatures, we obtained samples with distinct average grain sizes, ranging from 1.54-6.65 μm. A detailed investigation of the material's structural, morphologic, electronic, and magnetic properties using x-ray powder diffraction, powder neutron diffraction, x-ray absorption near edge structure spectroscopy, scanning electron microscopy, and ac and dc magnetometry has revealed a systematic enhancement of the exchange bias effect with increasing the average grain size. This evolution is discussed in terms of changes in the material's porosity and grain morphology and its influence on the exchange couplings at the magnetic interfaces.

14 SOLAR ENERGY↗

Material processing, microstructure, and composite properties of low carbon Engineered Cementitious Composites (ECC)

Traditional PVA fiber-reinforced Engineered Cementitious Composites (ECC) show high tensile ductility and superior durability with tight crack width, but the high cost and embodied carbon can hinder its wider application in infrastructures. The objective of this study is to develop a better understanding of the fresh and hardened properties of an ECC that employs a lower embodied-carbon binder, Limestone Calcined Clay Cement (LC3), and lower-cost PP fiber that is widely available. Specifically, the interrelations between material processing, microstructure, and composite properties were studied experimentally. The results showed that ECC with high tensile ductility up to 9% tensile strain and tight crack width with 50 μm at 2% tensile strain can be achieved. It was found that a matrix paste with higher viscosity generally enhanced fiber dispersion uniformity and robustness in tensile strain-hardening. The paste viscosity is increased when OPC is replaced by LC3 and can be tuned with superplasticizer content. Larger maximum flaw size leads to lower first crack strength, beneficial for microcrack initiation and multiple cracking. This study generates fundamental knowledge linking processing-microstructure-performance of PP-LC3-ECC. This class of low embodied carbon ECC with tight crack width is expected to contribute to reducing the carbon footprint of the built environment.

36 MATERIALS SCIENCE↗

Evolution of carbide precipitates in Haynes® 282 superalloy processed by wire arc additive manufacturing

Precipitation hardening regulated with heat treatments is a critical technique for tuning the mechanical properties of Ni-based superalloys fabricated with additive manufacturing, where mechanical deformation is no longer viable for microstructural refinement. As one of the key precipitates, carbides prevail in the additively manufactured alloys, whose precipitation kinetics remain largely vague. This work studies the influence of heat treatments on the evolution of MC- and M 23 C 6 -type carbides within a Haynes® 282 superalloy prepared by wire arc additive manufacturing (WAAM). SEM-EDS analysis was performed to identify the evolution pathways of the carbides, and TEM and XRD characterizations were carried out to track the crystallographic features. The MC-type carbides are originally present in the as-printed alloy, which distribute uniformly across the whole material and remain largely unchanged in size during the heat treatments. By contrast, the incipiently non-existent M 23 C 6 -type carbides precipitate during an aging treatment at 1010 °C, which majorly extend along the grain boundaries as kinetically feasible sites. Further experimental and computational analysis confirms the enhancing effect of the M 23 C 6 -type carbides on the Vickers hardness. For the first time, this work revealed the evolution pathways of carbides within a Haynes® 282 superalloy prepared by WAAM, providing critical information for tunning the microstructure and mechanical properties. Finally, the carbide evolution kinetics established in this work can be potentially extended to other alloys prepared with WAAM, providing critical information to prevent mechanical failures associated with carbide coarsening.

36 MATERIALS SCIENCE↗

Stable, Ductile and Strong Ultrafine HT-9 Steels via Large Strain Machining

Beyond the current commercial materials, refining the grain size is among the proposed strategies to manufacture resilient materials for industrial applications demanding high resistance to severe environments. Here, large strain machining (LSM) was used to manufacture nanostructured HT-9 steel with enhanced thermal stability, mechanical properties, and ductility. Nanocrystalline HT-9 steels with different aspect rations are achieved. In-situ transmission electron microscopy annealing experiments demonstrated that the nanocrystalline grains have excellent thermal stability up to 700 °C with no additional elemental segregation on the grain boundaries other than the initial carbides, attributing the thermal stability of the LSM materials to the low dislocation densities and strains in the final microstructure. Nano-indentation and micro-tensile testing performed on the LSM material pre- and post-annealing demonstrated the possibility of tuning the material’s strength and ductility. The results expound on the possibility of manufacturing controlled nanocrystalline materials via a scalable and cost-effective method, albeit with additional fundamental understanding of the resultant morphology dependence on the LSM conditions.

36 MATERIALS SCIENCE↗

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Text Mining for Process–Structure–Properties Relationships in Metals

With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery—although significant challenges remain. While LLMs offer promising few- and zero-shot learning capabilities, particularly valuable in the materials domain where expert annotations are scarce, general-purpose LLMs often fail to address key materials-specific queries without further adaptation. To bridge this gap, fine-tuning LLMs on human-labeled data is essential for effective structured knowledge extraction (Liu in The Importance of Human-Labeled Data in the Era of LLMs, 2023). Here, in this study, we introduce a novel annotation schema designed to extract generic process–structure–properties relationships from scientific literature. We demonstrate the utility of this approach using a dataset of 128 abstracts, with annotations drawn from two distinct domains: high-temperature materials (Domain I) and uncertainty quantification in simulating materials microstructure (Domain II). Initially, we developed a conditional random field (CRF) model based on MatBERT—a domain-specific BERT variant—and evaluated its performance on Domain I. Subsequently, we compared this model with a fine-tuned LLM (GPT-4o from OpenAI) under identical conditions. Our results indicate that fine-tuning LLMs can significantly improve entity extraction performance over the BERT-CRF baseline on Domain I. However, when additional examples from Domain II were incorporated, the performance of the BERT-CRF model became comparable to that of the GPT-4o model. These findings underscore the potential of our schema for structured knowledge extraction and highlight the complementary strengths of both modeling approaches.

Materials science↗

Phase diagrams and microstructures of aqueous short alkyl chain polyethylene glycol ether carboxylate and carboxylic acid triblock surfactant solutions

The surfactant C 8 Eo 8 CH 2 COOH (Akypo LF2) and its salts have a small hydrophobic and a significantly longer hydrophilic part. As a consequence, there must be a significant steric constraint, once these surfactant molecules form micelles. In addition, the partially charged headgroups should bring some additional fine-tuning via electrostatic interactions to this "essentially non-ionic" surfactant. Experiments: Phase diagrams of binary mixtures of water and C 8 Eo 8 CH 2 COOH are established over large concentration and temperature ranges, also at different pHs and in the presence of sodium and calcium ions. Surface tensions and osmotic pressures are measured to understand the systems. To evaluate the microstructures, also Dynamic Light Scattering and Small-Angle X-ray Scattering are performed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Phase-Field Model for In-Space Manufacturing of Binary Alloys

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

36 MATERIALS SCIENCE↗

Automated identification of deformation twin systems in Mg WE43 from SEM DIC

In this study, the application of machine learning and computer vision approaches to microscale deformation data for the automated identification of deformation twinning systems, and their associated twin area, is introduced. Deformation data was obtained during in-situ SEM compression testing of a WE43 Mg alloy using digital image correlation (DIC) modified for use with electron microscopy. A 5.7 mm × 3.4 mm area of interest was analyzed, generating ~100 million data points of deformation. Experimental twin trace directions were determined by applying k-means clustering, morphological thinning, and Hough transforms to the deformation data. The identification of deformation twinning was achieved by consideration of the twin trace direction, its strain value, and its evolution. The deformation map was divided into areas corresponding to individual active twin systems, enabling the analysis of microstructure dependence of deformation behavior and twinning activity. The performance of the proposed twinning identification approach was evaluated by accuracy, precision, and sensitivity metrics. The effect of the tuning parameters used in the algorithm on the performance is also discussed.

36 MATERIALS SCIENCE↗

Enhancing perovskite electrocatalysis through synergistic functionalization of B-site cation for efficient water splitting

The family of perovskite oxides is a promising class of catalysts for diverse energy conversion processes including water splitting. In this work, a facile two-step manipulation (in-situ exsolution and post-sulfurization) strategy was proposed and applied to LaCo 0.2 Fe 0.8 O 3 (LCF) perovskite parent, through which, the electronic state, spatial immersion and intrinsic activity of B-site cobalt (Co) were stepwise tuned at nanoscale proximity accordingly (i.e., lattice Co ions segregated Co 0 → embedded CoS 2 ). Impressively, the as-prepared catalyst (S-LCF) obtains an emergent oxygen deficient microstructure seamlessly pinned with uniformly distributed CoS 2 nanoparticles (NPs), which demonstrates enhanced performance toward both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), and shows good stability in overall water splitting. The density functional theory (DFT) calculations illustrate the optimized metal-oxygen covalency and hydrogen adsorption Gibbs free energy (Δ G H *) on S-LCF, which further buttresses the prominence of our B-site cation engineering tactics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel method to control explosive shock sensitivity: Formulations, experiments and modeling

The microstructure of a heterogeneous high explosive (HE) affects its shock initiation sensitivity and detonation performance. Alteration of the void content and/or void structure (i.e., bulk heating or mechanical damage) therefore changes the shock initiation behavior. Controlling and predicting the change in shock sensitivity after an HE has undergone microstructural changes addresses an important and challenging goal for the design and understanding of novel energetic material formulations. In this study, we aimed to develop HE systems to precisely tune shock sensitivity by a thermal treatment prior to use. Specifically, we incorporated a small fraction (1 wt% or less) of thermally expandable microspheres (TEMs) during the formulation process of various plastic-bonded explosives (PBX). TEMs typically consist of a thermoplastic acrylonitrile shell (10-50 µm diameter), which encapsulates an inert low boiling hydrocarbon. Upon heating, the TEMs expand as the shell softens while the hydrocarbon gasifies, increasing the internal pressure and expanding the particle by as much as 120 vol% (irreversibly). Here, we present our progress on shock sensitivity comparisons of HE formulations doped with TEMs after heating and expansion. Experiments, using Composition C-4 thermally cycled to 120°C, showed an increase in shock sensitivity. Additionally, mesoscale modeling revealed that the TEM itself does not act as a hotspot, but instead has a secondary effect on the response of nearby voids. We conclude that TEMs indeed do provide a method to tune shock sensitivity. Further, our results emphasize the non-uniformity of shock waves at the mesoscale, and that upstream defects influence the reactivity of downstream defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

F4‐TCNQ as an Additive to Impart Stretchable Semiconductors with High Mobility and Stability

Abstract Numerous strategies are developed to impart stretchability to polymer semiconductors. Although these methods improve the ductility, mobility, and stability of such stretchable semiconductors, they nonetheless still need further improvement. Here, it is shown that 2,3,5,6‐tetrafluoro‐7,7,8,8‐tetracyanoquinodimethane (F4‐TCNQ) is an effective molecular additive to tune the properties of a diketopyrrolopyrrole‐based (DPP‐based) semiconductor. Specifically, the addition of F4‐TCNQ is observed to improve the ductility of the semiconductor by altering the polymer’s microstructures and dynamic motions. As a p‐type dopant additive, F4‐TCNQ can also effectively enhance the mobility and stability of the semiconductor through changing the host polymer’s packing structures and charge trap passivation. Upon fabricating fully stretchable transistors with F4‐TCNQ‐DPP blended semiconductor films, it is observed that the resulting stretchable transistors possess one of the highest initial mobility of 1.03 cm 2 V −1 s −1 . The fabricated transistors also exhibit higher stability (both bias and environmental) and mobility retention under repeated strain, compared to those without F4‐TCNQ additive. These findings offer a new direction of research on stretchable semiconductors to facilitate future practical applications.

Mun, Jaewan↗

Combinatorial Synthesis and High-Throughput Characterization of Microstructure and Phase Transformation in Ni–Ti–Cu–V Quaternary Thin-Film Library

Ni–Ti–based shape memory alloys (SMAs) have found widespread use in the last 70 years, but improving their functional stability remains a key quest for more robust and advanced applications. Named for their ability to retain their processed shape as a result of a reversible martensitic transformation, SMAs are highly sensitive to compositional variations. Alloying with ternary and quaternary elements to fine-tune the lattice parameters and the thermal hysteresis of an SMA, therefore, becomes a challenge in materials exploration. Combinatorial materials science allows streamlining of the synthesis process and data management from multiple characterization techniques. In this study, a composition spread of Ni–Ti–Cu–V thin-film library was synthesized by magnetron co-sputtering on a thermally oxidized Si wafer. Composition-dependent phase transformation temperature and microstructure were investigated and determined using high-throughput wavelength dispersive spectroscopy, synchrotron X-ray diffraction, and temperature-dependent resistance measurements. Of the 177 compositions in the materials library, 32 were observed to have shape memory effect, of which five had zero or near-zero thermal hysteresis. These compositions provide flexibility in the operating temperature regimes that they can be used in. A phase map for the quaternary system and correlations of functional properties are discussed with respect to the local microstructure and composition of the thin-film library.

42 ENGINEERING↗

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗

In Situ Wood Delignification toward Sustainable Applications

As one of the most abundant and versatile natural materials on Earth, recently wood has attracted tremendous attention from scientists and engineers due to its outstanding advantages, including hierarchically porous microstructure, high mechanical strength, environmental friendliness, renewability, and biodegradability. Wood’s hierarchically porous structure and chemical components (e.g., cellulose, hemicelluloses, and lignin) enable its mechanical, ionic, optical, and thermal properties to be tuned via physical, chemical, and/or thermal modifications. Among these various approaches, the chemical delignification of bulk wood is the most fascinating, in which the majority of lignin and hemicelluloses is removed while leaving the cellulose intact, maintaining wood’s physical integrity and hierarchical structure. This delignified structure is unique, composed of hollow, aligned channels made up of cellulose microfibrils, and particularly attractive given its origin from a sustainable and renewable resource. As a result, delignified wood has attracted increasing attention for applications that go far beyond traditional wood utilization, such as lightweight yet strong structural materials, energy storage and conversion, environmental remediation, flexible electronics, and bioengineering. Here, we review recent developments in bulk wood delignification strategies toward the achievement of such advanced wood technologies for sustainable applications, with a focus on the research in our group. Similar to chemical pulping and bleaching, wood delignification involves a series of nucleophilic reactions based on alkaline Na 2 SO 3 or Na 2 S systems (i.e., chemical pulping) or electrophilic, radical, and oxidation reactions based on H 2 O 2 , ClO 2 , or NaClO systems (i.e., chemical bleaching) to deconstruct, fragment, and promote the hydrophilicity of lignin macromolecules, which finally make lignin easier to be removed. We discuss the structure and properties of partially and near-completely delignified wood, with a focus on process-structure–property relationships. The resulting delignified wood materials, with tunable structure and properties, demonstrate various advanced functions, in a wide range of advanced applications, such as building and construction, green energy, and electronics. Finally, the potential challenges and appealing perspectives of in situ wood delignification are discussed. In situ wood delignification, as a powerful modification strategy, has speeded up the development of advanced wood technologies and wood-based functional materials and products.

36 MATERIALS SCIENCE↗