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At least 91 records · Page 5

Tailoring the nanotwin spacing of Ni-Mo-W alloys via composition and substrate temperature control

Alloy chemistry and deposition conditions can strongly influence the structure and properties of nanostructured materials. However, in Ni-Mo-W alloys, the limited influence of deposition rate on the twin spacing compels the exploration of other routes to tailor the structure and properties. This study was undertaken to investigate the effect of composition and substrate temperature on the nanotwin spacing of sputter-deposited Ni-Mo-W alloys. Increasing the Ni content from 84 at.% to 93 at.% doubled the average twin spacing from 1.8 nm to 3.8 nm, while raising the substrate temperature from room temperature to 200°C for a fixed Ni content of 91 at.% resulted in an increase from 2.9 nm to 5.0 nm. Concurrent weakening of the {111} texture occurred with both increased Ni and temperature. Furthermore, the combined effectiveness of composition and temperature demonstrated here provides a potential process window for tuning the twin spacing while maintaining the strongly textured columnar structure.

36 MATERIALS SCIENCE↗

Tailoring coherent beam combined laser pulse trains for high peak and average power applications

Laser systems based on coherent beam combination (CBC) that rely on tiled pupil architecture intrinsically carry digital capabilities independently applicable to all three essential characteristics of a laser pulse: amplitude, phase and polarization. Those capabilities allow the far-field energy distribution to be flexibly tailored in real time. Operation in the femtosecond regime at high repetition rates gives access to a wide range of applications requiring both high peak and average powers. We address the task of independent peak versus average power adjustment needed for applications seeking to decouple nonlinear phenomena associated with GW peak power from the thermal load inherent to kW average power operation. The technical solutions proposed are presented in the framework of the Ecole Polytechnique XCAN CBC laser platform (61 independent channels) with an emphasis on thermal management measures implemented to ensure its nominal operation.

47 OTHER INSTRUMENTATION↗

Tailoring Interfaces in Solid-State Batteries Using Interfacial Thermochemistry and Band Alignment

Solid-state lithium ion batteries have enhanced thermal stability compared to batteries using liquid electrolytes. Although their practical implementation is limited by undesired side reactions between the electrode and electrolyte, different modification strategies have been proposed to stabilize these reactive interfaces. These approaches have been primarily based upon bulk materials properties, however, which may not necessarily be representative of the chemistry at the solid/solid interface. In this work, first principles calculations and X-ray scattering experiments are used to elucidate molecular-level reactivity and develop design principles for tailored interfaces based on surface and interfacial properties. Because of its well-known instability, the interface between the Li metal anode and the lithium lanthanum titanate (LLTO) solid electrolyte is applied as a model system. Density functional theory calculations are used to describe bulk, surface, and interfacial thermochemistry of the Li/LLTO system, and interfacial reconstruction is probed using ab initio molecular dynamics. These simulations of the Li/LLTO interface demonstrate facile decomposition concomitant with reduction of Ti 4+ ions. Based on further insights from computational analysis of the surface band edge positions, La 2 O 3 is proposed as an interlayer coating and is shown to provide an energetic barrier for interfacial charge transfer and decomposition reactions from X-ray reflectivity measurements and theoretical calculations. The findings in this work suggest that design strategies based on surface and interfacial properties can be used to kinetically stabilize electrode/electrolyte interfaces in solid-state batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailoring the Interfacial Interactions of Porous Polymer Membranes to Accelerate Atomic Layer Deposition: The Latent Path to Antifouling Membranes

Atomic layer deposition (ALD) is a powerful strategy to engineer hybrid organic-inorganic membranes with emergent functionalities. The combination of atomic-level thickness control, a wide materials palette, and unprecedented conformality allows the physiochemical properties (e.g., hydrophilicity) of mesoporous polymer membranes to be precisely tuned. The nucleation of ALD material growth on polymer surfaces relies on Lewis acid-base interactions and remains an overlooked motif with tremendous potential to accelerate ALD nucleation and growth. Strategies to enhance these interactions could enable desirable properties such as antifouling behavior to be imparted on inert polymer surfaces that lack the necessary functional groups for ALD nucleation. Here, in this study, we demonstrate that the reactivity of polyacrylonitrile (PAN) membranes toward ALD metal oxide (MO) precursors with Lewis acid characteristics is enhanced by introducing strong Lewis base functional groups (amidoxime: Am) on the PAN backbone (Am-PAN). The resulting Lewis acid-base interactions accelerate the MO nucleation in Am-PAN and reduce the number of deposition cycles required to achieve hydrophilicity compared with the untreated PAN membrane. Unveiling the reaction mechanism, in situ Fourier transform infrared (FTIR) spectroscopy measurements established enhanced interaction dynamics between the ALD MO precursors and the Am-PAN membrane, unlike the PAN membrane. Spectroscopic ellipsometry and thermogravimetric analysis measurements revealed higher MO loadings in Am-PAN membranes compared to PAN membranes for the same number of ALD cycles. We found that strong Lewis acid-base interactions accelerated the ALD for a range of materials including Al 2 O 3 , TiO 2 , SnO 2 , and ZnO. More broadly, our work demonstrates that tailoring metal-precursor-polymer interactions is a powerful strategy to accelerate and modulate the ALD. We used this design strategy to fabricate Al 2 O 3 -Am-PAN hybrid membranes that showed 2-fold higher antifouling capability compared to pristine PAN membranes prepared with an equivalent number of Al 2 O 3 ALD cycles. Our approach expands the scope of design options for fouling-resistant porous hybrid inorganic-organic membranes and may ultimately reduce the operational costs of water treatment.

36 MATERIALS SCIENCE↗

Tailoring the Structure of Carbon Molecular Sieves Derived from an Aromatic Polyamide

Energy-efficient and selective separation technologies are required to reclaim aqueous waste streams for reuse. Carbon molecular sieves (CMS) are one material capable of separating organic solvent and gaseous mixtures due to the presence of permanent, rigid, and molecular sieving pores and could potentially be used in aqueous separations. Here, a novel CMS material is derived from an aromatic polyamide precursor with tailored fabrication techniques. Structural characteristics of this CMS have been probed with various analyses and are potentially ideal for selective separations as adsorbents. In this work, elemental analyses provide insight about the potential chemical structures of CMS materials that result from degradation mechanisms. Gravimetric sorption data is used to estimate sorption, diffusion, and permeability selectivity with water and N, N-dimethylformamide. While challenges to the development and implementation of such carbonaceous materials remain, highly selective materials are critical starting points for enabling ultra-challenging separation processes of the future.

36 MATERIALS SCIENCE↗

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗

Synergistic Combination of Living Ring-Opening Metathesis Polymerization and Atom Transfer Radical Polymerization to Synthesize Structurally Tailored and Engineered Macromolecular Networks

Structurally tailored and engineered macromolecular (STEM) networks are attractive materials for soft robotics, stretchable electronics, tissue engineering, and 3D printing due to their tunable properties. To date, STEM networks have been synthesized by atom transfer radical polymerization (ATRP) or the combination of reversible addition–fragmentation chain-transfer (RAFT) polymerization and ATRP. RAFT polymerization could have limited selectivity with ATRP inimer sites that can participate in radical-transfer processes. On the other hand, living ring-opening metathesis polymerization (ROMP) can produce a polymeric network with latent ATRP initiator sites in high selectivity. Herein, for the first time, we report the syntheses of STEM zero-generation (STEM-0) networks using a monomer, a cross-linker, and an ATRP/ROMP inimer via living ROMP, followed by their modification using a second monomer via ATRP to synthesize STEM first-generation (STEM-1) networks. The mechanical property and swelling capacity analyses of these networks were carried out. A change in mechanical properties and swelling capacity of these networks was observed due to their structural modification.

Absorption↗

Plasma-Induced Tailoring of Graphene Oxide Surfaces for Electrochemical Applications: Functionalization and Etching

This study investigates the use of radio frequency air plasma as an eco-friendly method to rapidly and reversibly tailor the surface properties of graphene oxide (GO) films. We observed a transition from hydrophilic (contact angle ∼55°) to superhydrophilic (<10°) with short plasma exposure, attributed to a synergistic combination of surface modification and etching. Spectroscopic analyses (FTIR, XPS) revealed early stage formation of carbonyl groups and reduction of hydroxyls, while longer treatments induced atomic-level etching (AFM) and structural changes (XRD). This surface engineering enhanced the dielectric properties of GO films but led to reduced aqueous stability. The elucidated interplay between plasma-induced functionalization and etching provides valuable insights for the controlled modification of GO surfaces for various applications, including advanced dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailoring Solvation Solvent in Localized High-Concentration Electrolytes for Lithium||Sulfurized Polyacrylonitrile

Sulfurized polyacrylonitrile (SPAN) is a promising cathode material for lithium-sulfur (Li-S) batteries due to its significantly reduced polysulfide (PS) dissolution compared to the elemental S cathode. Although conventional carbonate-based electrolytes is stable with SPAN electrodes, it is less stable with Li metal anode (LMA). Recently, localized high-concentration electrolytes (LHCEs) have been developed to improve the stability of LMA. Here, we report a new strategy to further improve the performance of LI||SPAN batteries by replacing the conventional solvating solvent 1,2-dimethoxyethane (DME) in the LHCE with a new solvating solvent, 1,2-diethoxyethane (DEE), the new LHCEs exhibits less reactivity against Li 2 S 2 , alleviates PS dissolution, forms a better cathode-electrolyte interphase layer on the SPAN, and enhances structure reversibility even at elevated temperature (ET, 45°C). With the same salt and diluent as in other LHCEs, the LHCE with DEE leads to better performance in Li||SPAN batteries (with 82.9% capacity retention after 300 cycles at ET), preservation of SPAN cathode structure, and suppression of the volume change of LMA. The similar strategy on tailoring the solvating solvents in LHCEs can also be used in other rechargeable batteries to improve their performances.

1,2-diethoxyethane↗

Tailoring the Physicochemical Properties of Nb Thin Films via Surface Engineering Methods

The modification of surface oxide layers formed on niobium (Nb) thin films via chemical mechanical planarization (CMP) and accelerated neutral atom beam (ANAB) processing provides a promising route toward tailoring their emergent properties and performance when used as superconducting qubits. Here, in this study, we show that CMP- and ANAB-formed Nb oxides are significantly thinner and smoother than the native oxide, as revealed by transmission electron microscopy (TEM) and atomic force microscopy. Scanning TEM and energy-dispersive X-ray spectroscopy along with X-ray photoelectron spectroscopy identified an oxidation gradient within the native and surface-engineered oxides. The topside layer is dominated by Nb 5+ (Nb 2 O 5 ), with various Nb suboxides present closer to the oxide/metal interface. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiling confirmed the presence of an oxygen content gradient and demonstrated the enhanced resistance of the CMP- and ANAB-formed oxides to oxygen surface exchange and subsequent diffusion via 18 O 2 isotopic labeling experiments. ToF-SIMS also identified an interfacial layer containing trapped hydrogen (H)-containing species at the Nb oxide/metal interface. In situ ToF-SIMS and TEM revealed migration of the H/OH interfacial layer coinciding with decomposition of the surface oxide. Furthermore, our density functional theory calculations indicated that both H from moisture present in ambient air and bulk H in Nb films tend to segregate at the interface. These findings underscore the importance of understanding surface oxidation mechanisms, hydrogen incorporation, and their impact on the designed functionalities of Nb-based devices.

36 MATERIALS SCIENCE↗

Enhancing Low-Temperature Syngas Production via Surface Tailoring of Supported Intermetallic Nanocatalysts

An active and coke-resistant silica-encapsulated intermetallic Ni 3 Zn nanoparticle catalyst was developed for low-temperature (450 °C) dry reforming of methane (DRM). The catalyst exhibited a remarkable 4-fold increase in activity (4.5 s –1 ) with over 99% CO selectivity and 3 orders of magnitude less carbonaceous species and demonstrated remarkable stability (70 h) compared to that of a monometallic Ni catalyst. Here, the key is the combined effect of surface ensemble structure and electronic interaction modulation through the surface composition tailoring achieved by off-stoichiometric Ni and Zn loading in controlling surface chemistry for achieving different activities and H 2 /CO ratios. Characterized by ion spectroscopy, X-ray photoelectron spectroscopy, and the neutron pair distribution function, it was revealed that paired Ni δ – –Zn δ+ active sites are crucial for DRM. Transient infrared spectroscopy and isotopic analysis uncovered the synergistic effect of Ni δ – –Zn δ+ sites in activating C–H bonds and dissociating CO 2 to prevent coke formation under low-temperature conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heuristic Computational Model for Predicting Lignin Solubility in Tailored Organic Solvents

Lignin is a random heteropolymer that has been extensively studied as a renewable source of aromatic precursors for high-value chemicals, biofuels, and bioplastics. A key challenge in lignin valorization is the structural and compositional heterogeneity of lignin feedstocks. Solvent-based approaches are commonly used to fractionate lignin to reduce this heterogeneity, but solvent selection can be challenging due to variability in lignin composition. In this work, we developed computational methods to predict good and poor organic solvents as a function of lignin composition. We analyzed 28 different linear pentamer structures, 18 from known libraries and 10 hypothetical polymers, and calculated their activity coefficients in 50 different organic solvents by using the conductor-like screening model for realistic solvents. We used these data to train a regression model that enabled the extensive investigation of the impact of solvent and monolignol compositions on predicted lignin solubility. The exhaustive exploration of solubility trends using model predictions revealed sets of solvents, identified using Kamlet–Taft parameters, that are predicted to promote lignin dissolution regardless of lignin composition. We further identified solvents expected to selectively isolate lignin fractions enriched in certain subunits. Furthermore, these results establish heuristic guidelines for solvent selection that can be used to tailor fractionation processes for lignin feedstocks of distinct composition or to design new processes that isolate fractions with higher proportions of selected subunits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of Bio-Based Repairable Polyimines with Tailored Properties by Lignin Fractionation

Developing sustainable polymers with low-value lignin remains a challenge. Herein, lignin-containing repairable polyimines were synthesized with tailored properties using lignin fractionation. First, softwood Kraft lignin is fractionated into a more homogeneous fraction with a lower molecular weight and a higher OH content. Next, Kraft lignin and its fraction are esterified by levulinic acid to introduce active ketone groups and subsequently condensed with oleylamine (OAm) and bis(3-aminopropyl)-terminated polydimethylsiloxane (PDMS) via a catalyst-free Schiff-base reaction to form grafted lignin-OAm copolymers and cross-linked lignin-PDMS polymer networks (MKL-P and MFL-P), respectively. Results show that lignin-OAm polyimines can be self-repaired and hot reprocessed under pressure, while lignin-PDMS polyimines can be repaired with the assistance of a healing agent, heat, and pressure. Dynamic mechanical analyses demonstrate that the stress–relaxation behaviors of the polyimines follow the Arrhenius law under thermal-stress activation, indicating the occurrence of transimination. Moreover, compared with Kraft lignin, the lignin fraction ameliorates the grafting density of ketones and enhances the cross-linking density of lignin-PDMS polyimine networks. The higher cross-linking density of MFL-P leads to superior stress–relaxation activation energy, thermal stability, hydrophobicity, and light-shielding ability but inferior repairability and translucency. Finally, this work provides insights into the polymerization of lignin-based polymer networks and the potential application of lignin-PDMS polyimines for repairable, translucent, anti-UV, and hydrophobic coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tailoring Interfaces for Enhanced Methanol Production from Photoelectrochemical CO 2 Reduction

Efficient and stable photoelectrochemical reduction of CO 2 into highly reduced liquid fuels remains a formidable challenge, which requires an innovative semiconductor/catalyst interface to tackle. In this study, we introduce a strategy involving the fabrication of a silicon micropillar array structure coated with a superhydrophobic fluorinated carbon layer for the photoelectrochemical conversion of CO 2 into methanol. The pillars increase the electrode surface area, improve catalyst loading and adhesion without compromising light absorption, and help confine gaseous intermediates near the catalyst surface. The superhydrophobic coating passivates parasitic side reactions and further enhances local accumulation of reaction intermediates. Upon one-electron reduction of the molecular catalyst, the semiconductor–catalyst interface changes from adaptive to buried junctions, providing a sufficient thermodynamic driving force for CO 2 reduction. These structures together create a unique microenvironment for effective reduction of CO 2 to methanol, leading to a remarkable Faradaic efficiency reaching 20% together with a partial current density of 3.4 mA cm –2 , surpassing the previous record based on planar silicon photoelectrodes by a notable factor of 17. Furthermore, this work demonstrates a new pathway for enhancing photoelectrocatalytic CO 2 reduction through meticulous interface and microenvironment tailoring and sets a benchmark for both Faradaic efficiency and current density in solar liquid fuel production.

14 SOLAR ENERGY↗

Entropy-Tailored Fast-Charging Sodium Layered Cathodes

O3-type layered transition metal (TM) oxides are widely used as cathode materials for Na-ion batteries due to their high energy density potential, enabled by the state of charge (SoC)-dependent transition from octahedral (O-type) to prismatic (P-type) structures during Na-ion (de)sodiation. However, the O–P transition is often criticized for compromising the Na-ion mobility and limiting the cycle life. Herein, we reveal the intrinsic correlation between O–P transitions, oxygen behaviors, and Na-ion kinetics. We demonstrate that a compositionally versatile, entropy-tailored approach can promote preferred transitions (characterized by large lattice parameter deviations in the O-type region and rapid O–P biphasic reactions), enhancing Na-ion migration, as revealed by in situ high-energy synchrotron X-ray diffraction (HEXRD). Additionally, irreversible oxygen loss at high SoC is effectively mitigated, while TM migration and surface reconstruction are greatly suppressed, further accelerating Na-ion transport and stabilizing the structure, as confirmed by X-ray absorption spectroscopy (XAS) and theoretical analyses. The result is an exceptionally high rate capability of 88.7 mAh g –1 at 20 C (2.4 A g –1 ) with a superior normalized retention of 72.6%, accompanied by a prolonged lifetime with 74.3% retention after 1000 cycles. In conclusion, this work advances the understanding of the chemistry–property relationships in O3-type layered cathodes and broadens the prospects for fabricating high-power-density electrodes.

36 MATERIALS SCIENCE↗

Ultra-short pulse laser acceleration of protons to 80 MeV from cryogenic hydrogen jets tailored to near-critical density

Laser plasma-based particle accelerators attract great interest in fields where conventional accelerators reach limits based on size, cost or beam parameters. Despite the fact that particle in cell simulations have predicted several advantageous ion acceleration schemes, laser accelerators have not yet reached their full potential in producing simultaneous high-radiation doses at high particle energies. The most stringent limitation is the lack of a suitable high-repetition rate target that also provides a high degree of control of the plasma conditions required to access these advanced regimes. Here, we demonstrate that the interaction of petawatt-class laser pulses with a pre-formed micrometer-sized cryogenic hydrogen jet plasma overcomes these limitations enabling tailored density scans from the solid to the underdense regime. Our proof-of-concept experiment demonstrates that the near-critical plasma density profile produces proton energies of up to 80 MeV. Based on hydrodynamic and three-dimensional particle in cell simulations, transition between different acceleration schemes are shown, suggesting enhanced proton acceleration at the relativistic transparency front for the optimal case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tailoring tokamak error fields to control plasma instabilities and transport

A tokamak relies on the axisymmetric magnetic fields to confine fusion plasmas and aims to deliver sustainable and clean energy. However, misalignments arise inevitably in the tokamak construction, leading to small asymmetries in the magnetic field known as error fields (EFs). The EFs have been a major concern in the tokamak approaches because small EFs, even less than 0.1%, can drive a plasma disruption. Meanwhile, the EFs in the tokamak can be favorably used for controlling plasma instabilities, such as edge-localized modes (ELMs). Here we show an optimization that tailors the EFs to maintain an edge 3D response for ELM control with a minimized core 3D response to avoid plasma disruption and unnecessary confinement degradation. We design and demonstrate such an edge-localized 3D response in the KSTAR facility, benefiting from its unique flexibility to change many degrees of freedom in the 3D coil space for the various fusion plasma regimes. This favorable control of the tokamak EF represents a notable advance for designing intrinsically 3D tokamaks to optimize stability and confinement for next-step fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗