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At least 325 records · Page 18

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Ducted Fuel Injection And Cooled Spray Technologies For Particulate Control In Heavy-duty Diesel Engines (Final Report)

Cooled Spray (CS) and Ducted Fuel Injection (DFI) are in-cylinder technologies for diesel engines that can reduce particulate matter and soot emissions and data has been published showing that these technologies can reduce soot emissions by 75-100% for some engines at some operating conditions. However, little is known about scaling the devices for engine size. Additionally, the performance of either technology over the engine duty cycle has not been explored. This project addresses both of these points through single-cylinder engine investigations. The objectives of this project are to provide details about dimensional scaling of these devices and to demonstrate 75% PM reduction over a range of operating conditions on a single-cylinder engine. Two engines were used for this project: a 125mm bore optically accessible engine at Sandia National Laboratories and a 168mm bore metal engine at Southwest Research Institute. The optical engine was used to study the performance of DFI and CS inserts for a large injector orifice diameter injector that is characteristic of a locomotive engine and to perform scaling studies for DFI. The metal engine was used to perform scaling and alignment studies for CS and to evaluate the technology for both EGR and non-EGR engines over the engine operating map. Modifications were required for both engines to accept the prototype inserts being tested. The optical engine required a new fuel injector, cylinder head and piston so that tests could be run at the pressures and engine speeds required. Additionally, a novel rotating stage was designed for the optical engine to simplify alignment of the modules. The metal engine required a modified cylinder head to accept CS inserts and a modified piston to provide additional space around the fuel injector for the CS inserts. Tests on the optical engine showed that DFI reduces PM emissions for both small injector orifices (0.170mm diameter) and large injector orifices (0.290mm). For high load testing, the DFI modules were not as effective as at low load testing, but it was acknowledged that minimal geometric optimization was performed and more improvements may be possible. Comparing DFI to CS and conventional diesel combustion (CDC), DFI performed better than CS or CDC. The CS geometries used in these studies may not be ideal for that engine and additional modifications likely would improve performance. Tests on the metal engine showed PM reductions as high has 80% at some operating conditions with duty-cycle PM reductions of ~50% for EGR and non-EGR configurations. The CS testing on the metal engine showed that chamfering of the fuel passage inlet either through hydro-erosion or mechanical grinding provided significant improvements in the PM reduction capabilities of the insert. Additionally, alignment sensitivities were explored and the data show that the tolerance to misalignment is approximately 0.05 to 0.1mm for the inserts that were studied here. Air-fuel ratio was shown to be important in the effectiveness of the CS inserts. In several tests, it was shown that the CS inserts are more effective at reducing the PM for high-AFR operating conditions compared to low AFR conditions. In summary, multiple designs were evaluated on both engines. It was found that for the conditions and configurations studied here, a fuel passage diameter of ~2.5mm performed best overall. Significant duty-cycle PM reductions are possible using these technologies and sensitivities to AFR, alignment fuel passage diameter and inlet fuel passage shaping were explored and are reported here. More PM reduction may be possible with improved geometric design and attention to alignment practices.

02 PETROLEUM↗

Fundamental Understanding of “Fresh” Lithium Nucleation and Growth in Sulfide-Based Anode-Free Solid-State Batteries: Effects of Substrate, Current Density, and Li + Supply

Understanding the electrochemical extraction and deposition of lithium (Li) from cathode is crucial for advancing anode-free solid-state batteries (AFSSBs). Herein, cryo-transmission electron microscopy (cryo-TEM) and electrochemical studies are employed to investigate how current collector surface properties, current densities, and cathode loadings influence the morphology of fresh electrochemically deposited Li and the electrochemical performance in sulfide-based AFSSBs. Cryo-TEM reveals that Cu current collectors induce irregular, dendritic Li deposits due to their lithiophobic nature and reactivity with Li 5.4 PS 4.4 Cl 1.6 (LPSC), while Ni and Au facilitate more uniform, planar-like Li growth. The morphology of the deposited Li also depends on current density: higher rates produce smaller, porous particles versus larger, denser deposits at lower rates. Importantly, for the first time, we discovered that low cathode loadings lead to poor cycling stability due to insufficient Li + supply for complete anode coverage, contrary to conventional solid-state batteries with preloaded Li metal anodes. This finding establishes a design principle where adequate cathode Li + reservoirs are essential for anode interface stability in AFSSBs. Overall, this work elucidates the interplayed effect of current collectors, current densities, and cathode loadings on Li morphology and cycle stability, offering fundamental insights into cathode-derived Li behavior and practical guidelines for optimizing AFSSBs performance through nucleation control and interface engineering.

25 ENERGY STORAGE↗

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

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

BaNi2P2↗

The Fluid Dynamics Uncertainty Quantification Challenge Problem: XFOIL vs. MFOIL

Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.

Lay, Aidan S [University of Tennessee, Knoxville (↗

Higher-order factorization machine for accurate surrogate modeling in material design

Efficient and robust optimization is important in material science for identifying optimal structural parameters and enhancing material performance. Surrogate-based active learning algorithms have recently gained great attention for their ability to efficiently navigate large, high-dimensional design spaces. Among surrogate models, 2 nd -order factorization machine (FM) models are widely employed as the surrogate model in active learning algorithms due to their balance between simplicity and effectiveness. However, their quadratic nature limits their capacity to capture complex, higher-order interactions among variables, often leading to suboptimal solutions. To overcome this limitation, we propose an active learning scheme integrating a 3 rd -order FM model, capable of modeling three-variable interactions and more intricate relationships in material systems. We comprehensively evaluate the surrogate modeling performance of the 3 rd -order FM case using various objective functions. Furthermore, we examine the optimization reliability and efficiency of the 3 rd -order FM-based active learning in a real-world material design task (e.g., nanophotonic structures for transparent radiative cooling). Our study shows that the 3 rd -order FM outperforms the 2 nd -order model in both surrogate accuracy and optimization performance, highlighting higher-order models’ promises for material design and optimization problems.

Factorization machine↗

Optical Control of Adaptive Nanoscale Domain Networks

Adaptive networks can sense and adjust to dynamic environments to optimize their performance. Understanding their nanoscale responses to external stimuli is essential for applications in nanodevices and neuromorphic computing. However, it is challenging to image such responses on the nanoscale with crystallographic sensitivity. Here, the evolution of nanodomain networks in (PbTiO 3 ) n /(SrTiO 3 ) n superlattices (SLs) is directly visualized in real space as the system adapts to ultrafast repetitive optical excitations that emulate controlled neural inputs. The adaptive response allows the system to explore a wealth of metastable states that are previously inaccessible. Their reconfiguration and competition are quantitatively measured by scanning x-ray nanodiffraction as a function of the number of applied pulses, in which crystallographic characteristics are quantitatively assessed by assorted diffraction patterns using unsupervised machine-learning methods. The corresponding domain boundaries and their connectivity are drastically altered by light, holding promise for light-programable nanocircuits in analogy to neuroplasticity. Phase-field simulations elucidate that the reconfiguration of the domain networks is a result of the interplay between photocarriers and transient lattice temperature. The demonstrated optical control scheme and the uncovered nanoscopic insights open opportunities for the remote control of adaptive nanoscale domain networks.

36 MATERIALS SCIENCE↗

Minimizing Inter‐Lattice Strain to Stabilize Li‐Rich Cathode by Order–Disorder Control

Li-rich Mn-based layered (LMR) cathodes with anionic redox chemistry show great potential for next-generation sustainable Li-ion battery (LIB) applications due to the low cost and high energy density. However, the asynchronous structural evolutions with cycling in the heterogeneous composite structure of LMR lead to serious lattice strain and thus fast electrochemical decay, which hinders the commercialization of LMR cathodes. Here, in this study, an order–disorder coherent LMR cathode is demonstrated that exhibits a higher average voltage (by 0.25 V), negligible voltage decay (97.6% voltage retention after 100 cycles at 100 mA g −1 ), and enhanced cycling stability (98% capacity retention after 200 cycles at 100 mA g −1 ) compared to its layered oxide counterparts. It is proposed that this order–disorder coherent structure design can promote a more synchronous and homogeneous structure evolution during charge and discharge, thus minimizing lattice strain, which significantly prevents layer collapse and collective degradation at high voltage, improving the electrochemical stability. The study displays the feasibility of optimizing the performance of Li-rich cathode materials through a dedicated order–disorder structure control for sustainable energy storage.

Xu, Shenyang [Peking University, Shenzhen (China)]↗

Emulation of Synaptic Plasticity in WO 3 ‐Based Ion‐Gated Transistors

Neuromorphic systems, inspired by the human brain, promise significant advancements in computational efficiency and power consumption by integrating processing and memory functions, thereby addressing the von Neumann bottleneck. This paper explores the synaptic plasticity of a WO3-based ion-gated transistor (IGT) in [EMIM][TFSI] and a 0.1 mol L −1 LiTFSI in [EMIM][TFSI] for neuromorphic computing applications. Cyclic voltammetry (CV), transistor characteristics, and atomic force microscopy (AFM) force–distance (FD) profiling analyses reveal that Li + brings about ion intercalation, together with higher mobility and conductance, and slower response time (τ). WO 3 IGTs exhibit spike amplitude-dependent plasticity (SADP), spike number-dependent plasticity (SNDP), spike duration-dependent plasticity (SDDP), frequency-dependent plasticity (FDP), and paired-pulse facilitation (PPF), which are all crucial for mimicking biological synaptic functions and understanding how to achieve different types of plasticity in the same IGT. The findings underscore the importance of selecting the appropriate ionic medium to optimize the performance of synaptic transistors, enabling the development of neuromorphic systems capable of adaptive learning and real-time processing, which are essential for applications in artificial intelligence (AI).

36 MATERIALS SCIENCE↗

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

Effectiveness of nature-based solutions to reduce flooding in Quad Cities Metro Area (QCMA) using SWMM-HEC based flood model

Nature-based solutions (NbS) have gained significant attention as strategies for addressing urban environmental challenges, particularly since the establishment of the UN Sustainable Development Goals (SDGs) for 2030. However, the current research on NbS for urban flood management lacks comprehensive methodological approaches for identifying suitable areas and evaluating their effectiveness across different urban settings. Here, this study attempts to fill this gap by proposing a methodological framework integrating multi-criteria analysis with a SWMM-HEC-based hydrologic and hydraulic (HH) model to assess the suitability of NbS for the Quad Cities Metro Area (QCMA), consisting of Davenport, Bettendorf, Moline, and Rock Island. Eight NbS options-green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels/cisterns - were considered based on volumetric efficiency and runoff reduction efficiency. The study reveals that implementing the proposed NbS could have substantially reduced flood depths in key historical flood events by 21% in 1993, 15% in 2008, 16% in 2011, 23% in 2014, 40% in 2019, and 10% in 2023. The findings highlight a critical trade-off between peak runoff and NbS implementation: while NbS effectively reduce flood impacts, they also enhance volumetric efficiency by approximately 43%. In high-density areas of the QCMA, flood depth reductions of around 20% suggest that NbS are a viable solution for dense urban environments with limited space. This shows the potential for integrating NbS into existing infrastructure, offering a promising approach for cities facing increasing flooding risks. The proposed methodology provides a practical framework for incorporating NbS into urban stormwater management, addressing gaps in optimizing NbS performance, and offering a pathway to scale their application in other urban areas with various environmental and social contexts.

CMIP6↗

Tuning transition metal nanoparticles on a non-traditional support via experimental design

The ability to control metal nanoparticle size and morphology on supported catalysts is crucial for optimizing catalytic performance in targeted applications. Here, this work presents a systematic approach for tuning Ni particle and crystallite size on an unconventional, low-porosity silica fume support through select thermal treatments. The catalyst was synthesized via the deposition of nickelocene onto silica fume, resulting in well-dispersed Ni nanoparticles. A face-centered central composite design was employed to systematically assess the effects of time, temperature, and sintering gas environment on metal particle growth. The results demonstrate that the sintering gas environment is the primary factor governing particle and crystallite evolution, with temperature as the next most significant influence. Nickel nanoparticles sintered at temperatures of 650 °C and above under inert conditions exhibited substantial growth and polycrystalline structures, whereas samples treated in oxidative environments formed NiO, restricting particle mobility. Minimally oxidative (500 ppm O₂) environments facilitated rapid sintering while effectively removing residual ligands from the one-step nickelocene deposition process. Extensive structural characterization via a combination of scanning transmission electron microscopy, X-ray diffraction, hydrogen temperature programmed reduction, and small-angle X-ray scattering revealed that oxidative treatments enhanced metal-support interactions, as evidenced by increased reduction temperatures and narrower particle size distributions. These findings establish quantitative relationships between sintering parameters and Ni nanoparticle characteristics, providing a framework for rational catalyst design through controlled thermal treatments. This methodology is broadly applicable to other catalytic systems and provides a quantitative foundation for catalyst design.

CVD↗

A comparative study on cubic and tetragonal Ce-ZrO 2 supported Rh catalysts for N 2 O decomposition

Zirconium oxide (ZrO 2 ) exhibits strong synergy with cerium oxide (CeO 2 ), acting as a structural and electronic promoter during catalytic redox reactions. As a result, Ce-ZrO 2 composite oxides are widely used as supports in various catalytic systems. In our previous work, we demonstrated that the incorporation of Zr 4+ into the CeO 2 lattice significantly enhanced Rh dispersion, improved redox ability, and stabilized surface Rh species, which collectively boosted the de-N 2 O activity of Rh/Ce-ZrO 2 catalysts. Building on these findings, the present study emphasizes that the crystallographic phase of Ce-ZrO 2 , governed by the Ce/Zr ratio, plays a decisive role in tuning the physicochemical environment of Rh active sites and thereby optimizing catalytic performance. In conclusion, tailoring the Ce/Zr ratio to favor the cubic fluorite structure emerges as a promising strategy for the rational design of highly active and stable catalysts for N 2 O decomposition and potentially other redox-sensitive environmental applications.

36 MATERIALS SCIENCE↗

Current understanding of Oxidative Coupling of Methane (OCM) reaction over supported Mn-Na 2 WO 4 catalysts

This perspective reviews the current understanding of the Oxidative Coupling of Methane (OCM) reaction over the supported Mn-Na 2 WO 4 /SiO 2 catalyst, with a focus on recent insights gained from state-of-the-art in-situ and operando spectroscopic characterization and chemical probe experiments under controlled environments. The supported Mn-Na 2 WO 4 /SiO 2 catalyst exhibits dynamic structural changes during the OCM reaction, involving multiple reactive lattice and adsorbed oxygen species, each associated with different oxide phases. These oxygen species play distinct roles in various steps of the OCM mechanism. The catalytic active sites for activation of CH 4 are associated with isolated surface Na-WO x sites on the SiO 2 support and the role of surface MnO x sites on SiO 2 is to oxidatively dehydrogenate C 2 H 6 to C 2 H 4 . Furthermore, this paper provides a detailed discussion of these roles and also introduces new experimental data from Temporal Analysis of Products (TAP) studies to clarify the ongoing debate in the literature regarding the contributions of lattice versus adsorbed oxygen species in OCM reaction product formation. Additionally, recommendations are offered for optimizing the performance of supported Mn-Na 2 WO 4 /SiO 2 catalysts to enhance CH 4 activation and C 2 product selectivity.

03 - NATURAL GAS↗

Effect of dilute Rh on oxygen dissociation, spillover, and the oxidation of Cu across many orders of magnitude pressure

Knowledge of how trace amounts of more reactive metals influence the oxidation rate and mechanism of Cu surfaces is essential for developing strategies to optimize the performance of Cu-based catalysts. We find that the addition of 1% Rh to Cu(111) increases the initial O 2 dissociation rate by approximately 9-fold. CO poisoning experiments reveal that single Rh atoms activate O 2 and facilitate the spillover of atomic oxygen to Cu sites. Scanning tunneling microscopy (STM) and in situ X-ray photoelectron spectroscopy (XPS) support this mechanism, showing enhanced surface oxygen near Rh atoms. Here, a density functional theory (DFT)-based model demonstrates that Rh binds the O 2 precursor 0.15 eV more strongly than Cu(111) and lowers the O 2 dissociation barrier by 0.02 eV. Both single-crystal and nanoparticle experiments show that at low oxygen pressures, Rh enhances Cu oxidation, whereas at higher pressures, it inhibits deeper oxidation, as evidenced by in situ ultraviolet-visible (UV-vis) spectra.

36 MATERIALS SCIENCE↗

Perspectives and challenges of ultra-high temperature ceramics for fusion plasma-facing applications

Ultra-high temperature ceramics (UHTCs) offer several potential advantages as plasma-facing components (PFCs) in fusion reactors due to their extreme melting points, tailorable thermal conductivity, and attractive unirradiated mechanical properties including fracture toughness comparable or superior to tungsten. Here, recent developments and material properties of UHTCs are briefly reviewed, along with an overview of limited studies on their responses to neutron irradiation and an evaluation of plasma-surface interactions. Five key research pathways, primarily focused on irradiation effects, for advancing UHTCs in PFC applications are discussed: (1) assessing irradiation effects on the coupled thermal–mechanical performance (2) addressing the lack of studies on irradiation, plasma-surface interactions, and their synergistic effects; (3) investigating high-temperature (>1000 °C) neutron irradiation effects critical for PFC performance; (4) optimizing multi-component UHTC compositions or composites to improve thermal or mechanical properties; (5) enhancing radiation resistance to mitigate microcracking and void swelling through strategies such as increasing sink strength by reducing grain size, introducing fine particles, and leveraging complex concentrated alloy concepts.

36 MATERIALS SCIENCE↗

Hardenability and microstructural evolution of a precipitation strengthened Ni 50 Ti 21 Hf 25 Al 4 alloy

NiTi-based quaternary alloys are used in a variety of mechanical components, such as bearings, actuators, and dampers, owing to their good hardenability, wear resistance, and corrosion resistance. Additionally, one of the most notable characteristics of NiTi-based alloys is their shape memory effect and pseudoelastic properties. Connecting the macroscopic processing parameters employed in the design of new intermetallic alloys to the nanoscale structural characteristics dictating their behavior is crucial for improving their mechanical properties and expanding the spectrum of potential applications. Here, in this work, an arc melted Ni 50 Ti 21 Hf 25 Al 4 (at%) alloy was solution treated at 1050 °C followed by quenching and aging at 600 °C to investigate the effect of aging time on the microstructure and mechanical properties. Two types of nano-sized precipitates were observed and determined as face-centered orthorhombic H-phase (TiHf)Ni and L2 1 Heusler precipitates Ni 2 TiAl. The morphology and orientation of the H-phase were investigated using scanning and transmission electron microscopy (SEM and TEM), elucidating the coarsening kinetics and strengthening contribution of that phase to the intermetallic mechanical behavior. Following coarsening, the presence of Heusler nanoprecipitates was detected under overaged conditions through TEM imaging and nanobeam electron diffraction patterns. A peak hardness condition of 756 HV was achieved after 70 h of aging, indicating that the co-precipitation of H-phase and Heusler precipitates through a well-designed aging treatment can lead to optimal mechanical performance, thus elevating the alloy’s potential as a viable material for industrial applications.

36 MATERIALS SCIENCE↗