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At least 109 records · Page 6

Embracing Anisotropy – Opportunities and Challenges to the Functional Application of Advanced Manufacturing of Energetic Materials

The growing use of additive manufacturing (AM) to manipulate materials, such as metals and plastics, is a result of the desire to realize the potential benefits (i.e., cheaper, faster, and simpler production of complex parts) of the process and the efforts of countless researchers to reduce the method to practice for a broad range of materials. However, in the field of energetic materials (EMs), similar benefits have been broadly claimed, but the transition to practical, industrial applications is still not obvious. The translation of small-scale experimental results to real-world application will have unique challenges, especially due to the nature and requirements of EM functionality. Some of the benefits of AM, such as simpler and faster part creation, are more easily realized. However, attaining the most profound benefits, such as added functionality enabled by spatial gradations of composition or density, will require much more effort from the EMs community to put them into general use.

36 MATERIALS SCIENCE↗

Tunable Polarity Behavior and Self-Driven Photoswitching in p-WSe 2 /n-WS 2 Heterojunctions

In Van der Waals (vdW) p–n heterojunctions consisting of various 2D layer compounds are fascinating new artificial materials that can possess novel physics and functionalities enabling the next-generation of electronics and optoelectronics devices. Here, it is reported that the WSe 2 /WS 2 p–n heterojunctions perform novel electrical transport properties such as distinct rectifying, ambipolar, and hysteresis characteristics. Intriguingly, the novel tunable polarity transition along a route of n-“anti-bipolar”–p-ambipolar is observed in the WSe 2 /WS 2 heterojunctions owing to the successive work of conducting channels of junctions, p-WSe 2 and n-WS 2 on the electrical transport of the whole systems. Moreover, the type-II band alignment we obtained from first principle calculations and built-in potential in this vdW heterojunction can also facilitate the efficient electron–hole separation, thus enabling the significant photovoltaic effect and a much enhanced self-driven photoswitching response in this system.

14 SOLAR ENERGY↗

Effects of threshold resummation for large-x PDF in large momentum effective theory

Parton distribution functions (PDFs) at large x are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of the large momentum P z expansion of lattice quasi-PDFs, we investigate large x PDFs, where the matching coefficient is factorized into the hard kernel, related to the active quark momentum xP z , and the threshold soft function, associated with the spectator momentum (1 − x)P z . The renormalization group equation of the soft function enables the resummation of the threshold double logarithms α k ln 2k (1 − x), which is crucial for a reliable and controllable calculation of large x PDFs. Our analysis with pion valence PDFs indicates that perturbative matching breaks down when the spectator momentum (1 − x)P z approaches Λ QCD , but remains valid when both xP z and (1 − x)P z are much larger than Λ QCD . Additionally, we incorporate leading renormalon resummation within the threshold framework, demonstrating good perturbative convergence in the region where both spectator and active quark momenta are perturbative scales.

factorization↗

Object-space optimization of tomographic reconstructions for additive manufacturing

Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated with realistic projector point spread functions, printing around occluding structures, printing with restricted angular range, and incorporation of materials chemistry such as inhibition. Finally, simulations show that the method facilitates new printing modalities such as printing into flat, rather than cylindrical packages to extend the applications of volumetric printing.

36 MATERIALS SCIENCE↗

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗

Atomic scale characterization of mismatched graphene layers

In the bourgeoning field of two dimensional layered materials and their atomically thin counterparts, it has been established that the electronic coupling between the layers of the material plays a key role in determining its properties. We are just beginning to understand how each material is unique in that respect while working our way up to building new materials with functionalities enabled by interlayer interactions. Here in this review, we will focus on a system that despite its apparent simplicity possesses a wealth of intriguing physics: layers of graphene with various degree of coupling. The situations discussed here are graphene layers vertically twisted with respect with each other, weakly decoupled electronically and laterally twisted forming grain boundaries. We emphasize experiments that atomically resolve the electronic properties.

74 ATOMIC AND MOLECULAR PHYSICS↗

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗

Engineered Biosynthesis of Alkyne-Tagged Polyketides by Type I PKSs

Polyketides produced by modular polyketide synthases (PKSs) are important small molecules widely used as drugs, pesticides, and biological probes. Tagging these polyketides with a clickable functionality enables the visualization, diversification, and mode of action study through bio-orthogonal chemistry. We report the de novo biosynthesis of alkyne-tagged polyketides by modular type I PKSs through starter unit engineering. Specifically, we use JamABC, a terminal alkyne biosynthetic machinery from the jamaicamide B biosynthetic pathway, in combination with representative modular PKSs. We demonstrate that JamABC works as a trans loading system for engineered type I PKSs to produce alkyne-tagged polyketides. In addition, the production efficiency can be improved by enhancing the interactions between the carrier protein (JamC) and PKSs using docking domains and site-directed mutagenesis of JamC. This work thus provides engineering guidelines and strategies that are applicable to additional modular type I PKSs to produce targeted alkyne-tagged metabolites for chemical and biological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lignin valorization reshapes sustainable biomass refining

As the largest natural reservoir of aromatics, lignin offers significant potential for bioproduct manufacturing through advances in valorization technologies. However, the intrinsically complex structures of lignin pose significant challenges for its fractionization and downstream valorization. Overcoming challenges in lignin chemistry modification is crucial for achieving effective lignin valorization and establishing sustainable biorefinery industries. This review explores the potential of tailoring lignin reactivity to enable functional bioproduct manufacturing thereby contributing to profitable biorefining. The intrinsic characteristics of lignin are first summarized, highlighting their roles in both fractionization and valorization. The latest progress in lignin fractionation is then presented, emphasizing their potential to tailor lignin chemistry, reactivity, and processibility. Furthermore, advancements in lignin valorization are covered, recognizing that tailored lignin reactivity is key to defining bioproduct functionality. By examining these chemical mechanisms, this review sheds on the structure-function relationships between lignin and its derived products. To address the dilemma of lignin valorization and biorefineries, a promising synergistic biorefinery is proposed. This involves redesigning biomass fractionation strategies, tailoring lignin chemistry, and upgrading both carbohydrate and lignin streams across the entire biorefinery chain—from feedstock to application. Altogether, a deeper understanding of tailored lignin chemistry is crucial for decoding the reaction mechanisms in biomass processing. A synergistic biorefinery could harness lignin's intrinsic properties to improve product functionality and address key challenges, paving the way for cost-effective, sustainable biorefinery solutions.

09 BIOMASS FUELS↗

Surface Immobilization of a Re(I) Tricarbonyl Phenanthroline Complex to Si(111) through Sonochemical Hydrosilylation

A sonochemical-based hydrosilylation method was employed to covalently attach a rhenium tricarbonyl phenanthroline complex to silicon(111). fac-Re(5-(p-Styrene)-phen)(CO) 3 Cl (5-(p-styrene)-phen = 5-(4-vinylphenyl)-1,10-phenanthroline) was reacted with hydrogen-terminated silicon(111) in an ultrasonic bath to generate a hybrid photoelectrode. Subsequent reaction with 1-hexene enabled functionalization of remaining atop Si sites. Attenuated total reflectance–Fourier transform infrared spectroscopy confirms attachment of the organometallic complex to silicon without degradation of the organometallic core, supporting hydrosilylation as a strategy for installing coordination complexes that retain their molecular integrity. Detection of Re(I) and nitrogen by X-ray photoelectron spectroscopy (XPS) further support immobilization of fac-Re(5-(p-styrene)-phen)(CO) 3 Cl. Cyclic voltammetry and electrochemical impedance spectroscopy under white light illumination indicate that fac-Re(5-(p-styrene)-phen)(CO) 3 Cl undergoes two electron reductions. Mott–Schottky analysis indicates that the flat band potential is 239 mV more positive for p-Si(111) co-functionalized with both fac-Re(5-(p-styrene)-phen)(CO) 3 Cl and 1-hexene than when functionalized with 1-hexene alone. XPS, ultraviolet photoelectron spectroscopy, and Mott–Schottky analysis show that functionalization with fac-Re(5-(p-styrene)-phen)(CO) 3 Cl and 1-hexene introduces a negative interfacial dipole, facilitating reductive photoelectrochemistry.

X-ray photoelectron spectroscopy↗

Designing Multiscale Porous Metal by Simple Dealloying with 3D Morphological Evolution Mechanism Revealed via X-ray Nano-tomography

Designing materials with multiscale, hierarchical structure is critical to drive the advancement of new technology. Specifically, porous metals with multiscale porosity from nanometer to micrometer sizes would lead to enhanced physical and chemical properties—the micron-sized pores can increase the effective diffusivity of ion transport within the porous media, and the nano-sized pores provide high specific surface area, enabling functionalities that are unique to nanoporous metals. A new ternary precursor alloy selection concept utilizing the different mixing enthalpies is demonstrated in this work for the design of multiscale, bimodal porous copper from a simple, one-step dealloying of Cu–Fe–Al ternary alloy. The nanoporosity in the bimodal porous structure is formed from dealloying of the Cu-rich phase, whereas the microporosity is controlled by dissolving the Fe-rich phase, determined by both the initial Fe particle size and sintering profile. In addition to advancing the materials design method, the multiscale pore formation during dealloying was directly visualized and quantified via an interrupted in situ synchrotron X-ray nano-tomography. The 3D morphological analysis on tortuosity showed that the presence of the microporosity can compensate the increase of the diffusion path length due to nanoporosity, which facilitates diffusion within the porous structure. Altogether the focus of the work is to introduce a new strategy to design multiscale porous metals with enhanced transport properties, and sheds light on the fundamental mechanisms on the 3D morphological evolution of the system using advanced synchrotron X-ray nano-tomography for future materials development and applications.

36 MATERIALS SCIENCE↗

Kinetic Control of Angstrom-Scale Porosity in 2D Lattices for Direct Scalable Synthesis of Atomically Thin Proton Exchange Membranes

Angstrom-scale pores introduced into atomically thin 2D materials offer transformative advances for proton exchange membranes in several energy applications. Here, we show that facile kinetic control of scalable chemical vapor deposition (CVD) can allow for direct formation of angstrom-scale proton-selective pores in monolayer graphene with significant hindrance to even small, hydrated ions (K + diameter ~6.6 Å) and gas molecules (H 2 kinetic diameter ~2.9 Å). We demonstrate centimeter-scale Nafion|Graphene|Nafion membranes with proton conductance ~3.3–3.8 S cm –2 (graphene ~12.7–24.6 S cm –2 ) and H + /K + selectivity ~6.2–44.2 with liquid electrolytes. The same membranes show proton conductance ~4.6–4.8 S cm –2 (graphene ~39.9–57.5 S cm –2 ) and extremely low H 2 crossover ~1.7 × 10 –1 – 2.2 × 10 –1 mA cm –2 (~0.4 V, ~25 °C) with H 2 gas feed. We rationalize our findings via a resistance-based transport model and introduce a stacking approach that leverages combinatorial effects of interdefect distance and interlayer transport to allow for Nafion|Graphene|Graphene|Nafion membranes with H + /K + selectivity ~86.1 (at 1 M) and record low H 2 crossover current density ~2.5 × 10 –2 mA cm –2 , up to ~90% lower than state-of-the-art ionomer Nafion membranes ~2.7 × 10 –1 mA cm –2 under identical conditions, while still maintaining proton conductance ~4.2 S cm –2 (graphene stack ~20.8 S cm –2 ) comparable to that for Nafion of ~5.2 S cm –2 . Furthermore, our experimental insights enable functional atomically thin high flux proton exchange membranes with minimal crossover.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Brush Polymer Infrared One-Dimensional Photonic Crystals via Linear Polymer Additives

Brush block copolymers (BBCPs) enable the rapid fabrication of self-assembled one-dimensional photonic crystals with photonic band gaps that are tunable in the UV-vis-IR, where the peak wavelength of reflection scales with the molecular weight of the BBCPs. Due to the difficulty in synthesizing very large BBCPs, the fidelity of the assembled lamellar nanostructures drastically erodes as the domains become large enough to reflect IR light, severely limiting their performance as optical filters. To overcome this challenge, short linear homopolymers are used to swell the arrays to ~180% of the initial domain spacing, allowing for photonic band gaps up to~1410 nm without significant opacity in the visible, demonstrating improved ordering of the arrays. Additionally, blending BBCPs with random copolymers enables functional groups to be incorporated into the BBCP array without attaching them directly to the BBCPs. The addition of short linear polymers to the BBCP arrays thus offers a facile means of improving the self-assembly and optical properties of these materials, as well as adding a route to achieving films with greater functionality and tailorability, without the need to develop or optimize the processing conditions for each new brush polymer synthesized.

Macfarlane, Robert J.↗

Chemical Control of Symmetry and Bandgap in Tungsten Oxyhalide van der Waals Semiconductors

Tunability in solid-state materials is essential for testing theory, discovering quantum phases, and enabling functionality. Layered van der Waals (vdW) semiconductors offer a unique platform, providing new degrees of freedom at the two-dimensional (2D) limit through exfoliation and external controls. Here, in this study, we demonstrate tunability of symmetry and electronic structure via halogen substitution in a family of layered vdW tungsten oxyhalides. Substituting the halogens in WO 2 X 2 (X = I, Br, Cl) tunes the bandgap across a broad energy range and modifies the structural symmetry from centrosymmetric to noncentrosymmetric. By alloying WO 2 I 2– y Br y , we continuously tune the polar distortion and optical gap across the visible range. These insights into halogen substitution effects on symmetry and electronic structure lay the foundation for new tunable vdW semiconductors for optoelectronics and nonlinear optics.

36 MATERIALS SCIENCE↗

Data Imbalance, Uncertainty Quantification, and Transfer Learning in Data‐Driven Parameterizations: Lessons From the Emulation of Gravity Wave Momentum Transport in WACCM

Abstract Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non‐linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large‐amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN‐based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics‐based gravity wave (GW) parameterizations as a test case. WACCM has complex, state‐of‐the‐art parameterizations for orography‐, convection‐, and front‐driven GWs. Convection‐ and orography‐driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto‐encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO 2 ). However, their performance is significantly improved by applying transfer learning, for example, re‐training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data‐driven parameterizations for various processes, including (but not limited to) GWs.

54 ENVIRONMENTAL SCIENCES↗

Atomistic characterization of the active-site solvation dynamics of a model photocatalyst

The interactions between the reactive excited state of molecular photocatalysts and surrounding solvent dictate reaction mechanisms and pathways, but are not readily accessible to conventional optical spectroscopic techniques. Here we report an investigation of the structural and solvation dynamics following excitation of a model photocatalytic molecular system [Ir 2 (dimen) 4 ] 2+ , where dimen is para-diisocyanomenthane. The time-dependent structural changes in this model photocatalyst, as well as the changes in the solvation shell structure, have been measured with ultrafast diffuse X-ray scattering and simulated with Born-Oppenheimer Molecular Dynamics. Both methods provide direct access to the solute–solvent pair distribution function, enabling the solvation dynamics around the catalytically active iridium sites to be robustly characterized. Our results provide evidence for the coordination of the iridium atoms by the acetonitrile solvent and demonstrate the viability of using diffuse X-ray scattering at free-electron laser sources for studying the dynamics of photocatalysis.

74 ATOMIC AND MOLECULAR PHYSICS↗

In-plane quasi-single-domain BaTiO 3 via interfacial symmetry engineering

The control of the in-plane domain evolution in ferroelectric thin films is not only critical to understanding ferroelectric phenomena but also to enabling functional device fabrication. However, in-plane polarized ferroelectric thin films typically exhibit complicated multi-domain states, not desirable for optoelectronic device performance. Here we report a strategy combining interfacial symmetry engineering and anisotropic strain to design single-domain, in-plane polarized ferroelectric BaTiO 3 thin films. Theoretical calculations predict the key role of the BaTiO 3 /PrScO 3 (110) O substrate interfacial environment, where anisotropic strain, monoclinic distortions, and interfacial electrostatic potential stabilize a single-variant spontaneous polarization. A combination of scanning transmission electron microscopy, piezoresponse force microscopy, ferroelectric hysteresis loop measurements, and second harmonic generation measurements directly reveals the stabilization of the in-plane quasi-single-domain polarization state. This work offers design principles for engineering in-plane domains of ferroelectric oxide thin films, which is a prerequisite for high performance optoelectronic devices.

36 MATERIALS SCIENCE↗