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At least 469 records · Page 26

Programming Amphiphilic Peptoid Oligomers for Hierarchical Assembly and Inorganic Crystallization

Natural organisms make a wide variety of exquisitely complex, nano-, micro-, and macroscale structured materials in an energy-efficient and highly reproducible manner. During these processes, the information-carrying biomolecules (e.g., proteins, peptides, and carbohydrates) enable (1) hierarchical organization to assemble scaffold materials and execute high-level functions and (2) exquisite control over inorganic materials synthesis, generating biominerals whose properties are optimized for their functions. Inspired by nature, significant efforts have been devoted to developing functional materials that can rival those natural molecules by mimicking in vivo functions using engineered proteins, peptides, DNAs, sequence-defined synthetic molecules (e.g., peptoids), and other biomimetic polymers. Among them, peptoids, a new type of synthetic mimetics of peptides and proteins, have received particular attention because they combine the merits of both synthetic polymers (e.g., high chemical stability and efficient synthesis) and biomolecules (e.g., sequence programmability and biocompatibility). The lack of both chirality and hydrogen bonds in their backbone results in a highly designable peptoid-based system with reduced structural complexity and side chain-chemistry-dominated properties. Here in this Account, we present our recent efforts in this field by programming amphiphilic peptoid sequences for (1) the controlled self-assembly into different hierarchically structured nanomaterials with favorable properties and (2) manipulating inorganic (nano)crystal nucleation, growth, and assembly into superstructures. First, we designed a series of amphiphilic peptoids with controlled side chain chemistries that self-assembled into 1D highly stiff and dynamic nanotubes, 2D membrane-mimetic nanosheets, hexagonally patterned nanoribbons, and 3D nanoflowers. These crystalline nanostructures exhibited sequence-dependent properties and showed promise for different applications. The corresponding peptoid self-assembly pathways and mechanisms were also investigated by leveraging in situ atomic force microscopy studies and molecular dynamics simulations, which showed precise sequence dependency. Second, inspired by peptide- and protein-controlled formation of hierarchical inorganic nanostructures in nature, we developed peptoid-based biomimetic approaches for controlled synthesis of inorganic materials (e.g., noble metals and calcite), in which we took advantage of the substantial side chain chemistry of peptoids and investigated the relationship between the peptoid sequences and the morphology and growth kinetics of inorganic materials. For example, to overcome the challenges (e.g., complexity of protein- and peptide-folding, poor thermal and chemical stabilities) facing the area of protein- and peptide-controlled synthesis of inorganic materials, we recently reported the design of sequence-defined peptoids for controlled synthesis of highly branched plasmonic gold particles. Moreover, we developed a rule of thumb for designing peptoids that predictively enabled the morphological evolution from spherical to coral-shaped gold nanoparticles (NPs). With this Account, we hope to stimulate the research interest of chemists and materials scientists and promote the predictive synthesis of functional and robust materials through the design of sequence-defined synthetic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New perspectives on materials and device dynamics using time-resolved full-field diffraction X-ray imaging

Understanding how materials evolve during synthesis, processing, or device operation requires experimental access to structural dynamics across wide ranges of length and time scales, often in bulk samples or even within packaged devices. Time-resolved full-field diffraction X-ray microscopy has recently emerged as a powerful way to meet this need by combining the penetration and structural sensitivity of X-ray diffraction with objective-lens-based magnification, sensitive high-resolution X-ray imaging detectors, and pump-probe and real-time imaging strategies. Advances in full-field X-ray diffraction microscopy, often termed dark-field X-ray microscopy (DFXM), enable simultaneous imaging of extended fields of view while retaining crystallographic selectivity. Time-resolved DFXM promises to enable advances in materials processing and dynamics, electrochemical and photochemical processes, and the design of electronic devices. This Perspective summarizes the key instrumental concepts that define the performance of these methods, including the choice of imaging optics, detector considerations, and the impact of source time structure at synchrotron light sources and X-ray free-electron lasers (XFELs). We discuss the simultaneous use of complementary imaging modes that are increasingly used in practice. The early demonstrations of the potential of time-resolved DFXM include real-time defect and grain-boundary dynamics during metal annealing, stroboscopic imaging of functional devices with high strain sensitivity, and ultrafast pump-probe implementations at XFELs that directly visualize acoustic-wave propagation and energy dissipation in bulk crystals.

Dark-field X-ray microscopy↗

Controlling reversible phase transitions in rare-earth nickelates for novel memory devices

Resistive switching in correlated complex oxides is lucrative for emerging applications in neuromorphic computing, and densely scaled non-volatile memory. Electrical conductance of such complex oxides can be controllable switched across multiple orders of magnitude by either (a) electroforming a conduction channel (e.g., in tungsten oxide), or (b) inducing Mott-Hubbard transition (e.g., in rare-earth nickelates)– both via controlled migration of defects (such as oxygen vacancies) under applied bias. Nevertheless, the promise of such defect-driven electronic transitions are far from realized due to a lack of fundamental understanding of the atomic-scale processes that underlie migration and spatiotemporal evolution of oxygen vacancies over nano-to-mesoscopic length/timescales under applied electric field. In this project, we employ a synergistic integration of density functional theory (DFT) calculations, ab initio/classical molecular dynamics (AIMD/CMD) simulations, machine learning (ML), precision synthesis, and multi-modal X-ray imaging experiments to address this knowledge gap. Such an integrated approach offers to elucidate the correlations between subtle structural distortion and oxidation states; treat localized charge carriers; describe defect/ion transport in the presence of electric field; and, in turn, greatly advance the current understanding of microstructural evolution in complex oxides under applied bias. The fundamental knowledge gained from this work will enable precise control over hierarchical defect structures and unravel new routes to manipulate resistance states in complex oxides. This, in turn, will accelerate design of novel devices with desired set of neural functionalities, and high-speed densely-scaled resistive random access memory technologies.

36 MATERIALS SCIENCE↗

Novel Superionic Na Conductors for Solid‐State Na batteries: Materials and Interface

This project aims to advance the fundamental understanding on how the cation or anion doping influence on the crystal structure, phase stability and ion transport of novel Na superionic conductors. Specifically, we focus on the Na 3-x A x SbS 4-y X y family solid electrolytes (A: cation dopant, X: anion dopant), a class of promising materials for all-solid-state sodium batteries owing to their high ionic conductivity and compositional tunability. By integrating materials synthesis, neutron scattering, and electrochemical characterization and theoretical simulations, this project sees to elucidate 1) how does the synthesis approaches (solid-state reaction, low-temperature reaction) on the phase purity and doping process; 2) how chemical doping (A: cation dopants such as Sn; X: anion dopants such as Se, F) modulate lattice dynamics and Na+ migration as well as interface stability toward Na metal. Specifically, this project’s proposed technology involves three objectives: (1) synthesize novel Na-ion conductors (anion or cation doped Na 3 SbS 4 ) with high phase purity and examine their structural features (e.g., phase stability); (2) understand Na-ion conductive properties of new Na-ion conductors through a combination of experimental characterizations and theoretical simulations; (3) investigate the interface stability of novel Na superionic conductors with electrode materials in solid-state Na batteries. These objectives will be achieved through combined experimental synthesis/characterizations and computational approaches. The obtained knowledge will provide a comprehensive synthesis-structure-property correlation, enabling the rational design of novel solid-state conductors with excellent conductivity and stability.

25 ENERGY STORAGE↗

Structural evolution and magnetic hardness of (Sm,Zr)(Fe,Co,Ti) 12 alloy particles via reduction-diffusion

The quest for achieving high coercivity in Sm(Fe,Co,Ti) 12 alloys, despite their inherent strong magnetocrystalline anisotropy, has posed significant challenges. Recently, (Sm,Zr)(Fe,Co,Ti) 12 monocrystalline particles have exhibited coercivity μ 0 H c > 1.2 T, showcasing promising prospects and significant potential for both manufacturing and research endeavors. This study delves into the structural evolution of (Sm,Zr)(Fe,Co,Ti) 12 (1:12) alloy particles made via the calciothermic reduction-diffusion synthesis process as influenced by the molar ratios of Ca atoms to O 2- ions (Ca/O), annealing time and annealing temperature. Critical insight that informs conditions to optimize the magnetic response is gained via systematic experimentation and advanced electron microscopy. Complex structural features, including core-shell morphologies and intricate multiphase compositions within individual particles, are unveiled. An optimal Ca/O ratio of 1.30 produces particles with a coercivity up to μ 0 H c = 1.63 T, while higher Ca/O ratios induce the formation of a Sm-rich TbCu 7 -type (1: 7 ) phase, which only partially transforms into the desired 1:12 phase during annealing. Persistent remnants of the 1:7 phase locally impact atomic structure, particle morphology, and coercivity. Furthermore, these findings underscore the complex interplay between synthesis parameters, resulting structures, and magnetic properties, informing the design and optimization of high-performance permanent magnets comprised of the (1:12) compound.

36 MATERIALS SCIENCE↗

Decoupling Li out-diffusion and surface diffusion in the lithiation-assisted epitaxial growth of lithium tungstate

Lithiation-assisted epitaxy offers a flexible and robust approach for synthesizing high-quality Li-containing materials and interfaces with precise control. Here, in this study, we use lithium tungstate (Li x WO 3+x/2 , where x = 0 to 2) as a model system to investigate the intertwined effects of Li out-diffusion-induced compositional changes and surface-diffusion-induced morphological changes. By systematically varying synthesis and processing conditions, we uncover their impact on lithium tungstate film formation. Comprehensive characterizations, including X-ray diffraction, atomic force microscopy, X-ray photoemission spectroscopy and time-of-flight secondary ion mass spectrometry, reveal that low-temperature growth (< 300 °C) followed by high-temperature annealing yields continuous lithium tungstate films with significantly reduced surface roughness. In contrast, high-temperature deposition (≥ 300 °C) accelerates surface diffusion and Li out-diffusion, leading to island formation. Furthermore, in situ scanning transmission electron microscopy demonstrates the beam sensitivity of Li 2 WO 4 and reveals a phase transition from Li 2 WO 4 to LiWO 3.5 under prolonged electron beam exposure. These findings deepen our understanding of how to control composition and morphology of Li-containing films, providing valuable insights for the design and integration of energy materials.

Shi, Jueli [Pacific Northwest National Laboratory ↗

Lead-Free Cs 4 CuSb 2 Cl 12 Layered Double Perovskite Nanocrystals

Concerns about the toxicity of lead-based perovskites have aroused great interest for the development of alternative lead-free perovskite-type materials. Recently, theoretical calculations predict that Pb 2+ cations can be substituted by a combination of Cu 2+ and Sb 3+ cations to form a vacancy-ordered layered double perovskite structure with superior optoelectronic properties. However, accessibilities to this class of perovskite-type materials remain inadequate, hindering their practical implementations in various applications. Here, we report the first colloidal synthesis of Cs 4 CuSb 2 Cl 12 perovskite-type nanocrystals (NCs). The resulting NCs exhibit a layered double perovskite structure with ordered vacancies and a direct bandgap of 1.79 eV. A composition-structure-property relationship has been established by investigating a series of Cs 4 Cu x Ag 2-2x Sb 2 Cl 12 perovskite-type NCs (0 ≤ x ≤ 1). The composition-induced crystal structure transformation, thus the electronic bandgap evolution has been explored by experimental observations and further confirmed by theoretical calculations. Taking advantages of both the unique electronic structure and solution processability, we demonstrate that the Cs 4 CuSb 2 Cl 12 NCs can be solution-processed as high-speed photodetectors with ultrafast photo-response and narrow bandwidth. We anticipate that our study will prompt future research to design and fabricate novel and high-performance lead-free perovskite-type NCs for a range of applications.

25 ENERGY STORAGE↗

High-entropy 1D halide perovskite piezoelectrics found by megalibrary synthesis and rapid nonlinear optical screening

Piezoelectric molecular crystals offer excellent compositional and structural tunability and sustainable processability. However, their discovery is slow, primarily due to the serial synthesis and screening processes used. Here, we report an approach that combines massively parallel megalibrary synthesis with scanning second harmonic generation (SHG) microscopy for rapid screening of piezoelectric molecular crystals. Megalibraries consisting of more than 1,000,000 compositionally distinct but positionally encoded TMCM x TMA (1–x) Cd y Pb (1–y) ClzBr (3–z) (TMCM: trimethylchloromethylammonium, TMA: tetramethylammonium; 0 ≤ x ≤ 1, 0 ≤ y ≤ 1, 0 ≤ z ≤ 3) nanocrystals were synthesized. The megalibraries were rapidly screened by SHG microscopy to identify notable noncentrosymmetric structures, which were then tested for piezoelectricity, facilitating discovery of a high-entropy noncentrosymmetric material with a large d 33 (TMCM 0.75 TMA 0.25 Cd 0.75 Pb 0.25 Cl 1.5 Br 1.5 , 42.8 picocoulombs per newton). Furthermore, this approach enabled systematic investigation of the Curie temperature (T C )–composition relationship in the TMCMCdCl z Br (3–z) system, facilitating reverse design of materials with targeted T C . Our work establishes a powerful approach to accelerate the discovery and design of unusual piezoelectrics for next-generation electronics and optics.

Li, Jun [Northwestern University, Evanston, IL (Un↗

An ultrastable heterostructured oxide catalyst based on high-entropy materials: A new strategy toward catalyst stabilization via synergistic interfacial interaction

Designing high–performance catalysts that can stabilize catalytic active sites against sintering to deactivation at temperature higher than 900°C is significant but challenging. In this work, we report a new strategy to obtain a transition metal oxide catalyst with high temperature stability for CO oxidation. This is achieved through a synergistic interfacial interaction at the interface of a heterostructure between high– entropy oxides (HEO, high temperature stability) and CuCeO x (catalytic site). The catalytic site (CuCeO x ) for CO oxidation is realized by dissolving an amount of Cu species in HEO into CeO 2 via an entropy–driven mechanochemical process. In situ XRD and HAADF–STEM have confirmed the high temperature stability of the heterostructure CuCeO x –HEO, which can remain its CO oxidation catalytic activity at elevated temperatures. It should be expected that this innovative will offer the potential to the synthesis of catalysts with high temperature stability in industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scale-free, programmable design of morphable chain loops of kilobots and colloidal motors

Micron-scale robots require systems that can morph into arbitrary target configurations controlled by external agents such as heat, light, electricity, and chemical environment. Achieving this behavior using conventional approaches is challenging because the available materials at these scales are not programmable like their macroscopic counterparts. To overcome this challenge, we propose a design strategy to make a robotic machine that is both programmable and compatible with colloidal-scale physics. Our strategy uses motors in the form of active colloidal particles that constantly propel forward. We sequence these motors end-to-end in a closed chain forming a two-dimensional loop that folds under its mechanical constraints. We encode the target loop shape and its motion by regulating six design parameters, each scale-invariant and achievable at the colloidal scale. We demonstrate the plausibility of our design strategy using centimeter-scale robots called kilobots . We use Brownian dynamics simulation to explore the large design space beyond that possible with kilobots, and present an analytical theory to aid the design process. Multiple loops can also be fused together to achieve several complex shapes and robotic behaviors, demonstrated by folding a letter shape “M,” a dynamic gripper , and a dynamic pacman . The material-agnostic, scale-free, and programmable nature of our design enables building a variety of reconfigurable and autonomous robots at both colloidal scales and macroscales.

36 MATERIALS SCIENCE↗

Reference Piping and Instrumentation Diagrams for Heat Transport Systems for Methanol Plants

This report aims to bridge the gap between advanced nuclear reactor vendors and methanol producers seeking decarbonization. It equips both parties with tools and preliminary information for integrating clean heat from advanced reactors into novel methanol production processes. The proposed investigation in this report involves a three-step approach: 1. Design of Current and Decarbonized Process Models for Methanol Production. This report initiates process modeling of two novel methanol production pathways, with their overall energy requirements comparative to classical methanol production (see Figure ES1). The two process models provide the foundation for analyzing integration of hermos-electric generation from advanced nuclear reactors. 2. Identification of Coupling Points to Integrate Advanced Reactors. This report investigates the integration with two advanced reactor technologies: light-water reactors (LWRs) and high-temperature gas reactors (HTGRs). The key coupling points between advanced nuclear reactors and the production facilities associated with the two decarbonized methanol process pathways are identified. 3. Preliminary Heat and Electricity Transfer Design from Reactors to Methanol Production Sites. The preliminary designs for piping and instrumentation to transfer heat from the boundary of advanced reactor technology location to the boundary of methanol production site are evaluated within the context of decarbonized pathways. The pipe analysis for heat transfer adheres to relevant codes and specifications from American Society of Mechanical Engineering. A simplified design for transmission of electricity to the industrial site has been provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analysis of neptunium oxides produced through modified direct denitration

Production of neptunium-237 ( 237 Np) target materials for plutonium-238 ( 238 Pu) radioisotope thermoelectric generators (RTGs) for deep space exploration requires advanced chemistry and engineering development. Currently, the domestic Pu-238 Supply Program at Oak Ridge National Laboratory produces neptunium dioxide (NpO 2 ) for target material using a modified direct denitration (MDD) flowsheet. Although the chemistry, reaction mechanisms, and product characteristics of MDD are well understood for uranium, corresponding studies of the neptunium system are still needed to continue optimization of target material properties, production equipment design, and production flowsheets. Here, the objective of this work is to characterize crystalline phases, morphology, surface texture, and particle size of NpO 2 produced via MDD reactions. Solid-phase characterization techniques, including powder X-ray diffraction (pXRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), were employed to achieve this objective. Subsequent data processing using the Morphological Analysis for Material Attribution (MAMA) software was performed to analyze particle morphology and size. Broadly, the powders were found to contain a mixture of NpO 2 and Np 2 O 5 after denitration with a variety of morphologies. After high-firing, the product was found to be NpO 2 with a typical polycrystalline oxide morphology and a grain size ranging from 0.72 to 0.94 µm. These analyses provide knowledge on the reaction pathway for a non-traditional NpO 2 synthesis method and offer additional unique insight into production-scale environments for transuranic materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Synthesis of High Surface Area VS2 for Nitrogen Reduction

Ammonia synthesis from dinitrogen provides a critical chemical feedstock to agriculture worldwide. The dominant process for ammonia synthesis is the Haber-Bosch process, which is fossil-fuel dependent and energy intensive. The electrochemical nitrogen reduction reaction (NRR) could provide a more environmentally friendly route to industrial ammonia synthesis. We have worked to realize electrochemical NRR by developing transition metal dichalcogenide NRR catalysts. In the first part of this presentation, a VS2-based NRR electrocatalyst, which has shown promising activity and selectivity, will be presented. The synthesis of this VS2-based catalyst is straightforward and results in few-layer VS2 or VSx, (x < 2) nanoflakes. Additionally, the proposed mechanism of NRR on VS2 will be discussed, and we will discuss DFT simulation of NRR on VS2 and MoS2 as well as planned in-situ Raman experiments to probe this mechanism. In the second part of this presentation, we will share several lessons learned during our early NRR research including important points of electrochemical cell design and experimental controls to reduce environmental ammonia contamination of experiments. Finally, we will address areas of opportunity for electrochemical NRR.

dichalcogenide↗

Elucidating the role of surface species in CO oxidation catalyzed by boron nitride nanotube supported transition metal oxides

Boron nitride nanotube (BNNT) is considered a highly promising catalyst support due to its outstanding thermal stability and chemical inertness. These characteristics make BNNT an attractive alternative for high-temperature applications. However, most studies to date have focused on incorporating platinum group metals (PGMs) to achieve high activity. Although BNNT-supported PGM catalysts are highly effective, their scarcity and high cost hinder widespread use in industrial processes. In this study, BNNT-supported transition metal oxides (TMO x /BNNT; TM = Fe, Co, Ni, and Cu) catalysts were investigated, and CO oxidation was applied as a model reaction to evaluate their catalytic performance. Several characterization techniques, including SEM-EDX, TEM, SXRD, H 2 -TPR, and XPS, were employed to examine their physicochemical properties. Notably, the particle size of the metal oxides differed significantly depending on the metal type. This variation is primarily attributed to the inherent metal–support interactions and the thermodynamic stability of each oxide during synthesis. These properties also affected catalytic activity, and various parameters, such as oxygen mobility and redox behavior, played important roles in determining performance. Finally, in situ DRIFTS, CO-TPSR, reaction-order analysis, and 18 O 2 isotope-labeling experiment were used to investigate the reaction mechanism. In conclusion, the findings provide insights into the design of cost-effective BNNT-supported catalysts and highlight their potential applicability in oxidation reactions.

36 MATERIALS SCIENCE↗

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. Here, the performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This article describes a novel fully data-driven probabilistic framework to derive a linear representation of postcontingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synthesis, Characterization, and Utilization of a Lignin-Based Adsorbent for Effective Removal of Azo Dye from Aqueous Solution

How to effectively remove toxic dyes from the industrial wastewater using a green low-cost lignocellulose-based adsorbent, such as lignin, has become a topic of great interest but remains quite challenging. In this study, cosolvent-enhanced lignocellulosic fractionation (CELF) pretreatment and Mannich reaction were combined to generate an aminated CELF lignin which is subsequently applied for removal of methylene blue and direct blue (DB) 1 dye from aqueous solution. 31P NMR was used to track the degree of amination, and an orthogonal design was applied to determine the relationship between the extent of amination and reaction parameters. The physicochemical, morphological, and thermal properties of the aminated CELF lignin were characterized to confirm the successful grafting of diethylenetriamine onto the lignin. The aminated CELF lignin proved to be an effective azo dye-adsorbent, demonstrating considerably enhanced dye decolorization, especially toward DB 1 dye (>90%). It had a maximum adsorption capacity of DB 1 dye of 502.7 mg/g, and the kinetic study suggested the adsorption process conformed to a pseudo-second-order kinetic model. The isotherm results also showed that the modified lignin-based adsorbent exhibited monolayer adsorption. The adsorbent properties were mainly attributed to the incorporated amine functionalities as well as the increased specific surface area of the aminated CELF lignin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phenylene-linked tetrapyrrole arrays containing free base and diverse metal chelate forms – Versatile synthetic architectures for catalysis and artificial photosynthesis

Tetrapyrrole macrocycles are central to photosynthesis yet a single macrocycle does not carry out photosynthesis; rather, assemblies of tetrapyrrole macrocycles work in concert in antenna complexes, reaction centers, and electron-transport chains to harvest sunlight, funnel excited-state energy and separate charge for biological use. A longstanding theme in artificial photosynthesis has been to construct covalently linked “arrays” of metalated and free base tetrapyrrole macrocycles for fundamental studies of such processes, which entail excited-state and ground-state interactions. Among linkers in arrays chemistry, the 1,2-, 1,3-, or 1,4-disubstituted phenylene unit has proved very attractive owing to the resulting short distance, defined architecture, and appropriate extent of electronic coupling of adjacent macrocycles to give rapid electron and/or energy transfer while largely retaining desired spectral features. Eight distinct strategies to construct phenylene-linked tetrapyrrole arrays are identified in a review with comprehensive coverage since inception in the early 1970s through mid-year 2021. The arrays predominantly incorporate porphyrins with very few chlorins and bacteriochlorins, reflecting historic availability of synthetic methods for macrocycle formation. Of the eight strategies, only two appear applicable to (bacterio)chlorins. While studies in artificial photosynthesis have largely fueled this field, applications in catalysis have also been examined. Altogether >400 arrays are covered. The review delves into synthesis and molecular design, sketches photophysical properties, and suggests unrealized opportunities in arrays chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparative Assessment of U-Net-Based Deep Learning Models for Segmenting Microfractures and Pore Spaces in Digital Rocks

Segmentation of high-resolution X-ray microcomputed tomography (µCT) images is crucial in digital rock physics (DRP), affecting the characterization and analysis of microscale phenomena in the porous media. The complexity of geological structures and nonideal scanning conditions pose significant challenges to conventional image segmentation approaches. Motivated by the recent increasing popularity of deep learning (DL) techniques in image processing, this work undertakes a comparative study of DL models, specifically U-Net and its variants, for segmenting multiple targets with distinguished features in digital rocks, including discrete fracture networks (DFNs), pore spaces, and solid rock. Particularly, DFNs have a smaller volumetric fraction over others, bringing in a substantial challenge of imbalanced segmentation. The primary focus is to evaluate the architecture and feature enhancement strategies of various DL models, including U-Net, attention U-Net, residual U-Net, U-Net++, and residual U-Net++. The models were designed as 2.5D, utilizing a central 2D image and its two adjacent upper and lower 2D images as input to provide a pseudo-3D context. In addition, because the ground truth of segmentation was unknown for real-world digital rocks, we created a benchmark data set following the inverse operations of segmentation. The data synthesis started from the label images (i.e., solid rock, pore spaces, and DFNs), followed by simulating partial volume blurring, adding random background noise, and introducing ring artifacts to mimic real raw X-ray µCT images. The data set, which included various rock types (i.e., sandstone and artificial data), scanning resolution, and magnitudes of noise and artifacts, was divided into training and testing data sets with a 90% and 10% ratio, respectively. Moreover, in addition to the conventional pixel-wise evaluation metrics, the physics-based metric of the lattice-Boltzmann method (LBM) simulated permeability provided more comprehensive assessments. The results demonstrated that the residual connections, nested architectures, and redesigned skip connections contribute to the model performance and give the residual U-Net++ the highest accuracy. The improvements were mainly on the boundaries and small targets, especially the DFNs, which dominate the interconnectivity and therefore affect the permeability greatly. This study also rigorously evaluated the efficiency and generalization of each model, demonstrating that the sophisticated architectures achieved excellent practicability and maintained robust performance on completely unseen data, ensuring their suitability for diverse and challenging DRP applications.

58 GEOSCIENCES↗