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At least 1,711 records · Page 95

The Triple Catalytic Action of Tertiary Nitrogen Catalysts in Recyclable Epoxy-Anhydride Thermosets

The thermosetting polymer matrix in fiber reinforced composites is an important component for energy related applications, such as the lightweighting of vehicles or their use in wind and waterpower turbine blades, due to their ability to provide superior adhesion, stiffness, and applicability to a wide range of manufacturing processes. Despite these benefits, today's thermosets are widely considered to be unrecyclable; thus, there is a large interest in redesigning these materials to be inherently recyclable so that energy intensive production of fibers and monomers can be circumvented, bolstering composite manufacture supply chains. Polyester covalent adaptable networks (PECANs) are one such promising alternative to the incumbent, nonrecyclable epoxy-amine thermosets. PECANs can be formed from the ring-opening co-polymerization (ROCOP) of epoxy-anhydride monomer mixtures and subsequent curing at mild temperatures to exhibit similar performance to conventional epoxies while also possessing unique dynamic chemistries along the ester-hydroxyl backbone that are capable of transesterification and thus reprocessability. While significant advancements have been made in formulating these materials for improved mechanical properties or optimizing solvolysis and reprocessing strategies, less attention has been placed on the impact of the residing amine catalyst used to generate the polyester network. In this work, we evaluated the triple-catalytic efficacy of 12 tertiary amines that act as a curing (bulk ROCOP), a transesterification (internal bond exchange), and a deconstruction (methanolysis) catalyst for PECAN thermosets. Specifically, we first distinguish between chain-growth and step-growth polymerization mechanisms for epoxy-amine and epoxy-anhydride mechanisms. We also utilized density functional theory (DFT) to estimate the basicity (pKb) of each catalyst. Of the tested catalysts, the ROCOP of the studied PECAN network can be completed between 95 and 247 min (at 80 degrees C), with variable gelation phenomena. Additionally, the stress relaxation (transesterification metric) efficiency of the tested PECAN networks with alternative embedded catalysts ranged from 95% to 15% reduction in stress after 5 h at 200 degrees C, and the depolymerization efficacy ranged from 2.5% to 9.8% deconstruction after 36 h at 130 degrees C. Overall, the nitrogen-based moieties were demonstrated to influence polymerization kinetics, catalyze the dynamic transesterification exchange mechanism, and aid in the solvolysis of the thermosets at end-of-life.

36 MATERIALS SCIENCE↗

Exploring the Photogenerated Charge Transfer Mechanism in Cu 2 O@MoS 2 Heterojunction Photocatalyst Using Transient Absorption Spectroscopy

Both heterojunction and core–shell photocatalysts have demonstrated promising performance in photocatalytic CO 2 conversions to fuels. However, fundamental knowledge of heterojunctions in core–shell structures is highly desired to facilitate the design of future photocatalysts. By combining advanced experimental characterizations and density functional theory (DFT) calculations, the role of the Cu 2 O@MoS 2 heterojunction in photocatalytic CO 2 conversions to fuels was investigated. We discovered that the charge dynamics and electron transfer properties of Cu2O@MoS 2 photocatalysts are altered by the heterojunction and Cu 2 O underlayer due to the electron transfer from Cu 2 O to MoS 2 and the change in CO 2 adsorption strength on the hybrid catalyst surface. Consequently, more electrons can travel to the surrounding liquid environment to be consumed by CO 2 reduction. This study provides experimental and theoretical investigations of the fundamental mechanisms of heterojunction core–shell photocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photodepositing CdS on the Active Cyano Groups Decorated g‐C 3 N 4 in Z‐Scheme Manner Promotes Visible‐Light‐Driven Hydrogen Evolution

Abstract g‐C 3 N 4 /CdS heterojunctions are potential photocatalysts for hydrogen production but their traditional type‐II configuration generally leads to weak oxidative and reductive activity. How to construct the novel Z‐scheme g‐C 3 N 4 /CdS counterparts to address this issue remains a great challenge in this field. In this work, a new direct Z‐scheme heterojunction of defective g‐C 3 N 4 /CdS is designed by introducing cyano groups (NC‐) as the active bridge sites. Experimental observations in combination with density functional theory (DFT) calculations reveal that the unique electron‐withdrawing feature of cyano groups in the defective g‐C 3 N 4 /CdS heterostructure can endow this photocatalyst with numerous advantageous properties including high light absorption ability, strong redox performance, satisfactory charge separation efficiency, and long lifetime of charge carriers. Consequently, the resultant photocatalytic system exhibits more active performance than CdS and g‐C 3 N 4 under visible light and reaches an excellent hydrogen evolution rate of 1809.07 µmol h −1 g −1 , which is 6.09 times higher than pristine g‐C 3 N 4 . Moreover, the defective g‐C 3 N 4 /CdS photocatalyst maintains good stability after 40 h continuous test. This work provides new insights into design and construction of Z‐scheme heterojunctions for regulating the visible‐light‐induced photocatalytic activity for H 2 evolution.

Wang, Zhipeng↗

Spatial Control of Substitutional Dopants in Hexagonal Monolayer WS 2 : The Effect of Edge Termination

The ability to control the density and spatial distribution of substitutional dopants in semiconductors is crucial for achieving desired physicochemical properties. Substitutional doping with adjustable doping levels has been previously demonstrated in 2D transition metal dichalcogenides (TMDs); however, the spatial control of dopant distribution remains an open field. In this work, edge termination is demonstrated as an important characteristic of 2D TMD monocrystals that affects the distribution of substitutional dopants. Particularly, in chemical vapor deposition (CVD)-grown monolayer WS 2 , it is found that a higher density of transition metal dopants is always incorporated in sulfur-terminated domains when compared to tungsten-terminated domains. Here two representative examples demonstrate this spatial distribution control, including hexagonal iron- and vanadium-doped WS 2 monolayers. Density functional theory (DFT) calculations are further performed, indicating that the edge-dependent dopant distribution is due to a strong binding of tungsten atoms at tungsten-zigzag edges, resulting in the formation of open sites at sulfur-zigzag edges that enable preferential dopant incorporation. Based on these results, it is envisioned that edge termination in crystalline TMD monolayers can be utilized as a novel and effective knob for engineering the spatial distribution of substitutional dopants, leading to in-plane hetero-/multi-junctions that display fascinating electronic, optoelectronic, and magnetic properties.

2D transition metal dichalcogenides↗

Boosting Electrochemical Catalysis and Nonenzymatic Sensing Toward Glucose by Single‐Atom Pt Supported on Cu@CuO Core–Shell Nanowires

Abstract It is critical to develop high‐performance electrocatalyst for electrochemical nonenzymatic glucose sensing. In this work, a single‐atom Pt supported on Cu@CuO core–shell nanowires (Pt 1 /Cu@CuO NWs) for electrochemical nonenzymatic glucose sensor is designed. Pt 1 /Cu@CuO NWs exhibit excellent electrocatalytic oxidation toward glucose with 70 mV lower onset potential (0.131 V) and 2.4 times higher response current than Cu NWs. Sensors fabricated using Pt 1 /Cu@CuO NWs also show high sensitivity (852.163 µA mM −1 cm −2 ), low detection limit (3.6 µM), wide linear range (0.01–5.18 µM), excellent selectivity, and great long‐term stability. The outstanding sensing performance of Pt 1 /Cu@CuO NWs, investigated by experiments and density functional theory (DFT) calculations, is attributed to the synergistic effect between Pt single atoms and Cu@CuO core–shell nanowires that generates strong binding energy of glucose on the nanowires. The work provides a new pathway for exploring highly active SACs for electrochemical nonenzymatic glucose sensor.

Chemistry↗

Atomically Dispersed Silver Atoms Embedded in NiCo Layer Double Hydroxide Boost Oxygen Evolution Reaction

Abstract Bimetallic layered double hydroxides (LDHs) are promising catalysts for anodic oxygen evolution reaction (OER) in alkaline media. Despite good stability, NiCo LDH displays an unsatisfactory OER activity relative to the most robust NiFe LDH and CoFe LDH. Herein, a novel NiCo LDH electrocatalyst modified with single‐atom silver grown on carbon cloth (Ag SA ‐NiCo LDH/CC) that exhibits exceptional OER activity and stability in 1.0 m KOH is reported. The Ag SA ‐NiCo LDH/CC catalyst only requires a low overpotential of 192 mV to reach a current density of 10 mA cm −2 , obviously boosting the OER activity of NiCo LDH/CC (410 mV@10 mA cm −2 ). Inspiringly, Ag SA ‐NiCo LDH/CC can maintain its high activity for up to 500 h at a large current density of 100 mA cm −2 , exceeding most single‐atom OER catalysts. In situ Raman spectroscopy studies uncover that the in situ formed NiCoOOH during OER is the real active species. Hard X‐ray absorption spectrum (XAS) and density functional theory (DFT) calculations validate that single‐atom Ag occupying Ni site increases the chemical valence of Ni elements, and then weakens the adsorption of oxygen‐contained intermediates on Ni sites, fundamentally accounting for the enhanced OER performance.

Chemistry↗

Tuning Local Atomic Structures in MoS 2 Based Catalysts for Electrochemical Nitrate Reduction

In recent years, there has been a substantial surge in the investigation of transition-metal dichalcogenides such as MoS 2 as a promising electrochemical catalyst. Inspired by denitrification enzymes such as nitrate reductase and nitrite reductase, the electrochemical nitrate reduction catalyzed by MoS 2 with varying local atomic structures is reported. Further, it is demonstrated that the hydrothermally synthesized MoS 2 containing sulfur vacancies behaves as promising catalysts for electrochemical denitrification. With copper doping at less than 9% atomic ratio, the selectivity of denitrification to dinitrogen in the products can be effectively improved. X-ray absorption characterizations suggest that two sulfur vacancies are associated with one copper dopant in the MoS 2 skeleton. DFT calculation confirms that copper dopants replace three adjacent Mo atoms to form a trigonal defect-enriched region, introducing an exposed Mo reaction center that coordinates with Cu atom to increase N 2 selectivity. Apart from the higher activity and selectivity, the Cu-doped MoS 2 also demonstrates remarkably improved tolerance toward oxygen poisoning at high oxygen concentration. Finally, Cu-doped MoS 2 based catalysts exhibit very low specific energy consumption during the electrochemical denitrification process, paving the way for potential scale-up operations.

36 MATERIALS SCIENCE↗

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗

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↗

Single-Particle Insights Into the Electronic Structure and Enhanced Stability of CsPbBr 3 /FAPbBr 3 Core/Crown Nanoplatelets at the Nanometer Scale

Colloidal perovskite nanoplatelets (NPLs), despite their exceptional optoelectronic properties, face significant challenges due to their intrinsic instability and trap-assisted non-radiative recombination. Although many studies employing surface engineering, such as selecting ligands or coating to passivate defects, have demonstrated improved optoelectronic properties, these enhancements are typically inferred from bulk-ensemble measurements; the effects at the single-particle level remain elusive. Here, we conduct single-particle-level studies using scanning tunneling spectroscopy (STS) on a unique core–crown system, CsPbBr 3 @FAPbBr 3 NPLs, where the lateral surfaces of the CsPbBr 3 core are coated with an FAPbBr 3 crown. Experimental density-of-states (DOS) analysis reveals a 47% reduction in deep-trap states in core-crown NPLs compared to core-only NPLs, consistent with nearly two-fold enhancements in photoluminescence quantum yields. Progressive I–V sweep measurements demonstrate superior electrical stability in core-crown NPLs, preserving band structure with minimal degradation, while core-only NPLs exhibit rapid bandgap shrinkage and trap formation. Density functional theory (DFT) calculations indicate that FA incorporation distorts Pb octahedral lattice, widening the bandgap. This study elucidates how surface engineering modulates charge localization, passivates defects, and enhances stability at the single-particle level. Moreover, by uncovering bias-induced trap states in single unpassivated NPLs, this study establishes a precise, robust approach for characterizing emerging perovskite nanocrystals.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Hydroxyl radical‐driven transformations of bisphenol A and 2,4‐dinitroanisole: Experimental and computational analysis

Abstract This study used experimental and computational analysis to investigate the advanced oxidation of bisphenol A (BPA) and 2,4‐dinitroanisole (DNAN). The pseudo first‐order reaction rate constants depended on the molar peroxide ratio and were between 0.13 and 0.28 min −1 for BPA and between 0.018 and 0.032 min −1 for DNAN. The kinetic differences appear to be due in part to the energy requirements for oxidation, which depended on the reaction mechanism but were typically lower for BPA than they were for DNAN. Density functional theory (DFT) was used to develop transformation pathways that included experimentally‐detected byproducts. The most energetically favored pathway for BPA oxidation begins with the formation of hydroxylated derivatives, while for DNAN, the most energetically favorable degradation pathway begins with the substitution of the methoxy group. Overall, these findings demonstrate the power of combining experimental and computational tools to reveal transformation mechanisms during water treatment. Practitioner Points Advanced oxidation transformations for two emerging water pollutants, bisphenol A and dinitroanisole, was investigated. The observed reaction kinetics depended on molar peroxide ratio in a manner that is in keeping with previous findings. Density functional theory‐based analysis revealed reaction energy requirements and degradation pathways.

Engineering↗

The Crystal Structure of BaZn 2 Se 2 (OH) 2 Featuring Brownmillerite‐Type Layers

Abstract A bimetallic hydroxychalcogenide, BaZn 2 Se 2 (OH) 2 , was synthesized through hydrothermal pouch methods. The single crystal X‐ray diffraction and electron diffraction indicates that the phase crystallizes in the orthorhombic space group Pnma and is composed of anionic layers [ZnSe 3/3 (OH) 1/1 ] − that are separated and charged balanced by Ba 2+ cations. The [ZnSe 3/3 (OH) 1/1 ] – layer comprises two unique Zn sites, which form interpenetrating zigzag chains with an in‐plane dipole moment and adopts a brownmillerite‐type structural motif. The adjacent layers contain tetrahedrally coordinated Zn chains of opposite handedness related by an inversion center, which cancel the microscopic dipoles to minimize the macroscopic electric polarization. The adoption of a brownmillerite structural motif in BaZn 2 Se 2 (OH) 2 can be rationalized by the distinct charge difference between Se 2− and OH − anions, which creates a sufficient dipole moment in the ZnSe 3 (OH) tetrahedra to allow the occurrence of twisted chains. FTIR spectroscopy confirms the existence of OH − anions and DFT calculations indicate that BaZn 2 Se 2 (OH) 2 is a semiconductor with a direct band gap. This work expands the chemistry of the brownmillerite family from traditional homoanionic oxides to multianion hydroxychalcogenides, offering a new opportunity to explore tunable structural complexity for better design of functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interstitial Atoms and the Frustrated and Allowed Structural Transitions Principle: Tunability in the Electronic Structure of AuCu 3 ‐type Frameworks in Dy 4 T 1− x Ga 12 (T = Ag, Ir)

In this Article, we explore how the chemical pressure (CP) features of an intermetallic phase may provide opportunities to couple perturbations in electron count with the stabilization of the underlying geometrical structure. AuCu 3 ‐type LnGa 3 (Ln = lanthanide or group 3 metal) phases contain octahedral cavities of negative CP held open by overly compressed Ln–Ga interactions, leading to a series of transition metal‐stuffed derivatives. We present new additions to this family with the synthesis and crystal structures of Dy 4 T 1−x Ga 12 with (T, x) = (Ag, 0.29) and (Ir, 0.15), adopting Y 4 PdGa 12 ‐type superstructures of the AuCu 3 ‐type. density functional Ttheory (DFT)‐CP calculations, when adjusted to avoid dipolar CP features, affirm that T atom incorporation provides a mechanism for the relief of packing tensions, while electronic density of states distributions illustrate that the T atoms serve largely as electron or hole donors to the band structure, as needed for them to attain d 10 configurations. The maximum obtainable value for x may be limited by a mismatch between the Fermi energy and pseudogap, in line with the balance of factors envisioned by the frustrated and allowed structural transitions principle. Furthermore, trends in resistivity measurements on T = Ir, Pd, and Ag compounds are interpretable in terms of the varying degrees of disorder arising from x < 1.0.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗

Mechanistic insights into the pyrolysis of poly (vinyl chloride)

The accumulation of unmanaged plastic waste in the environment has a devastating impact upon marine life and human health. Catalytic and thermal pyrolysis are promising technologies toward the efficient utilization of plastic waste. Yet, the processing of polymers, such as polyvinyl chloride (PVC), that decompose into corrosive compounds remains a major challenge. In this work, we employ density functional theory (DFT) and thermogravimetric analysis (TGA) to explore the elementary chemical steps that underpin the thermal decomposition of PVC. We determine that the dehydrochlorination reaction (i.e., 1 st stage of thermal decomposition) begins in tertiary chloride defects and propagates via HCl–mediated autocatalysis of internal allylic (IA) chloride groups. The latter groups, when in the vicinity of π–conjugated polymer segments, release HCl in a facile manner. We predict that other compounds, including hydrogen halides and H 2 O could also catalyze PVC’s dehydrochlorination. We suggest that hydrogen halides are the most efficient catalysts for this process, while other compounds like H 2 O may slow down the dehydrochlorination compared to purely HCl-catalyzed process, because of the dilution of the produced HCl. This result is corroborated by TGA experiments. Additionally, we study the thermochemistry and kinetics of polyene chain crosslinking and the formation of aromatics. The former reaction proceeds in parallel with the dehydrochlorination process (i.e., during the 1st stage of thermal decomposition), whilst the latter may occur at high temperatures (i.e., during the 2 nd stage of thermal decomposition). Furthermore, this work contributes to the fundamental understanding of molecular scale phenomena that take place during PVC pyrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structurally Driven Environmental Degradation of Friction in MoS2 Films

Abstract We report an investigation of the friction mechanisms of MoS 2 thin films under changing environments and contact conditions using a variety of computational and experimental techniques. Molecular dynamics simulations were used to study the effects of water and molecular oxygen on friction and bonding of MoS 2 lamellae during initial sliding. Characterization via photoelectron emission microscopy (PEEM) and Kelvin probe force microscopy (KPFM) were used to determine work function changes in shear modified material within the top few nanometers of MoS 2 wear scars. The work function was shown to change with contact conditions and environment, and shown by density functional theory (DFT) calculations and literature reports to be correlated with lamellae size and thickness of the basally oriented surface layer. Results from nanoscale simulations and macroscale experiments suggest that the evolution of the friction behavior of MoS 2 is linked primarily to the formation or inhibition of a basally oriented, molecularly thin surface film with long-range order.

Curry, John F.↗