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At least 1,369 records · Page 76

Aqueous TiO 2 Nanoparticles React by Proton-Coupled Electron Transfer

Redox reactions of aqueous colloidal TiO 2 4 nm nanoparticles (NPs) have been examined, including both citratecapped and uncapped NPs (c-TiO 2 and uc-TiO 2 ). Photoreduction gave stable blue colloidal c-TiO 2 R NPs with 10–60 electrons per particle. Equilibration of these reduced NPs with soluble redox reagents such as methylviologen (MV 2+ ) provided measurements of the colloid reduction potential as a function of pH. The potentials of c-TiO 2 from pH 2–9 varied linearly with pH, with a slope of –60 ± 5 mV/pH. Estimates of the potential at pH 12 were consistent with extrapolating that line to high pH. The reduction potentials did not correlate with the zeta potentials (ζ) or the surface charge of the NPs across this pH range. Similar reduction potentials were observed for c- and uc-TiO 2 at low pH even though they have quite different ζ potentials. These results show that the common surface-charging explanation of the pH dependence is not tenable in these systems. Oxidation of reduced c-TiO 2 R with the electron-transfer oxidant potassium triiodide (KI 3 ) occurred with a significant drop in pH, showing that protons were released when the electrons were removed from the NPs. Smaller pH drops were observed for the proton-coupled electron transfer (PCET) reagents O 2 (air) and 4-MeO-TEMPO (4-methoxy-2,2,6,6-tetramethylpiperine-1-oxy radical). The difference in the number of protons released with KI 3 vs O 2 and 4-MeO-TEMPO was roughly one proton per electron removed. Thus, the thermodynamically preferred reactivity of these colloidal TiO 2 NPs is PCET over the pH 2–13 range studied. The measured redox potentials refer to the chemical process TiO 2 + H + + e – → TiO 2 ·e – ,H + ; and therefore they do not correspond with an electronic energy such as a conduction band edge or flat band potential. The 1e – /1H + stoichiometry means that the TiO 2 reduction potentials correspond to a TiO 2 –H bond dissociation free energy (BDFE), determined to be 49 ± 2 kcal mol –1 . The PCET description is consistent with the pH dependence of E(TiO 2 /TiO 2 ·e – ,H + ), the release of protons upon oxidation, the lack of correlation with ζ potentials, the similarity of capped and uncapped NPs, and the small change in the potential and BDFE from the first to the last electron/proton pair (H atom) removed. Furthermore, this behavior is suggested to be the norm for redox-active oxide/water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular dipole moment learning via rotationally equivariant derivative kernels in molecular-orbital-based machine learning

This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree–Fock computations. A MOB pairwise decomposition of the correlation part of the dipole moment is applied, and these pair dipole moments could be further regressed as a universal function of MOs. The dipole MOB features consist of the energy MOB features and their responses to electric fields. An interpretable and rotationally equivariant derivative kernel for Gaussian process regression (GPR) is introduced to learn the dipole moment more efficiently. The proposed problem setup, feature design, and ML algorithm are shown to provide highly accurate models for both dipole moments and energies on water and 14 small molecules. To demonstrate the ability of MOB-ML to function as generalized density-matrix functionals for molecular dipole moments and energies of organic molecules, we further apply the proposed MOB-ML approach to train and test the molecules from the QM9 dataset. The application of local scalable GPR with Gaussian mixture model unsupervised clustering GPR scales up MOB-ML to a large-data regime while retaining the prediction accuracy. In addition, compared with the literature results, MOB-ML provides the best test mean absolute errors of 4.21 mD and 0.045 kcal/mol for dipole moment and energy models, respectively, when training on 110 000 QM9 molecules. The excellent transferability of the resulting QM9 models is also illustrated by the accurate predictions for four different series of peptides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

N-Doped Graphene (N-G)/MOF(ZIF-8)-Based/Derived Materials for Electrochemical Energy Applications: Synthesis, Characteristics, and Functionality

In recent years, graphene-type materials originating from metal–organic frameworks (MOFs) or integrated with MOFs have exhibited notable performances across various applications. However, a comprehensive understanding of these complex materials and their functionalities remains obscure. While some studies have reviewed graphene/MOF composites from different perspectives, due to their structural–functional intricacies, it is crucial to conduct more in-depth reviews focusing on specific sets of graphene/MOF composites designed for particular applications. In this review, we thoroughly investigate the syntheses, characteristics, and performances of N-G/MOF(ZIF-8)-based/derived materials employed in electrochemical energy conversion and storage systems. Special attention is given to realizing their fundamental functionalities. The discussions are divided into three segments based on the application of N-G/ZIF-8-based/derived materials as electrode materials for batteries, electrodes for electrochemical capacitors, and electrocatalysts. As electrodes for batteries, N-G/MOF(ZIF-8) materials can mitigate issues like an electrode volume expansion for Li-ion batteries and the ‘shuttle effect’ for Li-S batteries. As electrodes for electrochemical capacitors, these materials can considerably improve the ion transfer rate and electronic conductivity, thereby enhancing the specific capacitance while maintaining the structural stability. Also, it was observed that these materials could occasionally outperform standard platinum-based catalysts for the electrochemical oxygen reduction reaction (ORR). The reported electrochemical performances and structural parameters of these materials were carefully tabulated in uniform units and scales. Through a critical analysis of the present synthesis trends, characteristics, and functionalities of these materials, specific aspects were identified that required further exploration to fully utilize their inherent capabilities.

Electrochemistry↗

Tuning Active Site Flexibility by Defect Engineering of Graphene Ribbon Edge–hosted Fe–N3 Sites

Nitrogen-doped, carbon-supported transition metal catalysts are excellent for several reactions. Structural engineering of metal-Nx sites to boost catalytic activity is rarely studied. Here, we demonstrate that the structural flexibility of Fe-N3 site is vital for tuning the electronic structure of Fe atoms and regulating the catalytic transfer hydrogenation (CTH) activity. By introducing carbon defects, we construct Fe-N3 sites with varying Fe-N bond lengths distinguishable by X-ray absorption spectroscopy. We investigate the CTH activity by density functional theory and microkinetic calculations and reveal that the vertical displacement of the Fe atom out of the plane of the support, induced by the Fe-N3 distortion, raises the Fe [[EQUATION]]orbital and strengthens binding. We propose that the activity is controlled by the relaxation of the reconstructed site, which is further affected by Fe-N bond length, an excellent activity descriptor. Furthermore, we elucidate the origin of the CTH activity and principles for high-performing Fe-N-C catalysts by defect engineering.

09 BIOMASS FUELS↗

Piezochromic Behavior of 2,4,6-Triphenylpyrylium Tetrachloroferrate

In advanced photonics, there is a growing interest in piezochromic luminescent materials that exhibit multicolor switching, driven by their potential applications in optical recording, memory, and sensors. Here, the piezochromic behavior of 2,4,6-triphenylpyrylium tetrachloroferrate (Py-FeCl 4 ) under high pressures from 0 to 9 GPa is reported. The observed multicolor changing properties of Py-FeCl 4 (yellow–orange–red–maroon–black) are found to be fully reversible upon decompression to ambient conditions. The mechanism of Py-FeCl 4 piezochromism is investigated via Raman, infrared, and UV–vis spectroscopy combined with powder X-ray Diffraction. The absence of structural phase transitions as well as the abrupt shifts of bandgap values together with characteristic Raman and IR peaks within 0-9 GPa suggests that the Py-FeCl 4 multicoloring switching behavior is driven by an electron transfer between the inorganic FeCl 4 – anion and the organic pyrylium cation. The obtained results demonstrate that Py-FeCl 4 dye is a good candidate for developing high-pressure sensing technologies designed to function in extreme environments. Moreover, due to the inherent role of molecular-structure relationships in the pyrylium salt's photophysical properties, findings suggest the potential discovery of piezochromic behavior in other pyrylium compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ligand design in lanthanide complexes for luminescence, therapy, and sensing

In this chapter, we explore the research done by the de Bettencourt-Dias group in luminescent lanthanide complexes. The group has isolated ligands that sensitize the luminescence of lanthanide ions, and that bear additional functional groups that impart unique properties to the resulting complexes, such as the ability to generate cytotoxic singlet oxygen, or report on, through changes in emission intensity, viscosity or temperature at the nanoscale. The energy transfer processes are accessed through one-photon excitation or two-photon excitation through the ligand, as well as upconversion. Moreover, the group explored unique coordination chemistry of lanthanides, taking advantage of secondary interactions to isolate outer-sphere complexes of these ions.

Barber, Patrick S.↗

Luminescent Metal–Organic Framework for the Selective Detection of Aldehydes

The detection of toxic, hazardous chemical species is an important task because they pose serious risks to either the environment or human health. Luminescent metal–organic frameworks (LMOFs) as alternative sensors offer rapid and sensitive detection of chemical species. Interactions between chemical species and LMOFs result in changes in the photoluminescence (PL) profile of the LMOFs which can be readily detected using a simple fluorometer. Herein, we report the use of a robust, Zn-based LMOF, [Zn 5 (μ 3 -OH) 2 (adtb) 2 (H 2 O) 5 ·5 DMA] (Zn-adtb, LMOF-341), for the selective detection of benzaldehyde. Upon exposure to benzaldehyde, Zn-adtb experiences significant luminescent quenching, as characterized through PL experiments. Photoluminescent titration experiments reveal that LMOF-341 has a detection limit of 64 ppm and a Ksv value of 179 M –1 for benzaldehyde. Furthermore, we study the guest–host interactions that occur between LMOF-341 and benzaldehyde through in situ Fourier transform infrared and computational modeling employing density functional theory. The results show that benzaldehyde interacts more strongly with LMOF-341 compared to formaldehyde and propionaldehyde. Furthermore, our combined studies also reveal that the mechanism of luminescence quenching originates from an electron-transfer process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lanthanum-Doped Graphene for Electrocatalytic Reduction of Nitrogen Monoxide

Electrocatalytic conversion of nitrogen oxides is a promising approach to address nitrogen pollution in underground water. Nitrogen oxides, such as nitrate and nitrite, can be reduced to N 2 and NH 3 over an electrocatalyst, with NO as the key intermediate, subsequent reaction of which controls the overall activity and selectivity. Here, we report density functional theory calculations of NO electrocatalytic reduction (NOER) over lanthanum embedded in graphene, through which we show that the localized states in La drive the reaction favorably due to more pronounced molecular adsorption and charge transfer than transition metals such as Co. The free energy profiles are compared between the La-based single-atom catalyst (SAC) and Co-based SAC, for producing N 2 and NH 3 . We find that the La-SAC intensifies the electron transfer to the adsorbed NO, promoting the first protonation step of NO, which is the potential-limiting step on the Co-SAC. Also, an intriguing effect of the water solvent is revealed on the La-SAC. In addition to stabilizing the intermediate species, water molecules that are coordinated with La participate directly in the protonation steps, enhancing the catalyst activity. Furthermore, this study reveals the unique mechanism of NOER over rare-earth-based catalysts, highlighting the potential application of atomically dispersed f-block elements for electrocatalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bioinspired Cu(II) Defect Sites in ZIF-8 for Selective Methane Oxidation

Activating the C–H bonds of alkanes without further oxidation to more thermodynamically stable products, CO and CO 2 , is a long-sought goal of catalytic chemistry. Here, inspired by the monocopper active site of methane monooxygenase, we synthesized a Cu-doped ZIF-8 metal–organic framework with 25% Cu and 75% Zn in the nodes and activated it by heating to 200 °C and dosing in a stepwise fashion with O 2 , methane, and steam. We found that it does oxidize methane to methanol and formaldehyde. The catalysis persists through at least five cycles, and beyond the third cycle, the selectivity improves to the extent that no CO 2 can be detected. Experimental characterization and analysis were carried out by PXRD, DRUV–vis, SEM, and XAS (XANES and EXAFS). The reaction is postulated to proceed at open-coordination copper sites generated by defects, and the mechanism of methanol production was explicated by density functional calculations with the revMO6-L exchange–correlation functional. The calculations reveal a catalytic cycle of oxygen-activated Cu I involving the conversion of two molecules of CH 4 to two molecules of CH 3 OH by a sequence of hydrogen atom transfer reactions and rebound steps. For most steps in the cycle, the reaction is more favored by singlet species than by triplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning nonequilibrium electron forces for spin dynamics of itinerant magnets

Abstract We present a generalized potential theory for conservative as well as nonconservative forces for the Landau-Lifshitz magnetization dynamics. Importantly, this formulation makes possible an elegant generalization of the Behler-Parrinello machine learning (ML) approach, which is a cornerstone of ML-based quantum molecular dynamics methods, to the modeling of force fields in adiabatic spin dynamics of out-of-equilibrium itinerant magnetic systems. We demonstrate our approach by developing a deep-learning neural network that successfully learns the electron-mediated exchange fields in a driven s-d model computed from the nonequilibrium Green’s function method. We show that dynamical simulations with forces predicted from the neural network accurately reproduce the voltage-driven domain-wall propagation. Our work also lays the foundation for ML modeling of spin transfer torques and opens a avenue for ML-based multi-scale modeling of nonequilibrium dynamical phenomena in itinerant magnets and spintronics.

36 MATERIALS SCIENCE↗

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗

Graphene nanopattern as a universal epitaxy platform for single-crystal membrane production and defect reduction

Heterogeneous integration of single-crystal materials offers great opportunities for advanced device platforms and functional systems. Although substantial efforts have been made to co-integrate active device layers by heteroepitaxy, the mismatch in lattice polarity and lattice constants has been limiting the quality of the grown materials. Layer transfer methods as an alternative approach, on the other hand, suffer from the limited availability of transferrable materials and transfer-process-related obstacles. Here, we introduce graphene nanopatterns as an advanced heterointegration platform that allows the creation of a broad spectrum of freestanding single-crystalline membranes with substantially reduced defects, ranging from non-polar materials to polar materials and from low-bandgap to high-bandgap semiconductors. Additionally, we unveil unique mechanisms to substantially reduce crystallographic defects such as misfit dislocations, threading dislocations and antiphase boundaries in lattice- and polarity-mismatched heteroepitaxial systems, owing to the flexibility and chemical inertness of graphene nanopatterns. More importantly, we develop a comprehensive mechanics theory to precisely guide cracks through the graphene layer, and demonstrate the successful exfoliation of any epitaxial overlayers grown on the graphene nanopatterns. Furthermore, this approach has the potential to revolutionize the heterogeneous integration of dissimilar materials by widening the choice of materials and offering flexibility in designing heterointegrated systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Analysis and visualization of energy densities. II. Insights from linear-response time-dependent density functional theory calculations

Inspired by the analysis of Kohn–Sham energy densities by Nakai and coworkers, we extended the energy density analysis to linear-response time-dependent density functional theory (LR-TDDFT) calculations. Using ethylene–tetrafluoroethylene and oxyluciferin–water complexes as examples, distinctive distribution patterns were demonstrated for the excitation energy densities of local excitations (within a molecular fragment) and charge-transfer excitations (between molecular fragments). It also provided a simple way to compute the effective energy of both hot carriers (particle and hole) from charge-transfer excitations via an integration of the excitation energy density over the donor and acceptor grid points.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Brush-modified fluorescent organic nanoparticles by ATRP with rigidity-regulated emission

Organic nanoparticles provide exceptional intraparticle tailorability, enabling the incorporation of functional molecules for diverse applications. In this study, we present the synthesis and characterization of fluorescent organic nanoparticles (FoNPs) with encapsulated aggregation-induced emission (AIE) luminogens with emission properties regulated by particle rigidity. Atom transfer radical polymerization (ATRP) was employed in dispersed media to develop various fluorescence colors tuned by precise control over particle rigidity. Comprehensive analyses revealed that increased particle rigidity significantly enhanced photoluminescence, achieving quantum yields of up to 22% in selected solvents. The high chain-end fidelity facilitated the grafting of hydrophilic polymer brushes from surfaces of FoNPs used as macroinitiators, enabling their dispersion in aqueous media while maintaining bright fluorescence. These findings highlight the potential of rigidity-regulated FoNPs as versatile platforms for advanced material applications, particularly in fluorescent waterborne films and aqueous-phase sensing systems.

Yin, Rongguan [Carnegie Mellon Univ., Pittsburgh, ↗

Nanoscale modulation of flat bands via controllable charge density wave defects in 4⁢𝐻⁡𝑏−Ta⁢S 2

Electron correlation is a main driver of exotic quantum phases and their interplay. The 4H b-TaS 2 system, possessing an intrinsic heterostructure of 1T- and 1H -TaS 2 monolayers, offers a unique opportunity to control electron correlation by distorting the atomic lattice or tuning interlayer coupling. Here, we investigated intrinsically deformed charge-density waves (CDWs) in the 1T layer of 4H b-TaS 2 to elucidate and control their effects on flat bands using scanning tunneling microscopy and spectroscopy (STM/S) combined with first-principles calculations. We identified two types of CDW defects: Type 1 has structural distortion and locally suppressed flat bands, while Type 2 features an increased flat band filling factor of intact CDW structure. Density functional theory calculations indicate that a sulfur vacancy in the 1T layer distorts the CDW structure and gives rise to a Type 1, whereas a sulfur vacancy in the 1H layer reduces the interlayer charge transfer and leads to a Type 2. Furthermore, we demonstrated creating and erasing individual CDW defects via STM manipulation. Here, our findings provide a pathway to not only tune flat bands but also selectively manipulate the interaction between CDW, the atomic lattice, and interlayer coupling in strongly correlated systems with atomic precision.

Charge density waves↗

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Computational models for high-pressure transcritical turbulence in wall-modeled large-eddy simulation typically rely on wall-function models to overcome the need for resolving the boundary layer structures. However, the mechanisms and models of turbulent boundary layer at transcritical conditions remain poorly understood since the near-wall flow and heat transfer are significantly affected by the enhanced fluctuations and steep gradients in thermodynamic properties. Here, to address this issue, we study the mechanisms of transcritical turbulent boundary layers and wall-attached models at transcritical conditions. It is shown that the real-fluid variable-property effects are associated with the coupling between the near-wall cycle and the wall-normal coherent motions in the outer layer, resulting in the amplification of turbulent energy in the outer layer and noticeable energy transfer between the log-layer and the outer layer; hence, turbulence in the log-layer is modulated by the outer layer. Based on this underlying physical principle, we propose the characteristic velocity and length scales for the attached eddy at transcritical conditions, and extend the attached eddy model to transcritical turbulent boundary layers by introducing a mixed scaling that incorporates both inner and outer scalings. We show that the new characteristic scales and extended attached-eddy model perform well in characterizing the structures in transcritical turbulent boundary layers.

Li, Fangbo↗