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At least 1,171 records · Page 65

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗

Sustainable Critical Minerals: Mining, Production, and Legacy

Critical minerals (CMs) are required in renewable energy systems, electric vehicles, electronics, and national defense. Global demand has increased rapidly due to energy and digital transitions, and the United States has become increasingly reliant on vulnerable supply chains. Geological scarcity, trade barriers, environmental hurdles, and processing challenges impede domestic CM production growth. Emerging strategies, including circular economy practices and advanced sustainable mining and processing techniques, can mitigate supply chain and economic risks. To advance these approaches, consistent research priorities, policy revisions, and technology investments are required to develop a resilient CM supply. Doing so with a focus on sustainability goals can simultaneously advance domestic economic and technological goals while limiting environmental impacts and supporting global environmental goals.

biomining↗

Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman–Rubin Convergence Diagnostics

The determination of the solvation free energy of ions and molecules holds profound importance across a spectrum of applications spanning chemistry, biology, energy storage, and the environment. Molecular dynamics simulations are powerful tools for computing this critical parameter. Nevertheless, the accurate and efficient calculation of the solvation free energy becomes a formidable endeavor when dealing with complex systems characterized by potent Coulombic interactions and sluggish ion dynamics and, consequently, slow transition across various metastable states. Here, in the present study, we expose limitations stemming from the conventional calculation of the statistical inefficiency g in the thermodynamic integration method, a factor that can hinder the determination of convergence of the solvation free energy and its associated uncertainty. Instead, we propose a robust scheme based on Gelman–Rubin convergence diagnostics. We leverage this improved estimation of uncertainties to introduce an innovative accelerated thermodynamic integration method based on the Gaussian Process regression. This methodology is applied to the calculation of the solvation free energy of trivalent rare-earth elements immersed in ionic liquids, a scenario in which the aforementioned challenges render standard approaches ineffective. The proposed method proves to be effective in computing solvation free energy in situations where traditional thermodynamic integration methods fall short.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Threshold Ionization Spectroscopy and Theoretical Calculations of LnO (Ln = La and Ce)

Mass-analyzed threshold ionization (MATI) spectroscopy was used to measure the vibronic spectra of LnO (Ln = La and Ce). Single-reference coupled cluster and relativistic multireference configuration calculations were carried out to compare with the measured vibronic energies. The spectrum of LaO displays a single vibronic band system, while that of CeO shows multiple ones. The ionization energies of LaO and CeO are measured as 5.2446 (6) and 5.3332(6) eV, respectively, which are a hundredfold improvement over the literature values. The vibrational energies of the neutral molecule and corresponding ion reveal the charge effect on the metal-oxygen bond of both species. The single band system in the spectrum of LaO arises from the transition of the ground state of the neutral molecule with the La(6s 1 )O(2p 6 ) valence configuration to the ground state of the singly charged ion with the La(6s o )O(2p 6 ) configuration. Here, the multiple band systems in the spectrum of CeO are attributed to the spin-orbit coupling for the Ce(4f 1 6s 1 )O(2p 6 ) configuration of the neutral molecule and an excited state for the Ce(4f 1 )O(2p 6 ) configuration of the ion.

74 ATOMIC AND MOLECULAR PHYSICS↗

Fundamental Insights into Cathode Stability: Linking Compositional Tuning and Local Coordination in Complex Metal Oxides under Aqueous Transformations

Compositional tuning of complex metal oxides in Li-ion battery materials influences their performance as well as their end-of-life behavior, in particular, the tendency to release toxic metal cations in aqueous solution. We modeled ternary variants of a parent LiCoO 2 delafossite structure by varying the metal identity and relative amounts. This yielded ten model formulations of Li(A 4/6 B 1/6 C 1/6 )O 2 , where the material is enriched with the A metal and doped with B and C, with Ni, Mn, Co, Fe, Al, V, and Ti as constituent metals. To assess their stability in aqueous conditions, metal release energetics were calculated using a combination of Density Functional Theory calculations and thermodynamics. Metal release in ternary oxides is dictated by subtle variations in the coordination environment of the leaving group. To identify governing chemical features across diverse compositions with varying local coordination environments, we leverage random forest regression and descriptor importance analysis. A key result is that metal–oxygen orbital hybridization, quantified using a projected density-of-states-derived descriptor, H d/p , provides a physically grounded measure of interaction strength that governs metal release energetics. This refined perspective goes beyond conventional oxidation state considerations and offers more robust insights for materials science. Finally, we model defect surface-bound O 2 dimer formation as a proxy for reactive oxygen species (ROS) generation. The results show that Ni-rich compositions more readily stabilize spin-polarized O 2 dimers, corroborating experimental reports of an increased ROS-driven biological response. In conclusion, our results establish a compositional and electronic basis for metal release and surface oxygen reactivity that form a rationale for complex metal oxide design principles.

36 MATERIALS SCIENCE↗

Characterizing Ultrafast Intersystem Crossing Pathways in Molecular Pt Dimers Using Time-Resolved Wide-Angle X-ray Scattering

Vibronic coupling between transition metal charge transfer states is a potential mechanism for enhancing the intersystem crossing (ISC) rate. Vibronic coupling-driven ISC has been observed in Pt­(II) dimer complexes, where the trajectory across excited-state pathways is tuned by atomic displacements via Pt–Pt stretching vibrations. Time-resolved wide-angle X-ray scattering (TR-WAXS) was utilized to quantify the Pt–Pt contraction following metal–metal-to-ligand charge transfer (MMLCT) excitation in Pt dimers with different bridging ligands. Both complexes exhibit Pt–Pt bond formation with a decrease in Pt–Pt distance of ∼ 0.25 Å and coherent vibrational wavepackets (CVWPs) encoded in the Pt–Pt contraction of both dimers. However, the complexes exhibit different time-dependent evolution of their CVWPs. Analysis of interference patterns between different CVWPs is used to track the trajectory across the excited-state surfaces. Furthermore, this work demonstrates that the interference between CVWPs in ultrafast TR-WAXS encodes indirect information regarding electronic excited-states to reveal the Pt dimer bridge-dependent ISC mechanism.

Computational chemistry↗

Microphase Separation in Polyelectrolyte Blends: Weak Segregation Theory and Relation to Nuclear "Pasta".

We develop the weak segregation theory of micro phase separation in stoichiometric blends of oppositely and weakly charged polyelectrolytes, which would be immiscible in the absence of charged units. Short-range repulsions between polycation and polyanion monomers induce the formation of oppositely charged domains, the size of which is controlled by their excess Coulomb energy. The diagram of blend morphologies is constructed in the framework of Leibler's mean-field approach and to account for fluctuations within the Brazovskii-Fredrickson-Helfand approximation. Phase behavior of the polyelectrolyte blends is fully analogous to that of neutral diblock copolymers. The mean-field analysis predicts that the order-disorder transition (ODT) is second order for the symmetric blend. In asymmetric mixtures, an increasing incompatibility between polyelectrolytes triggers the usual cascade of first-order phase transitions, dis -> bcc -> hex -> lam. Fluctuations alter the phase diagram topology and allow the direct transitions from the disordered state (dis) to hex and lam microphases; for the symmetric blend, ODT becomes weakly first order. We also discuss that both microphase separation in polyelectrolyte blends and the formation of nuclear "pasta" phases within neutron stars are governed by similar physical principles, despite the 6 orders of magnitude difference in the periods of these structures.

Rumyantsev, Artem M.↗

Ball Milling-Enabled Fe 2.4+ to Fe 3+ Redox Reaction in Prussian Blue Materials for Long-Life Aqueous Sodium-Ion Batteries

Aqueous Na-ion batteries using Prussian blue materials have inherent advantages on safety, material sustainability, and economic cost. However, it is challenging to obtain long term cycling stability because many redox reactions have poor intrinsic stability in water. In this report we demonstrate reversible Fe 2.4+ to Fe 3+ redox reaction of Prussian blue electrodes cycled in 17 m NaClO 4 water-in-salt electrolyte. The cubic phase c-Na 1.17 Fe[Fe(CN) 6 ]·0.35H 2 O) derived from monoclinic Prussian blue (m-Na 1.88 Fe[Fe(CN) 6 ]·0.7H 2 O) through ball milling delivers excellent cycling stability of >18,000 cycles with >90% capacity retention at 10C rate. The specific capacity is ~75 mAh/g and ~67 mAh/g at 1C and 10C rate, respectively. Systematic characterizations including electron microscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, and X-ray absorption spectroscopy have verified the phase transition and iron oxidation state evolution, revealing the mechanism that enables the material’s high rate and long durability as the battery cathode.

25 ENERGY STORAGE↗

Combined First-Principles and Experimental Investigation into the Reactivity of Codeposited Chromium–Carbon under Pressure

High-pressure synthesis in the diamond anvil cell suffers from the lack of a general approach for the control of precursor stoichiometry and homogeneity. Here, we present results from a new method we have developed that uses magnetron cosputtering to prepare stoichiometrically precise and atomically mixed amorphous films of Cr:C. Laser-heated diamond anvil cell experiments carried out on a flake of this sample at pressures between 13.5 and 24.3 GPa lead to the observation of Cr 3 C (Pnma) over the entire pressure range–in good agreement with our in-house theoretical predictions–but also reveal two other metastable phases that were not expected: a novel monoclinic chromium carbide phase and the NaCl-type CrC (Fm3̅m) phase. The unexpected stability of CrC is investigated by using first-principles methods, revealing a large stabilizing effect tied to substoichiometry at the carbon site. These results offer an important case study into the current limitations of crystal structure prediction methods with regard to phase complexity and bolster the growing need for advanced theoretical approaches that can more completely survey experimentally unexplored phase space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Mechanism of High Capacitance in Nickel Hexaaminobenzene-Based Conductive Metal-Organic Frameworks in Aqueous Electrolytes

Recently, intrinsically conductive metal-organic frameworks (MOFs) have demonstrated promising performance in fast-charging energy storage applications and may outperform some current electrode materials (e.g., porous carbons) for supercapacitors in terms of both gravimetric and volumetric capacitance. In this report, we examine the mechanism of high capacitance in a nickel hexaaminobenzene-based MOF (NiHAB). Using a combination of in situ Raman and X-Ray absorption spectroscopies, as well as detailed electrochemical studies in a series of aqueous electrolytes, we demonstrate in this work that the charge storage mechanism is in fact a pH-dependent surface pseudocapacitance, and, unlike typical inorganic systems, where transition metals change oxidation state during charge/discharge cycles, NiHAB redox activity is ligand-centered.

25 ENERGY STORAGE↗

Quantum Machine-Learning for Eigenstate Filtration in Two-Dimensional Materials

Quantum machine-learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure calculations of molecular systems and spin models in magnetic systems. However, the discussion in all these recipes focuses specifically on targeting the ground state. Herein we demonstrate a quantum algorithm that can filter any energy eigenstate of the system based on either symmetry properties or a predefined choice of the user. The workhorse of our technique is a shallow neural network encoding the desired state of the system with the amplitude computed by sampling the Gibbs–Boltzmann distribution using a quantum circuit and the phase information obtained classically from the nonlinear activation of a separate set of neurons. We show that the resource requirements of our algorithm are strictly quadratic. To demonstrate its efficacy, we use state filtration in monolayer transition metal dichalcogenides which are hitherto unexplored in any flavor of quantum simulations. We implement our algorithm not only on quantum simulators but also on actual IBM-Q quantum devices and show good agreement with the results procured from conventional electronic structure calculations. We thus expect our protocol to provide a new alternative in exploring the band structures of exquisite materials to usual electronic structure methods or machine-learning techniques that are implementable solely on a classical computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Definition of the S = 1 π vs S = 2 σ Reactivity and S = 2 Character in the Ground State of an S = 1 Fe IV O Complex

Iron(IV)-oxo intermediates found in iron enzymes and artificial catalysts are competent for H atom abstraction in catalytic cycles. For S = 2 intermediates, both axial and equatorial approaches are well-established. The mechanism for S = 1 sites is not as well understood: an equatorial approach is more energetically favorable, and an axial approach requires crossing from the S = 1 to the S = 2 surface. Here, in this study, we use 1s2p resonant inelastic X-ray scattering (RIXS) and Fe L-edge X-ray absorption spectroscopy on the S = 1 [Fe IV O(TMC)(CH3CN)] 2+ and observe both S = 2 and S = 1 final states, which enables the experimental evaluation of the energetics of the axial and equatorial reactivity of an S = 1 Fe IV O center on its S = 2 vs S = 1 surface. The observation of S = 2 final states in the RIXS spectrum demonstrates significant S = 2 character spin–orbit mixed into the S = 1 ground state.

energy↗

Investigation of the monopole magneto-chemical potential in spin ices using capacitive torque magnetometry

The single-ion anisotropy and magnetic interactions in spin-ice systems give rise to unusual non-collinear spin textures, such as Pauling states and magnetic monopoles. The effective spin correlation strength (J eff ) determines the relative energies of the different spin-ice states. With this work, we display the capability of capacitive torque magnetometry in characterizing the magneto-chemical potential associated with monopole formation. We build a magnetic phase diagram of Ho 2 Ti 2 O 7 , and show that the magneto-chemical potential depends on the spin sublattice (α or β), i.e., the Pauling state, involved in the transition. Monte Carlo simulations using the dipolar-spin-ice Hamiltonian support our findings of a sublattice-dependent magneto-chemical potential, but the model underestimates the J eff for the β-sublattice. Additional simulations, including next-nearest neighbor interactions (J 2 ), show that long-range exchange terms in the Hamiltonian are needed to describe the measurements. This demonstrates that torque magnetometry provides a sensitive test for J eff and the spin-spin interactions that contribute to it.

36 MATERIALS SCIENCE↗

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as $\sqrt{T/N}$. When only K$\ll$T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to $\sqrt{K/N}$. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

97 MATHEMATICS AND COMPUTING↗

Antiferromagnetic metal phase in an electron-doped rare-earth nickelate

Long viewed as passive elements, antiferromagnetic materials have emerged as promising candidates for spintronic devices due to their insensitivity to external fields and potential for high-speed switching. Recent work exploiting spin and orbital effects has identified ways to electrically control and probe the spins in metallic antiferromagnets, especially in non-collinear or non-centrosymmetric spin structures. The rare-earth nickelate NdNiO 3 is known to be a non-collinear antiferromagnet in which the onset of antiferromagnetic ordering is concomitant with a transition to an insulating state. In this work, we find that for low electron doping, the magnetic order on the nickel site is preserved, whereas electronically, a new metallic phase is induced. We show that this metallic phase has a Fermi surface that is mostly gapped by an electronic reconstruction driven by bond disproportionation. Furthermore, we demonstrate the ability to write to and read from the spin structure via a large zero-field planar Hall effect. Our results expand the already rich phase diagram of rare-earth nickelates and may enable spintronics applications in this family of correlated oxides.

36 MATERIALS SCIENCE↗