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At least 217 records · Page 12

An AI-driven framework for evaluating local and state authorities’ permitting processes

The demand for new energy infrastructure is increasing across the United States, but heterogenous permitting processes and embedded requirements across different local jurisdictions can cause project delays, increase “soft costs,” and hinder developer expansion. This study analyzes the variability in local permitting requirements across the U.S. and develops a quantitative approach to describe their clarity and effectiveness in enabling infrastructure project development. By using an Energy Language Model (ELM), a large language model (LLM) for energy technologies, we systematically gathered permitting information from nearly 300 state-, county-, and city-level documents, creating a structured dataset of requirements and procedures on an unprecedented scale and speed. Our analysis revealed that local (city and county) permitting requirement documents are underrepresented compared to state-level guidance documents, which can impede timely and cost-effective installation of new electric infrastructure. Our validation process showed that the final database has an accuracy of approximately 95%. We, further, created a new quantitative method to score permitting requirements for clarity and efficiency, with electric vehicle supply equipment as an initial use case. The average local permitting document scored a 1.8 out of 5, which we interpret as meaning that half of the requirements developers face when installing electric infrastructure are ambiguous, increasing both cost and time. We also created a “Generalized Permit Process”, highlighting common procedural steps and identifying specific opportunities for municipalities to improve their documentation. This research establishes a systematic and scalable framework for evaluating the complexities of local infrastructure permitting processes by combining LLM-powered data collection and quantitative scoring. The framework enables policymakers and developers to identify and mitigate procedural bottlenecks, with the expectation that these improvements can accelerate application review and approval, reduce project costs, and expedite connection to utility distribution grids. As a foundational approach for streamlining local project development processes, this study’s methods are intended to be extended to a wide range of energy applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The underappreciated role of anthropogenic sources in atmospheric soluble iron flux to the Southern Ocean

The atmospheric deposition of soluble (bioaccessible) iron enhances ocean primary productivity and subsequent atmospheric CO 2 sequestration in iron-limited ocean basins, especially the Southern Ocean. While anthropogenic sources have been recently suggested to be important in some northern hemisphere oceans, the role in the Southern Ocean remains ambiguous. By comparing multiple model simulations with the new aircraft observations for anthropogenic iron, we show that anthropogenic soluble iron deposition flux to the Southern Ocean could be underestimated by more than a factor of ten in previous modeling estimates. Our improved estimate for the anthropogenic iron budget enhances its contribution on the soluble iron deposition in the Southern Ocean from about 10% to 60%, implying a dominant role of anthropogenic sources. We predict that anthropogenic soluble iron deposition in the Southern Ocean is reduced substantially (30-90%) by the year 2100, and plays a major role in the future evolution of atmospheric soluble iron inputs to the Southern Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding intercalation chemistry for sustainable aqueous zinc–manganese dioxide batteries

Rechargeable aqueous Zn-MnO 2 technology combines one of the oldest battery chemistries with favourable sustainability characteristics, including safety, cost and environmental compatibility. However, the ambiguous charge storage mechanism presents a challenge to fulfil the great potential of this energy technology. In this work, we leverage on advanced electron microscopy, electrochemical analysis and theoretical calculations to look into the intercalation chemistry within the cathode material, or α-MnO 2 more specifically. We show that Zn 2+ insertion into the cathode is unlikely in the aqueous system; rather, the charge storage process is dominated by proton intercalation to form α-H x MnO 2 . We further reveal anisotropic lattice change as a result of entering protons proceeding from the surface into the bulk of α-MnO 2 , which accounts for the structural failure and capacity decay of the electrode upon cycling. Our work not only advances the fundamental understanding of rechargeable zinc batteries but also suggests the possibility to optimize proton intercalation kinetics for better-performing cell designs. A rechargeable aqueous Zn-MnO 2 battery features a combination of favourable sustainability characteristics from safety to cost. The authors deploy advanced characterizations and theoretical calculations to provide fresh insight into the charge storage mechanism, which not only closes an ongoing debate but suggests ways forward.

25 ENERGY STORAGE↗

Ab initio thermodynamics reveals the nanocomposite structure of ferrihydrite

Ferrihydrite is a poorly crystalline iron oxyhydroxide nanomineral that serves a critical role as the most bioavailable form of ferric iron for living systems. However, its atomic structure and composition remain unclear due in part to ambiguities in interpretation of X-ray scattering results. Prevailing models so far have not considered the prospect that at the level of individual nanoparticles multiple X-ray indistinguishable phases could coexist. Using ab initio thermodynamics we show that ferrihydrite is likely a nanocomposite of distinct structure types whose distribution depends on particle size, temperature, and hydration. Nanoparticles of two contrasting single-phase ferrihydrite models of Michel and Manceau are here shown to be thermodynamically equivalent across a wide range of temperature and pressure conditions despite differences in their structural water content. Higher temperature and water pressure favor the formation of the former, while lower temperature and water pressure favor the latter. For aqueous suspensions at ambient conditions, their coexistence is maximal for particle sizes up to 12 nm. The predictions inform and help resolve different observations in various experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational modeling predicts the stability of both Pd + and Pd2 + ion-exchanged into H-CHA

Passive NO x adsorbers (PNA) using Pd/zeolites have emerged as a promising solution for the reduction of cold-start emissions from vehicle exhaust. However, the nature of the active sites and the mechanisms underlying NO x adsorption in Pd/zeolites remain a subject of ongoing investigation. In this study, we employ quantum chemical simulations to investigate the structure of Pd species in cation-exchange sites at isolated Al and Al pairs in the 6-ring and 8-ring of the CHA framework before the introduction of NO x . Our calculations show that the speciation of Pd in these exchange sites strongly depends on the precise Al arrangement within the framework, as well as the operating conditions. Ionically dispersed Pd is found to be the most favorable species over a wide range of oxidizing and reducing conditions. Small oligomers of PdO and metallic Pd do not appear to be competitive at either isolated Al or Al pairs. Notably, our calculations show that ion exchange sites other than next–next–nearest neighbor Al pairs in the 6-ring will be preferentially occupied by Pd + instead of Pd 2+ . The stability of Pd + in the zeolite environment is an interesting contrast with its rareness in molecular Pd compounds. Nonetheless, a detailed analysis of the electronic structure shows that predicted Pd oxidation states are consistent with chemical intuition for all complexes investigated in this study. We also discuss the potential ambiguity in Pd characterization provided by typical experimental techniques such as XANES, EXAFS and UV-Vis, and highlight the need for additional EPR spectroscopy studies to further elucidate the initial Pd speciation in zeolites for PNA applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorption of ethylenediamine on Cu surfaces: attributes of a successful capping molecule using first-principles calculations

The shape-controlled synthesis of Cu nanocrystals can benefit a wide range of applications, though challenges exist in achieving high and selective yields to a particular shape. Capping agents play a pivotal role in controlling shape, but their exact role remains ambiguous. In this study, the adsorption of ethylenediamine (EDA) on Cu(100) and Cu(111) was investigated with quantum density functional theory (DFT) to reveal the complex roles of EDA in promoting penta-twinned Cu nanowire growth. We find EDA has stronger binding on Cu(100) than on Cu(111), which agrees the general expectation that penta-twinned Cu nanowires express facets with stronger capping-molecule binding. Despite this stronger binding, ab initio thermodynamics reveals the surface energy of EDA-covered Cu(111) is lower than that EDA-covered Cu(100) at all solution-phase EDA chemical potentials, so there is no thermodynamic driving force for penta-twinned nanowires. We also investigated the capability of EDA to protect Cu surfaces from oxidation in water by quantifying energy barriers for a water molecule to diffuse through EDA layers on Cu(100) and Cu(111). The energy barrier on Cu(100) is significantly lower, which supports observations of faster oxidation of Cu(100) in electrochemical experiments. Thus, we elucidate another possible function of a capping agent – to enable selective oxidation of crystal facets. This finding adds to the general understanding of successful attributes of capping agents for shape-selective nanocrystal growth.

36 MATERIALS SCIENCE↗

Unveiling the complex configurational landscape of the intralayer cavities in a crystalline carbon nitride

The in-depth understanding of the reported photoelectrochemical properties of the layered carbon nitride, poly(triazine imide)/LiCl (PTI/LiCl), has been limited by the apparent disorder of the Li/H atoms within its framework. To understand and resolve the current structural ambiguities, an optimized one-step flux synthesis (470 °C, 36 h, LiCl/KCl flux) was used to prepare PTI/LiCl and deuterated-PTI/LiCl in high purity. Its structure was characterized by a combination of neutron/X-ray diffraction and transmission electron microscopy. The range of possible Li/H atomic configurations was enumerated for the first time and, combined with total energy calculations, reveals a more complex energetic landscape than previously considered. Experimental data were fitted against all possible structural models, exhibiting the most consistency with a new orthorhombic model (Sp. Grp. Ama2) that also has the lowest total energy. In addition, a new Cu(I)-containing PTI (PTI/CuCl) was prepared with the more strongly scattering Cu(I) cations in place of Li, and most closely matching with the partially-disorder structure in Cmc2 1 . Thus, a complex configurational landscape of PTI is revealed to consist of a number of ordered crystalline structures that are new potential synthetic targets, such as with the use of metal-exchange reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗

Scrutinizing formally Ni IV centers through the lenses of core spectroscopy, molecular orbital theory, and valence bond theory

Nickel K- and L 2,3 -edge X-ray absorption spectra (XAS) are discussed for 16 complexes and complex ions with nickel centers spanning a range of formal oxidation states from II to IV. K-edge XAS alone is shown to be an ambiguous metric of physical oxidation state for these Ni complexes. Meanwhile, L 2,3 -edge XAS reveals that the physical d-counts of the formally Ni IV compounds measured lie well above the d 6 count implied by the oxidation state formalism. The generality of this phenomenon is explored computationally by scrutinizing 8 additional complexes. The extreme case of NiF 6 2- is considered using high-level molecular orbital approaches as well as advanced valence bond methods. The emergent electronic structure picture reveals that even highly electronegative F-donors are incapable of supporting a physical d 6 Ni IV center. The reactivity of Ni IV complexes is then discussed, highlighting the dominant role of the ligands in this chemistry over that of the metal centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solving the P–O/P–OH riddle: direct synthesis and neutron diffraction characterization of dianionic dithiophosphonates

Here, we report the first definitive neutron diffraction study aimed at resolving the P–OH/P$=$O structural ambiguity in metal dithiophosphonates. The small NH 4 counterion forces a rare syn-configuration via an extended hydrogen-bonding network. Neutron analysis definitively confirmed the fully deprotonated P$=$O moiety, thus confirming the formation of a dianionic dithiophosphonate, a versatile synthon in homoleptic and heteroleptic coordination environments.

Pillay, Michael N. [National Dong Hwa Univ. (Taiwa↗

A data-driven network optimisation approach to coordinated control of distributed photovoltaic systems and smart buildings in distribution systems

The increasing integration of distributed energy resources, including demand-side resources and distributed photovoltaics (PVs), into distribution systems has resulted in more complicated power system operation. A data-driven network optimisation approach is proposed to coordinate the control of distributed PVs and smart buildings in distribution networks considering the uncertainties of solar power, outdoor temperature and heat gain associated with building thermal dynamics. These uncertain parameters have a significant impact on the operation and control of distributed PVs and smart buildings, bringing challenges to the distribution system operation. In the proposed data-driven distributionally robust optimisation (DRO) approach, the Wasserstein ball is used to construct an ambiguity set for the uncertain parameters, which does not require the probability distributions to be known. Furthermore, a conditional value-at-risk is incorporated into the Wasserstein-based DRO model and converted into a computationally tractable mixed-integer convex optimisation problem. Benchmarked with robust optimisation and chance-constrained programming, the proposed data-driven model can give a less conservative robust solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Exploring the connection between compact object mergers and fast X-ray transients

Context. The connection between compact object mergers and some extragalactic fast X-ray transients (FXRTs) has long been hypothesised but never ultimately established. Aims. In this work, we investigate two FXRTs, the LEIA X-ray Transient LXT 240402A and the Einstein Probe EP 250207b, whose precise positions lie close to nearby (z ≲ 0.1) quiescent galaxies with a negligible probability of chance coincidence, identifying them as particularly promising cases of merger-driven explosions in the local Universe. Methods. We used Chandra to derive accurate localisations for both events and secure otherwise ambiguous associations with their optical counterparts. Deep optical and near-infrared observations with VLT, GTC, and LBT were performed to characterise the surrounding environment and search for kilonova emission, the hallmark of neutron star mergers. Complementary early-time X-ray monitoring with Swift and Einstein Probe was used to constrain the non-thermal afterglow. Results. We find that both FXRTs remain compatible with a compact binary merger progenitor, which produced low-mass ejecta and kilonova emission subdominant to the afterglow. However, alternative explanations such as a distant (z ≳ 1) core-collapse supernova cannot be conclusively ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)↗

Deformation of Néel-type skyrmions revealed by Lorentz transmission electron microscopy

Néel-type magnetic skyrmions in multilayers are promising candidates for ultra-low power spintronic devices. To image the Néel-type skyrmions using Lorentz transmission electron microscopy (L-TEM), the samples must be tilted. Thus, the external magnetic field consists of both in-plane and out-of-plane components. To date, it is still not well known on the effect of the in-plane magnetic field on the L-TEM images, leading to ambiguities in retrieving the structure of Néel-type skyrmions. Here, Néel-type skyrmions in three [Pt/Co/Ta]$_{20}$ multilayer samples, with the easy magnetization axis being tuned from the out-of-plane to the in-plane direction by increasing the Co thickness from 1.8 to 2.2 nm, are imaged. When using a smaller defocus value (-2 mm) and a higher magnification (×9100) of L-TEM, a surprising dark-bright-dark-bright double contrasted pattern, instead of the previously reported dark-bright contrasted pattern, is observed. The additional dark-bright contrasted pattern becomes more evident for thicker Co layer samples in which the magnetization axis tilts more toward the in-plane direction. Further analysis, via a combination of magnetic force microscopy experiments, micromagnetic simulations, and micromagnetic analysis to Lorentz TEM simulation, shows that the additional dark-bright features originate from the deformation of the Néel-type skyrmions within an in-plane magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

57Fe Mössbauer isomer shift of pure iron and iron oxides at high pressure—An experimental and theoretical study

The 57Fe isomer shift (IS) of pure iron has been measured up to 100 GPa using synchrotron Mössbauer spectroscopy in the time domain. Apart from the expected discontinuity due to the α→ε structural and spin transitions, the IS decreases monotonically with increasing pressure. The absolute shifts were reproduced without semi-empirical calibrations by periodic density functional calculations employing extensive localized basis sets with several common density functionals. However, the best numerical agreement is obtained with the B1WC hybrid functional. Extension of the calculations to 350 GPa, a pressure corresponding to the Earth’s inner core, predicted the IS range of 0.00 to -0.85 mm/s, covering the span from Fe(0) to Fe(VI) compounds measured at ambient pressure. The calculations also reproduced the pressure trend from polymorphs of prototypical iron oxide minerals, FeO and Fe2O3. Analysis of the electronic structure shows a strong donation of electrons from oxygen to iron at high pressure. The assignment of formal oxidation to the Fe atom becomes ambiguous under this condition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration of an x-ray Raman spectroscopy setup to study warm dense carbon at the high energy density instrument of European XFEL

We present a proof-of-principle study demonstrating x-ray Raman Spectroscopy (XRS) from carbon samples at ambient conditions in conjunction with other common diagnostics to study warm dense matter, performed at the high energy density scientific instrument of the European x-ray Free Electron Laser (European XFEL). We obtain sufficient spectral resolution to identify the local structure and chemical bonding of diamond and graphite samples, using highly annealed pyrolytic graphite spectrometers. Due to the high crystal reflectivity and XFEL brightness, we obtain signal strengths that will enable accurate XRS measurements in upcoming pump–probe experiments with a high repetition-rate, where the samples will be pumped with high-power lasers. Molecular dynamics simulations based on density functional theory together with XRS simulations demonstrate the potential of this technique and show predictions for high-energy-density conditions. Our setup allows simultaneous implementation of several different diagnostic methods to reduce ambiguities in the analysis of the experimental results, which, for warm dense matter, often relies on simplifying model assumptions. The promising capabilities demonstrated here provide unprecedented insights into chemical and structural dynamics in warm dense matter states of light elements, including conditions similar to the interiors of planets, low-mass stars, and other celestial bodies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental characterization of hot-electron emission and shock dynamics in the context of the shock ignition approach to inertial confinement fusion

We report on planar target experiments conducted on the OMEGA-EP laser facility performed in the context of the shock ignition (SI) approach to inertial confinement fusion. The experiment aimed at characterizing the propagation of strong shock in matter and the generation of hot electrons (HEs), with laser parameters relevant to SI (1-ns UV laser beams with I ~10 16 W/cm 2 ). Time-resolved radiographs of the propagating shock front were performed in order to study the hydrodynamic evolution. The hot-electron source was characterized in terms of Maxwellian temperature, T h , and laser to hot-electron energy conversion efficiency η using data from different x-ray spectrometers. The post-processing of these data gives a range of the possible values for T h and η [i.e., T h [keV] ϵ (20, 50) and η ϵ (2%, 13%)]. These values are used as input in hydrodynamic simulations to reproduce the results obtained in radiographs, thus constraining the range for the HE measurements. According to this procedure, we found that the laser converts ~10% ± 4% of energy into hot electrons with T h = 27 ± 8 keV. The paper shows how the coupling of different diagnostics and numerical tools is required to sufficiently constrain the problem, solving the large ambiguity coming from the post-processing of spectrometers data. The effect of the hot electrons on the shock dynamics is then discussed, showing an increase in the pressure around the shock front. Furthermore, the low temperature found in this experiment without pre-compression laser pulses could be advantageous for the SI scheme, but the high conversion efficiency may lead to an increase in the shell adiabat, with detrimental effects on the implosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nanoscale solid-state nuclear quadrupole resonance spectroscopy using depth-optimized nitrogen-vacancy ensembles in diamond

Nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) spectroscopy of bulk quantum materials have provided insight into phenomena, such as quantum phase criticality, magnetism, and superconductivity. With the emergence of nanoscale 2D materials with magnetic phenomena, inductively detected NMR and NQR spectroscopy are not sensitive enough to detect the smaller number of spins in nanomaterials. The nitrogen-vacancy (NV) center in diamond has shown promise in bringing the analytic power of NMR and NQR spectroscopy to the nanoscale. However, due to depth-dependent formation efficiency of the defect centers, noise from surface spins, band bending effects, and the depth dependence of the nuclear magnetic field, there is ambiguity regarding the ideal NV depth for surface NMR of statistically polarized spins. In this work, we prepared a range of shallow NV ensemble layer depths and determined the ideal NV depth by performing NMR spectroscopy on statistically polarized 19 F in Fomblin oil on the diamond surface. We found that the measurement time needed to achieve a signal-to-noise ratio of 3 using XY8-N noise spectroscopy has a minimum at an NV ensemble depth of 5.5 ± 1.5 nm for ensembles activated from 100 ppm nitrogen concentration. To demonstrate the sensing capabilities of NV ensembles, we perform NQR spectroscopy on the 11 B of hexagonal boron nitride flakes. We compare our best diamond to previous work with a single NV and find that this ensemble provides a shorter measurement time with excitation diameters as small as 4 μm. Furthermore, this analysis provides ideal conditions for further experiments involving NMR/NQR spectroscopy of 2D materials with magnetic properties.

2D materials↗