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At least 235 records · Page 13

Bipolar Membranes for Ion Management in (Photo)Electrochemical Energy Conversion

Conspectus (Photo)electrochemical energy conversion is important in the development of a carbon-neutral energy economy because it can provide a pathway for mitigating the intermittency of renewable energy sources such as wind and solar. In order to operate efficiently, these technologies, which include photoelectrochemical cells, water and CO 2 electrolyzers, fuel cells, and redox flow batteries, require fast charge transfer kinetics at the electrode/electrolyte interface as well as robust ion management in the electrolyte. In conventional electrolyzers and fuel cells, the electrolyte is strongly acidic or basic and ionic current is carried by H + or OH – ions. In contrast, photoelectrodes and electrocatalysts for water splitting are often studied in buffered solutions. The question of ion balance in these systems led us to analyze the polarization losses due to ion concentration gradients in cells that employed various buffer–membrane combinations. Continuously driving the buffer ions across an ionomer membrane not only lowers the buffer capacity of an aqueous electrolyte but also introduces pH gradients that result in significant energy losses. To address the problem, we and other groups have studied the use of reverse-biased bipolar membranes (BPMs) in (photo)electrolytic cells. BPMs consist of an anion exchange layer (AEL) laminated with a cation exchange layer (CEL) and are usually equipped with a catalytic layer in between to accelerate the water dissociation reaction. At the AEL/CEL interface, water dissociates into protons and hydroxide ions, which replenish those consumed at the cathode and anode. Compared to conventional water electrolyzers with proton/anion exchange membranes (PEM/AEM), BPM electrolyzers provide the unique advantage of continuously operating the cathode and anode under different pH conditions, which is desirable when the two electrode reactions have different pH requirements. BPMs also enable the use of buffered electrolytes at pH values that are optimized for electrode stability and product selectivity in applications such as CO 2 electrolysis. Product crossover losses and CO 2 pumping can be dramatically reduced in BPM-based CO 2 electrolyzers, relative to conventional alkaline membranes, by electrostatic repulsion (of anionic products) and electroosmotic drag (for neutral products). BPM-based gas fed CO 2 electrolyzers can achieve high current density, but they suffer from low Faradaic efficiency (FE) due to the acidic local environment of the CEL. This problem can be mitigated by adding an aqueous buffering layer or by creating a weak acid cation exchange film on the CEL face of the membrane. The use of BPMs in fuel cells and redox flow batteries offers some interesting advantages. Configurations with both reverse and forward bias have been studied, but forward bias has been favored due to material compatibility, reaction kinetics, and thermodynamic considerations. The net reaction at the AEL/CEL interface is the acid–base neutralization reaction, which has a high inherent reaction rate constant, but in the BPM is limited to a nanometric space-charge layer and requires efficient catalysis to achieve high current density. Understanding the mechanism of the acid–base neutralization and the opposite process, the water dissociation reaction, will be essential for improving the performance of forward-biased BPMs. In conclusion, this Account reviews our current understanding of the working mechanisms of BPMs and discusses how we can use them to effectively manage ions for various (photo)electrochemical applications.

Yan, Zhifei↗

Superatomic molecules with internal electric fields for light harvesting

Traditional p–n junctions used for photovoltaics require an interface where a light induced electron–hole pair is separated by an electric field. Developing alternative strategies for forming strong internal electric fields for electron–hole pair separation offers the possibility for better performance. We demonstrate that fusing two superatomic clusters with donor/acceptor ligands on opposite sides of the cluster leads to such a strong internal electric field. In two fused metal–chalcogenide Re6S8Cl2(L)4 clusters with donor PMe3 ligands and acceptor CO ligands on the opposite sides of the fused clusters, the electronic levels undergo shifts analogous to band bending in traditional p–n junctions. The fused cluster has a large dipole moment, and an optical spectrum that strongly absorbs excitation above the HOMO–LUMO gap of the fused clusters, but is optically very weak for the lowest energy excitation that can lead to electron–hole pair recombination. This is because the electron is localized on the CO portion of the fused cluster, while the electron–hole pair is localized on the PMe3 side of the cluster. It is shown that the electronic states localized on each side of the cluster can be aligned/misaligned by applying a voltage in different directions, offering diode like characteristics.

14 SOLAR ENERGY↗

Constrained variational optimization of counting-time allocation in sequential scattering measurements: Application to Bonse–Hart USANS

Sequential scattering measurements are often performed under a fixed experimental-time budget, even though the expected count rate varies strongly across the measured coordinate. When the dwell time at each measurement position can be controlled independently, this variation creates a general resource-allocation problem: how should the available time be distributed to minimize the uncertainty of the reconstructed profile? We formulate this problem as a constrained variational optimization for measurements governed by Poisson counting statistics. When each measurement is treated independently, minimizing the averaged squared relative uncertainty yields an inverse-square-root intensity allocation. The formulation is then generalized to include correlations between neighboring measurements and an instrumental resolution operator, leading to an allocation criterion that equalizes the marginal reduction in posterior uncertainty per unit measurement time. Bonse–Hart ultra-small-angle neutron scattering (USANS), in which reciprocal space is sampled sequentially through analyzer-angle stepping, provides an experimentally grounded application. Computational benchmarking shows that the optimized allocation outperforms uniform-time and constant-relative-error strategies, while application to an experimentally measured graphite USANS profile from the Spallation Neutron Source, using Poisson resampling under alternative schedules, demonstrates how counting time should be redistributed toward weak-intensity regions under an identical total duration. The resulting framework applies to sequential scattering and related scanning measurements whenever local dwell times are adjustable and directly determine the measurement uncertainties, and when the relevant correlation and instrumental-response models are available.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗

Metrics and extrapolation of resonant magnetic perturbation thresholds for ELM suppression

This large database study of resonant magnetic perturbation (RMP) edge localized mode (ELM) suppression thresholds in the AUG, DIII-D, EAST, and KSTAR tokamaks details the key strengths and weaknesses of RMP metrics. The RMP ELM suppression database used for this work contains plasma information at the time of transition from ELMing to ELM suppressed states where a clear experimental threshold is identified. The experimental threshold distributions are compared for five metrics: (1) the island overlap width, (2) pedestal top Chirikov overlap, (3) peeling edge displacement, (4) pedestal top resonant drive, and (5) edge dominant mode overlap. The distributions, the regularity of the dependence on RMP coil currents, and the sensitivities of a given metric to equilibrium reconstruction details are compared. The overlap metric proves to be a good compromise between including the appropriate plasma response physics and maintaining a numerical robustness. This quantity does not exhibit clear power-law scalings for projection, but machine learning can assist in predicting thresholds within the existing parameter ranges and providing uncertainty quantification of those predictions. Two new first-principles models, one utilizing a threshold from the non-linear Modified Rutherford equation evaluated at the pedestal top and one utilizing the SLAYER code to calculate the linear tearing threshold from torque balance, offer possible paths to extrapolation beyond the existing database parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Global minimization via classical tunneling assisted by collective force field formation

Simple elements interacting in networks can give rise to intricate emergent behaviors. Examples such as synchronization and phase transitions often apply in many contexts, as many different systems may reduce to the same effective model. Here, we demonstrate such a behavior in a model inspired by memristors. When weakly driven, the system is described by movement in an effective potential, but when strongly driven, instabilities cause escapes from local minima, which can be interpreted as an unstable tunneling mechanism. We dub this collective and nonperturbative effect a “Lyapunov force,” which steers the system toward the global minimum of the potential function, even if the full system has a constellation of equilibrium points growing exponentially with the system size. This mechanism is appealing for its physical relevance in nanoscale physics and for its possible applications in optimization, Monte Carlo schemes, and machine learning.

97 MATHEMATICS AND COMPUTING↗

Evaluating Physics-Informed Neural Network Performance for Seismic Discrimination between Earthquakes and Explosions

In this article, we evaluate adding a weak physics constraint, that is, a physics‐based empirical relationship, to the loss function with a physics‐informed manner in local distance explosion discrimination in the hope of improving the generalization capability of the machine learning (ML) model. We compare the proposed model with the two‐branch model we previously developed, as well as with a pure data‐driven model. Unexpectedly, the proposed model did not consistently outperform the pure data‐driven model. By varying the level of inconsistency in the training data, we find this approach is modulated by the strength of the physics relationship. In conclusion, this result has important implications for how to best incorporate physical constraints in ML models.

58 GEOSCIENCES↗

Electromagnetic control of spin ordered Mn 3 qubits: a density functional study

[Mn 3 O(O 2 CMe)(dpd 3/2 )] 2 is composed of two monomers each of which contain three Mn atoms at the vertices of an equilateral triangle. A full analysis of the electronic and magnetic structure of the dimer shows that each Mn atom carries a local spin of S = 2 while other spin states are energetically much higher. This result suggests application for conventional as well as quantum tasks. A detailed analysis of the electronic and magnetic structure of the monomer, on the other hand, suggests that there are three spin states of S = 1, S = 3/2 and S = 2 per monomer which are energetically competitive. Additionally, we found that while monomer–monomer interactions are very weak, the coupling of monomers via covalent linkers affects both the magnetization and electronic energy levels of monomers. In particular, the isolated monomers prefer a ground state with local spin of S = 1 on Mn atoms and an antiferromagnetically ordered structure while the dimers possess a ground state with local spin of S = 2 on Mn atoms and a ferromagnetically ordered structure. The investigation of the polarizability of both monomer and dimer is examined for antiferromagnetically ordered structures which induces a high dipole moment of 0.08 (a.u.) and 0.16 (a.u.) for monomer and dimer, respectively. The energy of the antiferromagnetic structure is also high compared to other spin-electric molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Strong Impact of Weak Horizontal Convergence on Continental Shallow Convection

Idealized large-eddy simulation (LES) is a basic tool for studying three-dimensional turbulence in the planetary boundary layer. LES is capable of providing benchmark solutions for parameterization development efforts. However, real small-scale atmospheric flows develop in heterogeneous and transient environments with locally varying vertical motions inherent to open multiscale interactive dynamical systems. These variations are often too subtle to detect them by state-of-the-art remote and in situ measurements, and are typically excluded from idealized simulations. The present study addresses the impact of weak [i.e., O(10-6) s-1] short-lived low-level large-scale convergence/divergence perturbations on continental shallow convection. The results show a strong response of shallow nonprecipitating convection to the applied weak large-scale dynamical forcing. Evolutions of CAPE, mean liquid water path, and cloud-top heights are significantly affected by the imposed convergence/divergence. In contrast, evolving cloud-base properties, such as the area coverage and mass flux, are only weakly affected. To contrast those impacts with microphysical sensitivity, the baseline simulations are perturbed assuming different observationally based cloud droplet number concentrations and thus different rainfall. For the tested range of microphysical perturbations, the imposed convergence/divergence provides significantly larger impact than changes in the cloud microphysics. Simulation results presented here provide a stringent test for convection parameterizations, especially important for large-scale models progressing toward resolving some nonhydrostatic effects.

Meteorology & Atmospheric Sciences↗

Pressure–strain interaction. II. Decomposition in magnetic field-aligned coordinates

In weakly collisional and collisionless magnetized plasmas, the pressure–strain interaction describes the rate of conversion between bulk flow and thermal energy density. In this study, we derive an analytical expression for the pressure–strain interaction in a coordinate system with an axis aligned with the local magnetic field. The result is eight groups of terms corresponding to different physical mechanisms that can contribute to the pressure–strain interaction. We provide a physical description of each term. Here, the results are immediately of interest to weakly collisional and collisionless magnetized plasmas and the fundamental processes that happen therein, including magnetic reconnection, magnetized plasma turbulence, and collisionless shocks. The terms in the field-aligned coordinate decomposition are likely accessible to measurement with satellite observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Citizen science coupled with machine learning to quantify green-blue infrastructure cooling potential in Maricopa County, Arizona

Here, this study investigates the spatiotemporal cooling performance of green and blue infrastructure (GBI) in the Dobson Ranch urban neighborhood in Phoenix, Arizona. We leveraged citizen science near-surface (2 m) air temperature (Tair) measurements to train a highly accurate Tair predicting LightGBM machine learning model (R 2 : 0.986, MAE: 0.251 °C, RMSE: 0.585 °C). On June 16, 2024, the park area exhibited approximately 1 °C cooling effect (relative to the neighborhood mean) during both day and night. In contrast, the nearby artificial lake exhibited a stronger cooling effect of 2.4 °C during the day but a slight warming of 0.3 °C at night. At 00:00, locations 50 m downwind of the park were 0.3 °C warmer than the park, while locations 50 m upwind were 0.8 °C warmer. At 11:00, we observed that the downwind area is 0.8 °C cooler and the upwind area is 0.6 °C warmer—at the same 50 m distances relative to the park. We also observed 1 °C cooler and warmer effects respectively at the same 50 m downwind and upwind locations at 19:00 on June 17, 2024. Our data-driven analysis highlights potential limitations of car-traverse measurements, showing that failure to account for temporal variations during the traverse can lead to overestimation of Tair at night and underestimation during the day. Our analysis also showed only a weak correlation (coefficient: 0.48) between Landsat-derived land surface temperature (LST) and model predicted Tair at the time of the local Landsat overpass (∼11.00). This highlights the potential error of relying solely on LST for human thermal exposure analysis—particularly within the heterogenous built-environment.

54 ENVIRONMENTAL SCIENCES↗

Ambient and High Pressure CuNiSb 2 : Metal-Ordered and Metal-Disordered NiAs-Type Derivative Pnictides

The mineral Zlatogorite, CuNiSb 2 , was synthesized in the laboratory for the first time by annealing elements at ambient pressure (CuNiSb 2 -AP). Rietveld refinement of synchrotron powder X-ray diffraction data indicates that CuNiSb 2 -AP crystallizes in the NiAs-derived structure ( P 3 m 1, #164) with Cu and Ni ordering. The structure consists of alternate NiSb 6 and CuSb 6 octahedral layers via face-sharing. The formation of such structure instead of metal disordered NiAs-type structure ( P 6 3 / mm c, #194) is validated by the lower energy of the ordered phase by first-principle calculations. Interatomic crystal orbital Hamilton population, electron localization function, and charge density analysis reveal strong Ni-Sb, Cu-Sb, and Cu-Ni bonding and long weak Sb-Sb interactions in CuNiSb 2 -AP. The magnetic measurement indicates that CuNiSb 2 -AP is Pauli paramagnetic. First-principle calculations and experimental electrical resistivity measurements reveal that CuNiSb 2 -AP is a metal. The low Seebeck coefficient and large thermal conductivity suggest that CuNiSb 2 is not a potential thermoelectric material. Single crystals were grown by chemical vapor transport. The high pressure sample (CuNiSb 2 -8 GPa) was prepared by pressing CuNiSb 2 -AP at 700 °C and 8 GPa. However, the structures of single crystal and CuNiSb 2 -8 GPa are best fit with a disordered metal structure in the P 3 m 1 space group, corroborated by transmission electron microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The origin of metallic conductivity in Pt 3 O 4 : a first principles study

The platinum oxide Pt 3 O 4 exhibits metallic conductivity even though it contains square-planar PtO4 units, which in related oxides such as PtO are usually associated with insulating behavior. To identify the electronic origin of this anomalous metallicity, we performed a comprehensive first-principles study using the PBE and r 2 SCAN functionals together with Hubbard U corrections and spin-orbit coupling (SOC). Structural benchmarks show that r 2 SCAN with SOC and a moderate U value (<4 eV) reproduces the experimental lattice constants and formation enthalpy, whereas larger U values (~8 eV) destabilize the cubic structure. Across all functionals and U values considered in this work, Pt 3 O 4 remains metallic. Analyses of the projected density of states, band structures, charge-density isosurfaces, and bonding characteristics demonstrate that the dominant contribution to the metallic character originates from delocalized Pt–O–Pt hybridized antibonding states at the Fermi level. Direct Pt–Pt interactions are present but contribute less strongly to the conductivity. Bader charge analysis reveals only weak Pt charge disproportionation, consistent with mixed Pt II /Pt III character, and a small charge-transfer energy that prevents localization of the Pt 5d electrons even at elevated U. In contrast, PtO develops a Mott or charge-transfer gap under modest U despite having the same PtO 4 coordination environment. These findings demonstrate that persistent Pt–O–Pt covalency is the primary driver of metallicity in Pt 3 O 4 and support the view that this phase can remain conductive under oxygen reduction and oxygen evolution reaction conditions in fuel cell and electrolyzer environments.

36 MATERIALS SCIENCE↗

Electron Heating in 2D Particle-in-cell Simulations of Quasi-perpendicular Low-beta Shocks

Abstract We measure the thermal electron energization in 1D and 2D particle-in-cell simulations of quasi-perpendicular, low-beta ( β p = 0.25) collisionless ion–electron shocks with mass ratio m i / m e = 200, fast Mach number M ms = 1 –4, and upstream magnetic field angle θ Bn = 55°–85° from the shock normal n ˆ . It is known that shock electron heating is described by an ambipolar, B -parallel electric potential jump, Δ ϕ ∥ , that scales roughly linearly with the electron temperature jump. Our simulations have Δ ϕ ∥ / ( 0.5 m i u sh 2 ) ∼ 0.1 –0.2 in units of the pre-shock ions’ bulk kinetic energy, in agreement with prior measurements and simulations. Different ways to measure ϕ ∥ , including the use of de Hoffmann–Teller frame fields, agree to tens-of-percent accuracy. Neglecting off-diagonal electron pressure tensor terms can lead to a systematic underestimate of ϕ ∥ in our low- β p shocks. We further focus on two θ Bn = 65° shocks: a M s = 4 ( M A = 1.8 ) case with a long, 30 d i precursor of whistler waves along n ˆ , and a M s = 7 ( M A = 3.2 ) case with a shorter, 5 d i precursor of whistlers oblique to both n ˆ and B ; d i is the ion skin depth. Within the precursors, ϕ ∥ has a secular rise toward the shock along multiple whistler wavelengths and also has localized spikes within magnetic troughs. In a 1D simulation of the M s = 4 , θ Bn = 65° case, ϕ ∥ shows a weak dependence on the electron plasma-to-cyclotron frequency ratio ω pe /Ω ce , and ϕ ∥ decreases by a factor of 2 as m i / m e is raised to the true proton–electron value of 1836.

Tran, Aaron (ORCID:0000000334834890)↗

Identification of Differential Equations by Dynamics-Guided Weighted Weak Form with Voting

In the identification of differential equations from data, significant progresses have been made with the weak/integral formulation. In this paper, we explore the direction of finding more efficient and robust test functions adaptively given the observed data. While this is a difficult task, we propose weighting a collection of localized test functions for better identification of differential equations from a single trajectory of noisy observations on the differential equation. We find that using high dynamic regions is effective in finding the equation as well as the coefficients, and propose a dynamics indicator per differential term and weight the weak form accordingly. For stable identification against noise, we further introduce a voting strategy to identify the active features from an ensemble of recovered results by selecting the features that frequently occur in different weighting of test functions. Systematic numerical experiments are provided to demonstrate the robustness of our method.

97 MATHEMATICS AND COMPUTING↗

The importance of localized modes spectral contribution to thermal conductivity in amorphous polymers

Abstract Polymers are a unique class of materials from the perspective of normal mode analysis. Polymers consist of individual chains with repeating units and strong intra-chain covalent bonds, and amorphous arrangements among chains with weak inter-chain van der Waals and for some polymers also electrostatic interactions. Intuitively, this strong heterogeneity in bond strength can give rise to special features in the constituent phonons, but such effects have not been studied deeply before. Here, we use lattice dynamics and molecular dynamics to perform modal analysis of the thermal conductivity in amorphous polymers. We find an abnormally large population of localized modes in amorphous polymers, which is fundamentally different from amorphous inorganic materials. Contrary to the common picture of thermal transport, localized modes in amorphous polymers are found to be the dominant contributors to thermal conductivity. We find that a significant portion of the localization happens within individual chains, but heat is dominantly conducted when localized modes involve two chains. These results suggest localized modes generally play a key role in thermal transport for different polymers. The results provide an alternative perspective on why polymer thermal conductivity is generally quite low and gives insight into how to potentially change it.

36 MATERIALS SCIENCE↗

All-atom molecular dynamics simulations of weak polyionic brushes: influence of charge density on the properties of polyelectrolyte chains, brush-supported counterions, and water molecules

All atom molecular dynamics (MD) simulations of planar Na+-counterion-neutralized polyacrylic acid (PAA) brushes are performed for varying degrees of ionization (and thereby varying charge density) and varying grafting density. Variation in the PE charge density (or degree of ionization) and grafting density leads to massive changes of the properties of the PE molecules (quantified by the changes in the height and the mobility of the PE brushes) as well as the local arrangement and distribution of the brush-supported counterions and water molecules within the brushes. The effect on the counterions is manifested by the corresponding variation of the counterion mobility, counterion concentration, extent of counterion binding to the charged site of the PE brushes, water-in-salt-like structure formation, and counterion-water–oxygen radial distribution function within the PE brushes. On the other hand, the effect on water molecules is manifested by the corresponding variation of water–oxygen–water–oxygen RDF, local water density, water–water and water–PE functional group hydrogen bond networks, static dielectric constant of water molecules, orientational tetrahedral order parameter, and water mobility. Enforcing such varying degree of ionization of weak polyelectrolytes is possible by changing the pH of the surrounding medium. Thus, our results provide insights into the changes in microstructure (at the atomistic level) of weak polyionic brushes at varying pH. Finally, we anticipate that this knowledge will prove to be vital for the efficient design of several nano-scale systems employing PE brushes such as nanomechanical gates, current rectifiers, etc.

42 ENGINEERING↗

An adaptive space-time phase field formulation for dynamic fracture of brittle shells based on LR NURBS

Here, we present an adaptive space-time phase field formulation for dynamic fracture of brittle shells. Their deformation is characterized by the Kirchhoff–Love thin shell theory using a curvilinear surface description. All kinematical objects are defined on the shell’s mid-plane. The evolution equation for the phase field is determined by the minimization of an energy functional based on Griffith’s theory of brittle fracture. Membrane and bending contributions to the fracture process are modeled separately and a thickness integration is established for the latter. The coupled system consists of two nonlinear fourth-order PDEs and all quantities are defined on an evolving two-dimensional manifold. Since the weak form requires C 1 -continuity, isogeometric shape functions are used. The mesh is adaptively refined based on the phase field using Locally Refinable (LR) NURBS. Time is discretized based on a generalized-α method using adaptive time-stepping, and the discretized coupled system is solved with a monolithic Newton–Raphson scheme. Finally, the interaction between surface deformation and crack evolution is demonstrated by several numerical examples showing dynamic crack propagation and branching.

42 ENGINEERING↗