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At least 523 records · Page 29

Tuning Alkaline Anion Exchange Membranes through Crosslinking: A Review of Synthetic Strategies and Property Relationships

Alkaline anion exchange membranes (AAEMs) are an enabling component for next-generation electrochemical devices, including alkaline fuel cells, water and CO2 electrolyzers, and flow batteries. While commercial systems, notably fuel cells, have traditionally relied on proton-exchange membranes, hydroxide-ion conducting AAEMs hold promise as a method to reduce cost-per-device by enabling the use of non-platinum group electrodes and cell components. AAEMs have undergone significant material development over the past two decades; however, challenges remain in the areas of durability, water management, high temperature performance, and selectivity. In this review, we survey crosslinking as a tool capable of tuning AAEM properties. While crosslinking implementations vary, they generally result in reduced water uptake and increased transport selectivity and alkaline stability. We survey synthetic methodologies for incorporating crosslinks during AAEM fabrication and highlight necessary precautions for each approach.

08 HYDROGEN↗

Grid-Interactive Multi-Zone Building Control Using Reinforcement Learning with Global-Local Policy Search

In this paper, we develop a grid-interactive multi-zone building controller based on a deep reinforcement learning (RL) approach. The controller is designed to facilitate building operation during normal conditions and demand response events, while ensuring occupants comfort and energy efficiency. We leverage a continuous action space RL formulation, and devise a two-stage global-local RL training framework. In the first stage, a global fast policy search is performed using a gradient-free RL algorithm. In the second stage, a local fine-tuning is conducted using a policy gradient method. In contrast to the state-of-the-art model predictive control (MPC) approach, the proposed RL controller does not require complex computation during real-time operation and can adapt to nonlinear building models. We illustrate the controller performance numerically using a five-zone commercial building.

30 DIRECT ENERGY CONVERSION↗

Direct Observation of Magnetic Bubble Lattices and Magnetoelastic Effects in van der Waals Cr 2 Ge 2 Te 6

Abstract Ferromagnetic van der Waals (vdW) materials are of large current interest for the fundamental study of low‐dimensional magnetism and for potential applications in multilayer heterostructures. Cr 2 Ge 2 Te 6 (CGT) is particularly exciting because it is a ferromagnetic semiconductor with tunable electronic and magnetic properties. Controlling the magnetic domain structure of CGT is a requirement for understanding its novel interface physics and for tuning behavior for potential devices. Herein, cryo‐Lorentz transmission electron microscopy is performed in the temperature range of 12–50K to directly image the magnetic domain structures in CGT. A rich phase diagram of domain structures including stripe domains, magnetic bubble lattices of mixed‐chirality, and topologically‐protected lattices of homochiral magnetic bubbles is observed. The types and chiralities of the bubbles can be controlled by topographical changes in the CGT flakes. Additionally, it is observed that in‐plane strain and magnetoelastic coupling can align and organize both bubble lattices and stripe domains. This study provides insights into creating and controlling complex magnetic domain structures for integration into multilayer heterostructures and for future studies of 2D magnetism.

36 MATERIALS SCIENCE↗

Advanced Low‐Flammable Electrolytes for Stable Operation of High‐Voltage Lithium‐Ion Batteries

Abstract Despite being an effective flame retardant, trimethyl phosphate (TMP a ) is generally considered as an unqualified solvent for fabricating electrolytes used in graphite (Gr)‐based lithium‐ion batteries as it readily leads to Gr exfoliation and cell failure. In this work, by adopting the unique solvation structure of localized high‐concentration electrolyte (LHCE) to TMP a and tuning the composition of the solvation sheaths via electrolyte additives, excellent electrochemical performance can be achieved with TMP a ‐based electrolytes in Gr∥LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells. After 500 charge/discharge cycles within the voltage range of 2.5–4.4 V, the batteries containing the TMP a ‐based LHCE with a proper additive can achieve a capacity retention of 85.4 %, being significantly higher than cells using a LiPF 6 ‐organocarbonates baseline electrolyte (75.2 %). Meanwhile, due to the flame retarding effect of TMP a , TMP a ‐based LHCEs exhibit significantly reduced flammability compared with the conventional LiPF 6 ‐organocarbonates electrolyte.

Jia, Hao↗

Advanced Low-Flammable Electrolytes for Stable Operation of High-Voltage Lithium-Ion Batteries

Despite being an effective flame retardant, trimethyl phosphate (TMP a ) is generally considered as an unqualified solvent for fabricating electrolytes used in graphite (Gr) based lithium ion batteries as it readily leads to Gr exfoliation and cell failure. In this work, by adopting the unique solvation structure of localized high-concentration electrolyte (LHCE) to TMP a and tuning the composition of the solvation sheath via electrolyte additive, excellent electrochemical performance can be achieved with TMPa based electrolytes in Gr||LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells. After 500 charge/discharge cycles within the voltage range of 2.5-4.4 V, the batteries containing TMPa based LHCEs with proper additive can achieve a capacity retention of 85.4%, being significantly higher than cells using a LiPF 6 -organocarbonates baseline electrolyte (75.2%). Meanwhile, due to the flame retarding effect of TMP a , TMP a based LHCEs exhibit significantly reduced flammability compared with the conventional LiPF 6 -organocarbonates electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A comparative study on cubic and tetragonal Ce-ZrO 2 supported Rh catalysts for N 2 O decomposition

Zirconium oxide (ZrO 2 ) exhibits strong synergy with cerium oxide (CeO 2 ), acting as a structural and electronic promoter during catalytic redox reactions. As a result, Ce-ZrO 2 composite oxides are widely used as supports in various catalytic systems. In our previous work, we demonstrated that the incorporation of Zr 4+ into the CeO 2 lattice significantly enhanced Rh dispersion, improved redox ability, and stabilized surface Rh species, which collectively boosted the de-N 2 O activity of Rh/Ce-ZrO 2 catalysts. Building on these findings, the present study emphasizes that the crystallographic phase of Ce-ZrO 2 , governed by the Ce/Zr ratio, plays a decisive role in tuning the physicochemical environment of Rh active sites and thereby optimizing catalytic performance. In conclusion, tailoring the Ce/Zr ratio to favor the cubic fluorite structure emerges as a promising strategy for the rational design of highly active and stable catalysts for N 2 O decomposition and potentially other redox-sensitive environmental applications.

36 MATERIALS SCIENCE↗

Daylight simulation workflows incorporating measured bidirectional scattering distribution functions

Daylight predictions of architectural spaces depend on good estimates of light transfer through skylights, windows and other fenestration systems. For clear glazing and painted surfaces, parametric transmission and reflection models have proven adequate, but there are many cases where light-scattering, semi-specular shading and daylighting materials defy simple characterization. Something as commonplace as fabric roller shades and venetian blinds may turn daylight prediction into guesswork, and numerous advanced systems on the market tuned specifically to enhance daylight are not sufficiently characterized to distinguish their performance. In this paper, we describe new tools available to handle novel and specialized fabrics, materials, and devices using data-driven modelling of bi-directional scattering distribution functions (BSDFs). These representations are usually tabulated at constant or adjustable angular resolution for efficient point-in-time and annual daylight simulations. We describe a variety of BSDF simulation workflows, including some of the tools and methods that make advanced analysis possible, and highlight some of the current challenges. We conclude with a discussion of future work and how such data might be created and shared worldwide.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extremum-Seeking-Based Ultra-local Model Predictive Control and Its Application to Electric Motor Speed Regulation

Electric vehicle (EV) market is rapidly expanding. As a critical component of EV, an electric motor needs to accurately follow a reference speed signal while respecting the electrical current constraint for safety. Those requirements are usually formulated as a model predictive control (MPC) problem. However, the performance of traditional model-based MPC depends on the accuracy of the system model, which may not always be guaranteed in reality. Therefore, we utilize a data-driven, model-free predictive control strategy, called ultra-local MPC (ULMPC), to control the speed of an electric motor. To further enhance the control performance of ULMPC, we employ the extremum-seeking control (ESC) to tune the control gain of the ULMPC online. Simulation and hardware experiments demonstrate the enhancement of the extremum-seeking-based ULMPC over a constant-gain ULMPC.

Zhou, Yujing↗

Bimetallic NiCu catalysts supported on a Metal-Organic framework for Non-oxidative ethanol dehydrogenation

Non-oxidative ethanol dehydrogenation is a promising route to produce acetaldehyde and hydrogen from sustainable feedstock. Bimetallic NiCu catalysts have shown high efficiency and selectivity for this chemical transformation. In this study, we leverage the high porosity and uniform catalyst deposition sites on a Zr-based metal–organic framework (MOF) catalyst support, NU-1000, to understand how the changes in Cu:Ni ratio affects the reactivity for non-oxidative ethanol dehydrogenation. We found that increasing the Ni 2+ concentration significantly reduces the activation energy of the reaction due to the role of Ni 2+ in suppressing the onset of Cu reduction. Furthermore, this study illustrates how MOFs can be used as catalyst supports to fine-tune the catalyst compositions and understand their effect on the overall catalytic performances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rate-induced aging effects on Parallel-Plate Avalanche Counter (PPAC) caused by heavy ion beams

The Facility for Rare Isotope Beams (FRIB) is one of the premier scientific user facilities for nuclear science with radioactive beams, capable of producing most (approximately 80%) of the isotopes expected to exist, from oxygen to uranium, at energies up to 200 MeV/u. With the increase in beam power from the present 10 kW to the planned 400 kW, FRIB experiments are about to enter a new era. An unprecedented rate capability as well as stable performance of all the planned instrumentation intended for beam diagnostics and beam tuning is required at the expected high beam intensities (> 1 MHz). A summary of aging phenomena at high heavy-ion beam rates observed in the Advanced Rare Isotope Separator (ARIS) detectors for beam diagnostics, including Parallel Plate Avalanche Counters (PPAC) and plastic scintillation for time-of-flight measurements, is discussed. Current research and development project to mitigate rate-induced aging are presented.

Aging effects↗

Automated power-following control for nuclear thermal propulsion startup and shutdown using MOOSE-based applications

This paper describes an investigation of various automated control strategies applied to a full-core multiphysics Griffin/Bison/RELAP-7 model of a prototypical nuclear thermal propulsion system. In all cases, control is achieved by actuating control drums based on the demanded power and predicted quantities from the numerical model. One key finding is that hybrid proportional integral derivative controllers – a novel type of controller that uses both power and reactivity predicted signals – can demonstrate a level of performance rivaling that of period-generated control. The former requires parameter tuning, while the latter mostly necessitates providing reactivity coefficients and temperature rates of change, which could be very challenging to accurately measure in real-time. In addition, decay heat plays an important role in determining cooling requirements during cooldown phases. A decay heat model, accounting for burn time and throttling, was derived, and is incorporated within the model to simulate the steady-state and shutdown phases and satisfyingly follow the power demand. However, temperature overshoots and non-constant specific impulse during throttling will necessitate further improvements.

33 ADVANCED PROPULSION SYSTEMS↗

The value of human data annotation for machine learning based anomaly detection in environmental systems

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

54 ENVIRONMENTAL SCIENCES↗

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited- state property predictions. The γ-tuning procedure in the gas phase is well established. However, no agreement on the best γ- tuning procedure has been made when considering the solvent effect with implicit solvent models like the polarizable continuum model (PCM). To answer that question, this study created a diverse dataset with 937 molecules with experimental solutionphase UV/vis absorption spectra. Three γ-tuning methods, the gasphase γ-tuning (GPγT), the partial vertical γ-tuning (PVγT), and the strict vertical γ-tuning (SVγT), were evaluated for the ωPBEh functional over the entire dataset. Additional benchmarks are done for the optimally tuned screened range-separated hybrid combined with the PCM approach (SRSH-PCM) and the solvation-mediated tuning procedure (sol-med-OT). Our findings revealed that the optimal γ-values obtained by the PVγT and the SVγT are significantly smaller than the GPγT. This trend holds consistently across all molecules in our dataset, and we explained the origin of this phenomenon. TDDFT calculations with PVγTand SVγT-tuned γ-values and default global Fock exchange fraction achieve superior performance compared to those using GPγTtuned or default γ and slightly outperform SRSH-PCM and sol-med-OT with similar or lesser computational cost. Furthermore, we found that the smaller γ-values from SVγT captured the expected 1/(εR) asymptotic behavior in the solution phase, resulting in accurate prediction of solution-phase CT excitations, consistent with the screened asymptote behavior encoded in SRSH-PCM. These results show that SVγT is the best scheme for high-throughput UV/vis absorption spectrum calculations using the ωPBEh functional from a data-driven perspective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Chemical and Mechanical Control of Phase Stability in Lanthanide-Substituted BiVO 4

Doping is widely used to enhance the photoelectrochemical performance of BiVO 4 , yet solubility limits and polymorphic stability constrain compositional tuning. Here, in this study, the role of trivalent cation substitution (Ln = La, Nd, Dy, Ho, Y) on pressure-induced phase transformations in Bi 1–x Ln x VO 4 (x ≤ 0.5) is described. Powder X-ray and neutron diffraction reveal that increasing Ln content stabilizes the tetragonal zircon-type polymorph under ambient conditions, while applied pressures of up to ∼5 GPa promote conversion to the monoclinic fergusonite-type polymorph. In-situ neutron diffraction on Bi 0.8 La 0.2 VO 4 shows a reversible monoclinic to tetragonal transition near 2–3 GPa with a bulk modulus of 147 GPa. The extent of conversion depends strongly on dopant identity, concentration, and synthetic route, with mixed-phase solid-state samples converting more efficiently than phase-pure coprecipitated materials. These results demonstrate pressure as a viable pathway to access metastable, doped BiVO 4 compositions beyond conventional solubility limits.

Sypkes, Kathryn I. [University of Sydney, NSW (Aus↗

Fine-tuned local coordination environment of Pt single atoms on ceria controls catalytic reactivity

Constructing single atom catalysts with fine-tuned coordination environments can be a promising strategy to achieve satisfactory catalytic performance. Herein, via a simple calcination temperature-control strategy, CeO 2 supported Pt single atom catalysts with precisely controlled coordination environments are successfully fabricated. The joint experimental and theoretical analysis reveals that the Pt single atoms on Pt 1 /CeO 2 prepared at 550 °C (Pt/CeO 2 -550) are mainly located at the edge sites of CeO 2 with a Pt–O coordination number of ca. 5, while those prepared at 800 °C (Pt/CeO 2 -800) are predominantly located at distorted Ce substitution sites on CeO 2 terrace with a Pt–O coordination number of ca. 4. Pt/CeO 2 -550 and Pt/CeO 2 -800 with different Pt 1 -CeO 2 coordination environments exhibit a reversal of activity trend in CO oxidation and NH 3 oxidation due to their different privileges in reactants activation and H 2 O desorption, suggesting that the catalytic performance of Pt single atom catalysts in different target reactions can be maximized by optimizing their local coordination structures.

36 MATERIALS SCIENCE↗

A comprehensive approach for elucidating the interplay between 4f n +1 and 4f n 5d 1 configurations in Ln 2+ complexes

Lanthanides (Ln) are typically found in the +3 oxidation state. However, in recent decades, their chemistry has been expanded to include the less stable +2 oxidation state across the entire series except promethium (Pm), facilitated by the coordination of ligands such as trimethylsilylcyclopentadienyl, C 5 H 4 SiMe 3 (Cp'). The [LnCp' 3 ] complexes have been the workhorse for the synthesis and theoretical study of the fundamental aspects of divalent lanthanide chemistry, where experimental and computational evidence have suggested the existence of different ground state (GS) configurations, 4f n+1 or 4f n 5d 1 , depending on the specific metal. Standard reduction potentials and 4f n+1 to 4f n 5d 1 promotion energies have been two factors usually considered to rationalize the occurrence of these variable GS configurations, however the driving force behind this phenomenon is still not clear. In this work we present a comprehensive theoretical approach to shed light on this matter using the [LnCp 3 ] - model systems. We begin by calculating 4f n+1 to 4f n 5d 1 promotion energies and successfully correlate them with existing experimental data. Furthermore, we analyze how changes in the GS charge distribution between the Ln ions, LnCp 3 and the reduced [LnCp 3 ] - complexes (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) correlate with experimental trends in redox potentials and the calculated promotion energies. For this purpose, a comprehensive theoretical work that includes relativistic ligand field density functional theory (LFDFT) and relativistic ab initio wavefunction methods was performed. This study will help the rational design of suitable environments to tune the different GS configurations as well as modulating the spectroscopic properties of new Ln 2+ complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗

Mixed-species charge and baryon balance functions studies with PYTHIA

Mixed species charge and baryon balance functions are computed based on proton-proton ( p p ) collisions simulated with the PYTHIA8 model. Simulations are performed with selected values of the collision energy s and the Monash tune and the ropes and shoving modes of PYTHIA8 to explore whether such measurements provide useful new information and constraints on mechanisms of particle production in p p collisions. Charge balance functions are studied based on mixed pairs of pions, kaons, and protons, whereas baryon balance functions are computed for mixed low mass strange and nonstrange baryons. Both charge and baryon balance functions of mixed particle pairs feature shapes and amplitudes that sensitively depend on the particle considered owing largely to the particle production mechanisms implemented in PYTHIA. The evolution of balance functions integrals with the longitudinal width of the acceptance are presented and one finds that sums of such integrals for a given reference particle obey expected sum rules for both charge and baryon balance functions. Additionally, both types of balance functions are found to evolve in shape and amplitude with increasing collision energy s and the PYTHIA tunes considered. Published by the American Physical Society 2024

Physics↗