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At least 91 records · Page 5

Understanding the evolution of double perovskite band structure upon dimensional reduction

Recent investigations into the effects of dimensional reduction on halide double perovskites have revealed an intriguing change in band structure when the three-dimensional (3D) perovskite is reduced to a two-dimensional (2D) perovskite with inorganic sheets of monolayer thickness (n = 1). The indirect bandgap of 3D Cs 2 AgBiBr 6 becomes direct in the n = 1 perovskite whereas the direct bandgap of 3D Cs 2 AgTlBr 6 becomes indirect at the n = 1 limit. Here, we apply a linear combination of atomic orbitals approach to uncover the orbital basis for this bandgap symmetry transition with dimensional reduction. We adapt our previously established method for predicting band structures of 3D double perovskites for application to their 2D congeners, emphasizing new considerations required for the 2D lattice. In particular, we consider the inequivalence of the terminal and bridging halides and the consequences of applying translational symmetry only along two dimensions. The valence and conduction bands of the layered perovskites can be derived from symmetry adapted linear combinations of halide p orbitals propagated across the 2D lattice. The dispersion of each band is then determined by the bonding and antibonding interactions of the metal and halide orbitals, thus affording predictions of the essential features of the band structure. We demonstrate this analysis for 2D Ag–Bi and Ag–Tl perovskites with sheets of mono- and bilayer thickness, establishing a detailed understanding of their band structures, which enables us to identify the key factors that drive the bandgap symmetry transitions observed at the n = 1 limit. Importantly, these insights also allow us to make the general prediction that direct → indirect or indirect → direct bandgap transitions in the monolayer limit are most likely in double perovskite compositions that involve participation of metal d orbitals at the band edges or that have no metal-orbital contributions to the valence band, laying the groundwork for the targeted realization of this phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.

Austria, Phillipe [ORNL] (ORCID:0000000236223973)↗

Cloud Radiative Effects on MJO Development in DYNAMO

Observed Madden-Julian Oscillation (MJO) events are examined with the aid of regional model simulations to understand the role of cloud radiative effects in the MJO development. The importance of this role is demonstrated by the absence of MJO in the model simulations that contain no cloud radiative effects. Comparisons of model simulations with and without the cloud radiative effects and observation help identify the major processes arising from those effects. Those processes develop essentially from heating in the upper-troposphere due to shortwave absorption within anvil clouds in the upper troposphere and the convergence of longwave radiation in the middle-upper troposphere, with a peak at 300-hPa, during deep convection. First, that heating adds extra buoyancy and accelerates the rising motion in the upper troposphere in deep convection. The vertical acceleration in the upper troposphere creates a vacuum effect and demands for more deep convection to develop. Second, in response to that demand and required by mass balance arises the large-scale horizontal and vertical mass, moisture, and energy convergence. It strengthens deep convection and, with the feedback from continuing cloud radiative effect, creates conditions that can perpetuate deep convection and MJO development. That perpetuation does not occur however because those processes arising from the cloud radiative heating in the upper troposphere stabilize the troposphere till it supports no further deep convection. Weakening deep convection reduces cloud radiative effects. The subsequent reduction of the vacuum effect in the upper troposphere diminishes deep convection completing an MJO cycle. These results advance our understanding of the development of the MJO in the radiative-convective system over warm waters in the tropics. They show that while the embryo of intraseasonal oscillation may exist in the system its growth/development is largely dependent on cloud radiative effects and feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Improving Performance and Durability of Low Temperature Direct Ammonia Fuel Cells: Effect of Backpressure and Oxygen Reduction Catalysts

Low temperature direct ammonia fuel cells (DAFCs) are attractive for transportation applications. The primary obstacle to their commercial use is their low performance and poor durability. In the present work, we focus on improving DAFCs performance and durability by examining the effect of operating backpressure and oxygen reduction reaction (ORR) catalysts such as Acta 4020, Pd/C and Pt/C. DAFCs with Acta 4020 cathode can reach a peak power density of 390 mW cm -2 which is among the best reported performance, but they can be operated for a period of 11 h at 300 mA cm -2 . DAFCs with Pd/C cathode offer a moderate performance with a peak power density of 304 mW cm -2 , but has a much improved durability - a continuous operation for up to 36 h with a slow decay rate of ~1 mV h -1 at 300 mA cm -2 . In addition, the degradation pathways for DAFCs with Pd/C cathode are probed by characterizing the initial and final electrodes by XPS, suggesting that cathodic Pd dissolution occurs during the durability test.

Electrochemistry↗

Assessment of the driving factors of CO 2 mitigation costs of household biogas systems in China: A LMDI decomposition with cost analysis model

China has been placing a substantial focus on biogas for reducing energy consumption and carbon dioxide (CO 2 ) emissions. The operation mode of biogas systems may make the CO 2 reduction target over-optimistic. There is limited research to investigate the influential factors that may be causing the gap between the actual and theoretical CO 2 reduction costs of biogas systems in China. In this research, by using field survey data of 209 biogas users and 489 non-biogas users from 19 villages in 2015, the gap between actual and theoretical unit CO 2 reduction cost is quantified at approximately 156 USD/t CO 2 . By employing the Logarithmic Mean Divisia Index I (LMDI) model, it is found that both the cost effect (48%) and the reduction effect (52%) contribute to the unit CO 2 reduction cost gap. Furthermore, four influential factors–household labor, accessibility to the energy resource, acceptance of biogas technology, and subsidy–significantly narrow the gap between actual and theoretical CO 2 reduction costs, while the levelized subsidy contributes to widening the gap. On average, biogas systems should be operated for at least four years and the substitution rate should be more than 67% in order to keep the gap between actual and theoretical CO 2 reduction costs under 50%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Chromium isotope fractionation during reduction of Chromium(VI) by Iron(II/III)-bearing clay minerals

Chromium stable isotope ratios are used to trace the reduction of Cr(VI) to Cr(III) in both ancient and modern systems. However, quantitative interpretation of Cr isotopic signatures has been stymied by the large variability in isotopic fractionation factors for Cr(VI) reduction by different reductants. Here we determine Cr isotope fractionation factors during Cr(VI) reduction by Fe(II/III)-bearing clay minerals, which are abundant in subsurface environments. Several variables were tested: pH, total Fe content of the clay, and the fraction of reduced Fe within the clay (Fe(II)/Fe(total)). The latter controls the standard reduction potential of the clay. Our results demonstrate that neither pH nor total Fe content of the clay have major effects on isotopic fractionation. In contrast, as the effective standard reduction potential of the clay and thus the standard free energy of Cr(VI) reduction become more negative, Cr isotope fractionation factors decrease in magnitude from - 4.9 to -1.3‰ according to a linear free energy relationship. This linear free energy relationship can be predicted from Marcus electron transfer theory and allows first-order predictions of Cr isotope fractionation factors to be made from the standard reduction potential or Fe(II)/Fe(total) of a clay, potentially improving our ability to model Cr isotope signatures in geochemical systems. Chromium is the first isotope system to show such a linear free energy relationship over a diverse range of reductants, including both aqueous and solid-phase reductants, and may provide a model for determining other redox-driven kinetic isotope effects in environmentally important isotope systems.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Pore-Scale Transport Effects in Electrochemical CO 2 Reduction on Gold via Coupled Microkinetic-Transport Modeling

A pore-resolved modeling framework is developed to quantify how pore-scale transport affects the intrinsic microkinetics of CO 2 -to-CO on Au. A DFT-informed microkinetic model is coupled self-consistently to a Generalized-Modified Poisson–Nernst–Planck (GMPNP) transport description in a single, electrolyte-filled cylindrical pore, allowing local concentrations and potential to feed back into site-specific reaction rates. FIB-SEM is used to determine pore sizes within realistic electrode materials. Across pore diameters, d p = 10–6000 nm, the surface-averaged CO 2 reduction rate is systematically reduced relative to the ideal microkinetic baseline where mass transport is not accounted for; the effectiveness factor 𝜂 𝑠,CO 2 , which quantifies this ratio, decreases rapidly at more negative potentials and is about 1% near −1.0 V vs SHE due to reactant depletion. Spatial maps reveal pore-bulk alkalization that emerges at higher cathodic bias, with a small, near-wall pH dip due to electrostatic repulsion of hydroxide at the cathode interface. For a fixed aspect ratio L p /d p , narrower pores exhibit larger 𝜂 𝑠,CO 2 by shortening diffusion paths, whereas variations in the aspect ratio L p /d p play a secondary role. A dimensionless analysis (surface/bulk Damköhler numbers) delineates operating regimes. In conclusion, this work offers a concept for incorporating microkinetic models into homogenized porous-electrode models through effectiveness factors and pore-size distribution.

Au-catalyst↗

Functionalized carbon nanotubes for thermionic emission and cooling applications

Barium strontium oxide-coated carbon nanotubes (CNTs) were implemented as a work function lowering and field enhancing functional coating on a coiled tungsten filament to create a new thermionic cathode. This cathode resembles conventional oxide cathodes in structure. It has the same coiled tungsten filament as a conventional oxide cathode but uses barium strontium oxide-coated CNTs instead of the traditional barium strontium calcium oxide powder mixture as an emissive coating. The cathode produces a strong thermionic emission. At 1395 K and 2.5 V/μm, the thermionic emission current of 0.87 A or current density of 2.9 A/cm 2 was obtained from this oxide-coated CNT cathode. This level of emission is about three times as large as a conventional oxide cathode operating at similar temperature and field strength. Strong thermionic emissions from the cathode also lead to a large thermionic cooling effect. Temperature reduction as large as 90° was observed from the cathode surface when it was emitting electrons. Strong thermionic emission and a large cooling effect obtained are the result of the combination of the low work function of barium strontium oxide (1.6 eV) and the large field effect induced by the CNTs. Plasma enhanced chemical vapor deposition was used to grow CNTs, and magnetron sputtering deposition was used to deposit the barium strontium oxide functional coating; details of the cathode fabrication are presented to illustrate both the versatility of the processing techniques and the adaptability of barium strontium oxide-coated CNTs as a functional coating. Finally, measurements on thermionic emission and thermionic cooling of the cathode are also presented.

36 MATERIALS SCIENCE↗

Coherency-Constrained Spectral Clustering for Power Network Reduction

This paper presents a methodology for reducing the complexity of large-scale power network models using spectral clustering, aggregation of electrical components, and cost function approximation. Two approaches are explored using unconstrained and constrained spectral clustering to determine areas for effective system reduction. Once the system areas are determined, both loads and generators by type are aggregated, and their new cost function is approximated through polynomial curve-fitting or statistical methods. The performance of reduced networks is evaluated in terms of their ability to follow the true daily cost of the original system over a 24-hour period considering a set of several days. Two test systems are taken as test beds. Application of the methodology to a modified version of the IEEE 39-bus system reduces it from 17 generators to a 4-bus system and 9 generators with about 93% of accuracy. Similarly, the IEEE 118-bus system is reduced from 19 generators to a 3-bus system with three aggregated units achieving over 99% of accuracy. These findings address scalability challenges and enhance accuracy for high and mid-loading level conditions, and by aggregating thermal units with similar cost functions.

42 ENGINEERING↗

Comparison of wild-type KT2440 and genome-reduced EM42 Pseudomonas putida strains for muconate production from aromatic compounds and glucose

Pseudomonas putida KT2440 is a robust, aromatic catabolic bacterium that has been widely engineered to convert bio-based and waste-based feedstocks to target products. Towards industrial domestication of P. putida KT2440, rational genome reduction has been previously conducted, resulting in P. putida strain EM42, which exhibited characteristics that could be advantageous for production strains. Here, we compared P. putida KT2440-and EM42-derived strains for cis,cis-muconic acid production from an aromatic compound, p-coumarate, and in separate strains, from glucose. To our surprise, the EM42-derived strains did not outperform the KT2440-derived strains in muconate production from either substrate. In bioreactor cultivations, KT2440-and EM42-derived strains produced muconate from p-coumarate at titers of 45 g/L and 37 g/L, respectively, and from glucose at 20 g/L and 13 g/L, respectively. To provide additional insights about the differences in the parent strains, we analyzed growth profiles of KT2440 and EM42 on aromatic compounds as the sole carbon and energy sources. In general, the EM42 strain exhibited reduced growth rates but shorter growth lags than KT2440. We also observed that EM42-derived strains resulted in higher growth rates on glucose compared to KT2440-derived strains, but only at the lowest glucose concentrations tested. Transcriptomics revealed that genome reduction in EM42 had global effects on transcript levels and showed that the EM42-derived strains that produce muconate from glucose exhibit reduced modulation of gene expression in response to changes in glucose concentrations. Overall, our results highlight that additional studies are warranted to understand the effects of genome reduction on microbial metabolism and physiology, especially when intended for use in production strains.

09 BIOMASS FUELS↗

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗

Beyond n-dopants for organic semiconductors: use of bibenzo[ d ]imidazoles in UV-promoted dehalogenation reactions of organic halides

2,2’-Bis(4-dimethylaminophenyl)- and 2,2'-dicyclohexyl-1,1',3,3'-tetramethyl-2,2',3,3'-tetrahydro-2,2'-bibenzo[ d ]imidazole ((N-DMBI) 2 and (Cyc-DMBI) 2 ) are quite strong reductants with effective potentials of ca. −2 V vs ferrocenium/ferrocene, yet are relatively stable to air due to the coupling of redox and bond-breaking processes. Here, we examine their use in accomplishing electron transfer-induced bond-cleavage reactions, specifically dehalogenations. The dimers reduce halides that have reduction potentials less cathodic than ca. −2 V vs ferrocenium/ferrocene, especially under UV photoexcitation (using a 365 nm LED). In the case of benzyl halides, the products are bibenzyl derivatives, whereas aryl halides are reduced to the corresponding arenes. The potentials of the halides that can be reduced in this way, quantum-chemical calculations, and steady-state and transient absorption spectroscopy suggest that UV irradiation accelerates the reactions via cleavage of the dimers to the corresponding radical monomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ ATR–SEIRAS of Carbon Dioxide Reduction at a Plasmonic Silver Cathode

Illumination of a voltage-biased plasmonic Ag cathode during CO 2 reduction results in a suppression of the H 2 evolution reaction while enhancing CO 2 reduction. This effect has been shown to be photonic rather than thermal, but the exact plasmonic mechanism is unknown. Here in this paper, we conduct an in situ ATR–SEIRAS (attenuated total reflectance–surface-enhanced infrared absorption spectroscopy) study of a sputtered thin film Ag cathode on a Ge ATR crystal in CO 2 -saturated 0.1 M KHCO 3 over a range of potentials under both dark and illuminated (365 nm, 125 mW cm –2 ) conditions to elucidate the nature of this plasmonic enhancement. We find that the onset potential of CO 2 reduction to adsorbed CO on the Ag surface is -0.25 V RHE and is identical in the light and the dark. As the production of gaseous CO is detected in the light near this onset potential but is not observed in the dark until -0.5 V RHE , we conclude that the light must be assisting the desorption of CO from the surface. Furthermore, the HCO 3 – wavenumber and peak area increase immediately upon illumination, precluding a thermal effect. We propose that the enhanced local electric field that results from the localized surface plasmon resonance (LSPR) is strengthening the HCO 3 – bond, further increasing the local pH. This would account for the decrease in H 2 formation and increase the CO 2 reduction products in the light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemoselective and Site-Selective Reductions Catalyzed by a Supramolecular Host and a Pyridine–Borane Cofactor

Supramolecular catalysts emulate the mechanism of enzymes to achieve large rate accelerations and precise selectivity under mild and aqueous conditions. While significant strides have been made in the supramolecular host-promoted synthesis of small molecules, applications of this reactivity to chemoselective and site-selective modification of complex biomolecules remain virtually unexplored. We report here a supramolecular system where coencapsulation of pyridine-borane with a variety of molecules including enones, ketones, aldehydes, oximes, hydrazones, and imines effects efficient reductions under basic aqueous conditions. Furthermore, upon subjecting unprotected lysine to the host-mediated reductive amination conditions, we observed excellent ε-selectivity, indicating that differential guest binding within the same molecule is possible without sacrificing reactivity. Inspired by the post-translational modification of complex biomolecules by enzymatic systems, we then applied this supramolecular reaction to the site-selective labeling of a single lysine residue in an 11-amino acid peptide chain and human insulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effectiveness of fat grafting in scar reduction: A systematic review and meta‐analysis

Abstract Background Scar brings great physical and mental pain to patients. Fat grafting may be a new and simple way to treat scar. This review aimed to systematically evaluate the correlation between fat grafting and scar reduction. Methods The author searched Chinese and English literature databases such as CNKI, Wanfang Data, Cqvip, Pubmed, Web of Science, Embase, CBM, etc. for articles published in the period from 2011 to 2021 about the randomized controlled trials (RCTs) to assess the effect of fat grating on scar reduction, and then performed meta‐analysis with Review Manager 5.4. Results A total of nine articles were included in the assessment of the effect of fat grafting on scar reduction, with meta‐analysis suggesting statistical significance (OR = 5.63, 95% CI: 3.01–10.53, p < 0.01). There was statistical significance in the difference observed between the simple fat grating group ( p = 0.004) and the group of existing therapies combined with fat grafting ( p < 0.0001). Conclusion Fat grafting may be a good method for scar treatment, especially when it's combined with other therapies. Still, due to the limitations of included RCTs, more large‐scale high‐quality RCTs must be carried out before solid conclusions can be drawn.

Zhang, Xiaoyuan↗