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At least 487 records · Page 27

Performance-limiting formation dynamics in mixed-halide perovskites

Wide-bandgap (WBG) mixed-halide perovskites as the front cell absorber are accomplishing perovskite-based tandem solar cells with over 29% power conversion efficiency. However, their large voltage deficits limit their ultimate performance. Only a handful of studies probe the fundamental mechanisms underlying the voltage deficits, which remain an unsolved challenge in the field. In this study, we investigate the formation dynamics and defect physics of WBG mixed-halide perovskites in contrast with their corresponding triiodide-based perovskites. Our results show that the inclusion of bromide introduced a halide homogenization process that occurs during the perovskite growth stage from an initial bromide-rich phase toward the final target stoichiometry. We further elucidated a physical model that correlates the role of bromide with the formation dynamics, defect physics, and eventual optoelectronic properties of the film. This work provides a fundamental and unique perspective toward understanding the performance-limiting factors affecting WBG mixed-halide perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First demonstration of tuning between the Kitaev and Ising limits in a honeycomb lattice

Recent observations of novel spin-orbit coupled states have generated interest in 4d/5d transition metal systems. A prime example is the J eff = $\frac{1}{2}$ state in iridate materials and α-RuCl 3 that drives Kitaev interactions. Here, by tuning the competition between spin-orbit interaction (λ SOC ) and trigonal crystal field (Δ T ), we restructure the spin-orbital wave functions into a previously unobserved μ = $\frac{1}{2}$ state that drives Ising interactions. This is done via a topochemical reaction that converts Li 2 RhO 3 to Ag 3 LiRh 2 O 6 . Using perturbation theory, we present an explicit expression for the μ = $\frac{1}{2}$ state in the limit Δ T ≫ λ SOC realized in Ag 3 LiRh 2 O 6 , different from the conventional J eff = $\frac{1}{2}$ state in the limit λ SOC ≫ Δ T realized in Li 2 RhO 3 . The change of ground state is followed by a marked change of magnetism from a 6 K spin-glass in Li 2 RhO 3 to a 94 K antiferromagnet in Ag 3 LiRh 2 O 6 .

36 MATERIALS SCIENCE↗

Dissecting components of the Campylobacter jejuni fetMP-fetABCDEF gene cluster under iron limitation

Campylobacter jejuni is a leading cause of bacterial gastroenteritis worldwide. Acute infection can be an antecedent to highly debilitating long-term sequelae. The expression of iron acquisition systems is vital for C. jejuni to survive the low iron availability within the human gut. The C. jejuni fetMP-fetABCDEF gene cluster is known to be upregulated during human infection and under iron limitation. While FetM and FetP have been functionally linked to iron transport in prior work, here we assess the contribution of each of the downstream genes (fetABCDEF) to C. jejuni growth during both iron-depleted and iron-replete conditions. Significant growth impairment was observed upon disruption of fetA, fetB, fetC, and fetD, suggesting a role in FetMP-mediated iron acquisition for each encoded protein. FetA expression was not dependent on the presence of FetB, FetC, FetD, FetE, or FetF. The functions of the putative thioredoxins FetE and FetF were redundant under iron-limited growth, requiring a double deletion (ΔfetEF) to exhibit a growth defect. C. jejuni FetE was expressed, and the structure was solved to 1.50 Å, revealing structural similarity to thiol-disulfide oxidases. Functional characterization in biochemical assays showed that FetE reduced insulin at a slower rate than Escherichia coli Trx and that together, FetEF promoted substrate oxidation in cell extracts, suggesting that FetE (and presumably FetF) are oxidoreductases that can mediate oxidation in vivo. This study advances our understanding of the contributions of the fetMP-fetABCDEF gene cluster to virulence at a genetic and functional level, providing foundational knowledge toward mitigating C. jejuni-related morbidity and mortality.

59 BASIC BIOLOGICAL SCIENCES↗

Supersymmetric Wilson loops on the lattice in the large N limit

We propose additional tests of holography by studying supersymmetric Wilson loops in p+1-dimensional maximally supersymmetric Yang?Mills (SYM) theories on the lattice in the large N limit. In the dual gravity description, this computation involves calculating the area of a fundamental string worldsheet in certain Type II supergravity backgrounds. Though thermodynamic observables have been computed on the lattice using Monte Carlo methods and agree with the supergravity results in various dimensions, not much has been done for the gauge-invariant operators such as the Wilson loop. We provide analytical predictions for these loops for various non-conformal Dp-brane background cases with ? ? 2 p?2 in the large N limit and comment on how these can be computed on non-orthogonal lattices in various models.

Jha, Raghav G. (ORCID:0000000329330102)↗

SD-pair shell model: Vibrational and rotational limits in the interacting boson–fermion model for like-nucleon system

Typical features of the Bose–Fermi symmetries associated with [Formula: see text] and [Formula: see text] limits in the interacting boson model are described in the SD-pair shell model (SDPSM) framework for like-nucleon system. It is found that the limiting spectra associated with [Formula: see text] (vibrational) and [Formula: see text] (rotational) in the interacting boson–fermion model can be well reproduced in the SDPSM framework. It is shown that coupling of collective degree of freedom with the single-particle degree of freedom in the pairing interaction almost has no effect on the spectrum of odd-A system comparing to the adjacent even–even system, while the coupling of the collective degree of freedom with the single-particle degree of freedom in the quadrupole–quadrupole interaction results in the level splitting of several excited levels.

Physics↗

Vanishing adsorption limit of Riemann problem solutions for the polymer model

Here we examine the vanishing adsorption limit of solutions of Riemann problems for the Glimm–Isaacson model of chemical flooding of a petroleum reservoir. A contact discontinuity is deemed admissible if it is the limit of traveling waves or rarefaction waves for an augmented system that accounts for weak chemical adsorption onto the rock. We prove that this criterion justifies the admissibility criteria adopted previously by Keyfitz–Kranzer, Isaacson–Temple and de Souza–Marchesin, provided that the fractional flow function depends monotonically on chemical concentration. We also demonstrate that the adsorption criterion selects the undercompressive contact discontinuities required to solve the general Riemann problem in an example model with non-monotone dependence.

97 MATHEMATICS AND COMPUTING↗

FASDA: An FPGA-Aided, Scalable and Distributed Accelerator for Range-Limited Molecular Dynamics

Conducting long-term simulations of small molecules using Molecular Dynamics (MD) is crucial in drug design. However, traditional methods to accelerate the process including ASICs or GPUs, have limitations. ASICs are difficult to access, while publicly accessible GPU packages for MD have issues with more GPUs when processing small molecules, causing decreased performance. Conversely, FPGAs are renowned for their scalability and have been commonly used as accelerators for various applications, making them suitable for the task. Moreover, with the availability of FPGAs in the cloud, pharmaceutical developers can now access FPGA devices. The only missing piece is a design deployed for MD acceleration. Therefore, we present FASDA, the first FPGA-based MD accelerator available for community development. FASDA is designed to evaluate range-limited MD, which is the most resource-intensive and computationally demanding component in MD. It outperforms the state of-the-art GPU solution by 4.67x, significantly reducing the time for MD in drug design.

Wu, Chunshu↗

A spatial evaluation of Arctic sea ice and regional limitations in CMIP6 historical simulations

The Arctic sea ice response to a warming climate is assessed in a subset of models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6), using several metrics in comparison with satellite observations and results from the Pan-Arctic Ice Ocean Modeling and Assimilation System and the Regional Arctic System Model. Our study examines the historical representation of sea ice extent, volume, and thickness using spatial analysis metrics, such as the integrated ice-edge error, Brier score, and Spatial Probability Score. We find that the CMIP6 multi-model mean captures the mean annual cycle and 1979-2014 sea ice trends remarkably well. However, individual models experience a wide range of uncertainty in the spatial distribution of sea ice when compared against satellite measurements and reanalysis data. Our metrics expose common and individual regional model biases, which sea ice temporal analyses alone do not capture. We identify large ice edge and ice thickness errors in Arctic sub-regions, implying possible model specific limitations in or lack of representation of some key physical processes. We postulate that many of them could be related to the oceanic forcing, especially in the marginal and shelf seas, where seasonal sea ice changes are not adequately simulated. We therefore conclude that an individual model’s ability to represent the observed/reanalysis spatial distribution still remains a challenge. We propose the spatial analysis metrics as useful tools to diagnose model limitations, narrow down possible processes affecting them, and guide future model improvements critical to the representation and projections of Arctic climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Knock-limited combustion of ethanol-, isobutanol-, and 2-methyl-3-buten-2-ol-gasoline blends in a direct-injected spark-ignition engine

Knock-limited combustion of alcohol-gasoline fuel blends was studied in a direct-injection spark-ignition engine. Ethanol, isobutanol (2-methyl-1-propanol), and methylbutenol (2-methyl-3-buten-2-ol) were splash-blended with a blendstock for oxygenate blending (BOB) gasoline. Ethanol was blended in fractions of 10%, 20%, and 30% by volume (E10, E20, and E30). Isobutanol and methylbutenol were blended to match the oxygen weight percentage of the ethanol blends, resulting in blends of 16%, 32%, and 49% (I16, I32, and I49) isobutanol by volume and 18%, 37%, and 56% (M18, M37, and M56) methylbutenol by volume. Neat BOB and gasoline primary reference fuels (PRF) with octane numbers (ON) of 87 (PRF87) and 100 (PRF100) were included for reference. The engine was operated at fixed speed, equivalence ratio, and injection timing while knock-limited spark advance was located across a range of intake pressures. Low-level alcohol blends E10 and M18 had similar knocking behavior and appeared to be slightly more knock-resistant than I16. For mid-level blends, E20 showed further improvement over I32 while M37 showed noticeably better knock resistance, able to match the knock-resistance of PRF100 for loads above 1000 kPa gross indicated mean effective pressure (GIMEP). For high-level blends, the difference between E30 and I49 was similar to their mid-level counterparts. However, M56 showed significant improvement over E30 and I49 throughout the entire range of loads tested. M56 exceeded the knock-resistance of PRF100 for loads above 700 kPa GIMEP. The improved knock-resistance combined with the increased volumetric energy density of methylbutenol resulted in improved fuel consumption and indicated efficiency. The overall results of this study indicate that the order of knock-resistance of these three alcohols, for direct-injection operation with injection during the intake stroke, is isobutanol < ethanol < methylbutenol when compared on an equal oxygen weight basis.

33 ADVANCED PROPULSION SYSTEMS↗

Adapting Reinforcement Learning Treatment Policies Using Limited Data to Personalize Critical Care

We report reinforcement learning (RL) demonstrates promise for developing effective treatment policies in critical care settings. However, existing RL methods often require large and comprehensive patient data sets and do not readily lend themselves to settings in which certain patient subpopulations are severely underrepresented. In this study, we develop a new method, noisy Bayesian policy updates (NBPU), for selecting high-performing reinforcement learning–based treatment policies for underrepresented patient subpopulations using limited observations. Our method uses variational inference to learn a probability distribution over treatment policies based on a reference patient subpopulation for which sufficient data are available. It then exploits limited data from an underrepresented patient subpopulation to update this probability distribution and adapts its recommendations to this subpopulation. We demonstrate our method’s utility on a data set of ICU patients receiving intravenous blood anticoagulant medication. Our results show that NBPU outperforms state-of-the-art methods in terms of both selecting effective treatment policies for patients with nontypical clinical characteristics and predicting the corresponding policies’ performance for these patients.

60 APPLIED LIFE SCIENCES↗

Far-field thermal imaging below diffraction limit

Non-uniform self-heating and temperature hotspots are major concerns compromising the performance and reliability of submicron electronic and optoelectronic devices. At deep submicron scales where effects such as contact-related artifacts and diffraction limits accurate measurements of temperature hotspots, non-contact thermal characterization can be extremely valuable. In this work, we use a Bayesian optimization framework with generalized Gaussian Markov random field (GGMRF) prior model to obtain accurate full-field temperature distribution of self-heated metal interconnects from their thermoreflectance thermal images (TRI) with spatial resolution 2.5 times below Rayleigh limit for 530nm illumination. Finite element simulations along with TRI experimental data were used to characterize the point spread function of the optical imaging system. In addition, unlike iterative reconstruction algorithms that use ad hoc regularization parameters in their prior models to obtain the best quality image, we used numerical experiments and finite element modeling to estimate the regularization parameter for solving a real experimental inverse problem.

42 ENGINEERING↗

Ultrafast optical switching and power limiting in intersubband polaritonic metasurfaces

Highly nonlinear optical materials with fast third-order nonlinear optical response are crucial for the operation of all-optical photonic devices, such as switches for signal processing and computation, power limiters, and saturable absorbers. The nonlinear response of traditional optical materials is weak, thus requiring large light intensities to induce significant changes in their properties. Here we show that optical control of the coupling rate in subwavelength patch antennas coupled to intersubband transitions in multi-quantum-well semiconductor heterostructures can provide a giant third-order nonlinear response, on the order of 3.4 × <#comment/> 10 − <#comment/> 13 m 2 / V 2 , with a response time < <#comment/> 2 p s . We utilize this effect to realize intersubband polaritonic metasurfaces and demonstrate their operation as highly nonlinear saturable and reverse saturable absorbers, enabling optical power limiters and other elements for all-optical modulation and control. Our approach enables a plethora of compact, low-power, highly nonlinear devices with spectral, temporal, and structured wavefront responses tailored by design.

Mann, Sander A. (ORCID:0000000277420615)↗

Global gross primary production simulated by three terrestrial biosphere models to analyse smoothing of limiting rates

Processed global terrestrial gross primary production (GPP) from three terrestrial biosphere models (TBMs). Two simulations were run with each model, one that selects the rate limiting process of photosynthesis based on the minimum of the potential rates (following Farquhar et al. 1980) and the other that uses quadratic smoothing between the potential rates (following Collatz et al. 1991). The three TBMs are: 1) the Energy Exascale Earth System Model (E3SM) land model (ELM) (release: v1.1.0) (Burrows et al., 2020), a coupled carbon, nitrogen, and phosphorus model with sun/shade big-leaf canopy photosynthesis scaling. 2) The Functionally Assembled Terrestrial Ecosystem Simulator (FATES, tag: sci.1.30.0_api.8.0.0) (Koven et al., 2019), coupled with the Community Land Model (CLM, version 5; Lawrence et al., 2019), a carbon-only vegetation demography model with multi-leaf and multi-canopy layers for scaling photosynthesis, and with a leaf area index (LAI) optimisation scheme. 3) The Sheffield Dynamic Global Vegetation Model (SDGVM, tag: Walkeretal2020_GCB), a carbon-only model with multi-leaf-layer canopy photosynthesis scaling and also with an LAI optimisation scheme (Walker et al., 2017; Woodward & Lomas, 2004). These data were generated to evaluate the effect of Collatz smoothing of limiting rates on simulated GPP across a range of terrestrial biosphere models. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures and .RDS files, a binary format specific to R and read with the 'readRDS' function.

54 ENVIRONMENTAL SCIENCES↗

When not to use machine learning: A perspective on potential and limitations

Abstract The unparalleled success of artificial intelligence (AI) in the technology sector has catalyzed an enormous amount of research in the scientific community. It has proven to be a powerful tool, but as with any rapidly developing field, the deluge of information can be overwhelming, confusing, and sometimes misleading. This can make it easy to become lost in the same hype cycles that have historically ended in the periods of scarce funding and depleted expectations known as AI winters. Furthermore, although the importance of innovative, high-risk research cannot be overstated, it is also imperative to understand the fundamental limits of available techniques, especially in young fields where the rules appear to be constantly rewritten and as the likelihood of application to high-stakes scenarios increases. In this article, we highlight the guiding principles of data-driven modeling, how these principles imbue models with almost magical predictive power, and how they also impose limitations on the scope of problems they can address. Particularly, understanding when not to use data-driven techniques, such as machine learning, is not something commonly explored, but is just as important as knowing how to apply the techniques properly. We hope that the discussion to follow provides researchers throughout the sciences with a better understanding of when said techniques are appropriate, the pitfalls to watch for, and most importantly, the confidence to leverage the power they can provide. Graphical abstract

36 MATERIALS SCIENCE↗

Pushing the limits of NAND technology scaling with ferroelectrics

Artificial intelligence (AI) continues to drive transformative advancements across various industries. The data-intensive nature of AI training (and inferencing) has resulted in the generation of unprecedented volumes of data with machine-generated content surpassing human-generated data by more than 100-fold in 2025. Efficiently managing this data influx necessitates advanced digital storage technologies. However, traditional NAND flash memory, which is critical for supporting data flows in AI systems—alongside high-bandwidth memory, for AI training—faces fundamental scaling limitations as it approaches the 1000-layer milestone, encompassing more than 40 trillion transistors. This article delves into the potential of hafnia-based ferroelectric materials as a breakthrough solution to these challenges. Recent advancements indicate that the intrinsic limitations of ferroelectric field-effect transistors (FEFETs) can be mitigated through material and device-level engineering. These advancements enable FEFETs to meet the stringent density, reliability, and scalability requirements of future three-dimensional NAND technology. The role of ferroelectrics in addressing NAND scaling challenges and expanding storage capabilities presents a promising avenue for meeting the storage demands of the AI-driven era.

3D NAND↗

Proton pulse charge calculation algorithm in Beam Power Limiting System at Spallation Neutron Source

A proton pulse charge calculation algorithm in the Beam Power Limiting System (BPLS) at the Spallation Neutron Source (SNS) was developed and implemented in an FPGA. The algorithm calculates one-minute running average of the pulse charges and issues a fault to the Personal Protection System (PPS) and the Machine Protection System (MPS) when a limit is reached. A bit-accurate model of the algorithm was first developed and tested in Matlab® and then implemented and simulated in VHDL using Vivado® design environment. Finally, the algorithm was verified on a µTCA-based hardware platform.

Bobrek, Miljko [ORNL] (ORCID:0000000332763451)↗

Performance Limits for Maritime Wide-Area Search (MWAS) Radar

One of the earliest applications for radar was to search for and find maritime vessels on the open sea. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. -

42 ENGINEERING↗

Independent Review of Paducah Gaseous Diffusion Plant Freon Release Authorized Limits and Evaluation of Corresponding Radiological Doses

The Portsmouth/Paducah Project Office (PPPO) proposes to use the American National Standard Institute (ANSI)/Health Physics Society (HPS) N13.12 (ANSI 2013) volumetric screening levels as Authorized Limits (ALs) for the release of cryofluorane R-114 (Freon) at the Paducah Gaseous Diffusion Plant (PGDP) in Paducah, Kentucky. A review of the proposed ALs document indicated that potential exposure scenarios from the release of Freon are adequately discussed therein. However, questions arose regarding the assumptions made for the ANSI N13.12 clearance values, and whether or not all pathway doses were adequately considered in the Authorized Limits Request. For example, PPPO used the inverse square rule to estimate dose to the truck driver. A more appropriate evaluation would have considered the material as a cylindrical source for this pathway. In addition, the inverse square rule was inadequately applied to the inhalation and ingestion pathways. Furthermore, while the ANSI N13.12 volumetric clearance values are used in the ALs, questions arose concerning whether the values are appropriate for materials of greater than 1 metric ton, and whether or not the ANSI N13.12 standard could be used for liquids that are sent to an incinerator. For these reasons, dose modeling was conducted to demonstrate that using ANSI/HPS N13.12 screening levels as ALs for release of PGDP Freon meets the dose criteria set in U.S. Department of Energy (DOE) Order 458.1. This report provides a bounding dose analysis using scenarios described in PPPO document. Realistic parameters, such as the incinerator characteristics data, are used when available.

61 RADIATION PROTECTION AND DOSIMETRY↗