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At least 73 records · Page 4

Electronic coupling through natural amino acids

Myriad scientific domains concern themselves with biological electron transfer (ET) events that span across vast scales of rate and efficiency through a remarkably fine-tuned integration of amino acid (AA) sequences, electronic structure, dynamics, and environment interactions. Within this intricate scheme, many questions persist as to how proteins modulate electron-tunneling properties. To help elucidate these principles, we develop a model set of peptides representing the common α-helix and β-strand motifs including all natural AAs within implicit protein-environment solvation. Using an effective Hamiltonian strategy with density functional theory, we characterize the electronic coupling through these peptides, furthermore considering side-chain dynamics. For both motifs, predictions consistently show that backbone-mediated electronic coupling is distinctly sensitive to AA type (aliphatic, polar, aromatic, negatively charged and positively charged), and to side-chain orientation. The unique properties of these residues may be employed to design activated, deactivated, or switch-like superexchange pathways. Electronic structure calculations and Green’s function analyses indicate that localized shifts in the electron density along the peptide play a role in modulating these pathways, and further substantiate the experimentally observed behavior of proline residues as superbridges. The distinct sensitivities of tunneling pathways to sequence and conformation revealed in this electronic coupling database help improve our fundamental understanding of the broad diversity of ET reactivity and provide guiding principles for peptide design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dependability Assessment of Software for Safety Instrumentation and Control Systems

In its 2013 recommendations to the International Atomic Energy Agency (IAEA), the Technical Working Group on Nuclear Power Plant Instrumentation and Control (TWG-NPPIC) identified assessment and evaluation of software dependability as a topic of interest for IAEA Member States. To implement the recommendation of the TWG-NPPIC, the IAEA Scientific Secretary for the TWG initiated a consultancy activity in 2014 to develop a technical report describing a dependability assessment framework suitable for safety instrumentation and control (I and C) systems in nuclear power plants (NPPs). The development of the software dependability assessment report has involved three consultancy meetings at IAEA headquarters in Vienna, Austria. The conduct of these meetings allowed consultation among subject matter experts to generate consensus technical information that serves as the content of the report. The technical contributors consist of international experts from academia, industry, regulatory bodies and research organizations. In September 2014, a technical meeting was held in Daejeon, Republic of Korea, to present interim findings of the consultancy effort and to solicit input from representatives of IAEA Member States. The information and technical comments contributed during the technical meeting were addressed in subsequent development of the report. This paper gives an overview of key technical elements of the IAEA report. The IAEA report presents a framework by which a dependability assessment of safety software can be performed. The specified guiding principles provide the basis for establishing an assessment strategy and implementing the assessment process. The assessment framework provides a systematic, coherent structure within which to organize technical and process evidence to satisfy arguments in support of claims about software dependability properties. During the consultancy activity, the participating subject matter experts focused on high level principles, a structured approach, and identification of suitable methods and techniques. However, it was recognized that what remains is to concretize the framework through specific examples and usage experience. Thus, following publication of the report, it is recommended that case studies be performed to illustrate and more precisely define specific phases and elements of the assessment framework. For example, current national assessment approaches could be mapped into the assessment framework to serve as case studies and help to identify any aspects of the assessment framework that needs further definition or adjustment. Additionally, a challenge problem could be defined to engage stakeholders to apply the assessment framework with a common focus. This could help to better illustrate strategic options and approaches to the assessment phases. It also could serve to suggest other considerations and potential sources of evidence not fully covered in the report. Based on findings from case studies, challenge problems and country experience, it should be possible to develop generalized templates to support application of the assessment framework. These findings can be collected to serve as the basis for a User's Guide on dependability assessment of safety software. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Roadmap on transformation optics

Transformation optics asks, using Maxwell's equations, what kind of electromagnetic medium recreates some smooth deformation of space? The guiding principle is Einstein's principle of covariance: that any physical theory must take the same form in any coordinate system. This requirement fixes very precisely the required electromagnetic medium. The impact of this insight cannot be overestimated. Many practitioners were used to thinking that only a few analytic solutions to Maxwell's equations existed, such as the monochromatic plane wave in a homogeneous, isotropic medium. At a stroke, transformation optics increases that landscape from 'few' to 'infinity', and to each of the infinitude of analytic solutions dreamt up by the researcher, there corresponds an electromagnetic medium capable of reproducing that solution precisely. The most striking example is the electromagnetic cloak, thought to be an unreachable dream of science fiction writers, but realised in the laboratory a few months after the papers proposing the possibility were published. But the practical challenges are considerable, requiring meta-media that are at once electrically and magnetically inhomogeneous and anisotropic. How far have we come since the first demonstrations over a decade ago? And what does the future hold? If the wizardry of perfect macroscopic optical invisibility still eludes us in practice, then what compromises still enable us to create interesting, useful, devices? While three-dimensional (3D) cloaking remains a significant technical challenge, much progress has been made in two dimensions. Carpet cloaking, wherein an object is hidden under a surface that appears optically flat, relaxes the constraints of extreme electromagnetic parameters. Surface wave cloaking guides sub-wavelength surface waves, making uneven surfaces appear flat. Two dimensions is also the setting in which conformal and complex coordinate transformations are realisable, and the possibilities in this restricted domain do not appear to have been exhausted yet. Beyond cloaking, the enhanced electromagnetic landscape provided by transformation optics has shown how fully analytic solutions can be found to a number of physical scenarios such as plasmonic systems used in electron energy loss spectroscopy and cathodoluminescence. Are there further fields to be enriched? A new twist to transformation optics was the extension to the spacetime domain. By applying transformations to spacetime, rather than just space, it was shown that events rather than objects could be hidden from view; transformation optics had provided a means of effectively redacting events from history. The hype quickly settled into serious nonlinear optical experiments that demonstrated the soundness of the idea, and it is now possible to consider the practical implications, particularly in optical signal processing, of having an 'interrupt-without-interrupt' facility that the so-called temporal cloak provides. Inevitable issues of dispersion in actual systems have only begun to be addressed. Now that time is included in the programme of transformation optics, it is natural to ask what role ideas from general relativity can play in shaping the future of transformation optics. Indeed, one of the earliest papers on transformation optics was provocatively titled 'General Relativity in Electrical Engineering'. The answer that curvature does not enter directly into transformation optics merely encourages us to speculate on the role of transformation optics in defining laboratory analogues. Quite why Maxwell's theory defines a 'perfect' transformation theory, while other areas of physics such as acoustics are not apparently quite so amenable, is a deep question whose precise, mathematical answer will help inform us of the extent to which similar ideas can be extended to other fields. Here, the contributors to this Roadmap, who are all renowned practitioners or inventors of transformation optics, will give their perspectives into the field's status and future development.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized Sn clusters and their host pores in carbon nanofiber) during sodiation and desodiation is revealed using a state-of-the-art 3D electron microscopic reconstruction technique. For the first time, the anomalous expansion of Sn clusters after desodiation is observed owing to the aggregation of clusters/single atoms. Pore connectivity is retained despite the anomalous expansion, suggesting inhibition of solid electrolyte interface formation in the sub-2-nm pores. Taking advantage of the built-in nanoconfinement feature, the CNF film with nanometer-sized interconnected pores hosting Sn clusters (≈2 nm) enables high utilization (95% at a high rate of 1 A g –1 ) of Sn active sites while maintaining an improved initial Coulombic efficiency of 87%. Finally, the findings provide insights into electrochemical reactions in a confined space and a guiding principle in electrode design for battery applications.

36 MATERIALS SCIENCE↗

Accelerated Search for BaTiO 3 -Based Ceramics with Large Energy Storage at Low Fields Using Machine Learning and Experimental Design

The problem that is considered is that of maximizing the energy storage density of Pb-free BaTiO3-based dielectrics at low electric fields. It is demonstrated that how varying the size of the combinatorial search space influences the efficiency of material discovery by comparing the performance of two machine learning based approaches where different levels of physical insights are involved. It is started with physics intuition to provide guiding principles to find better performers lying in the crossover region in the composition–temperature phase diagram between the ferroelectric phase and relaxor ferroelectric phase. Such an approach is limiting for multidopant solid solutions and motivates the use of two data-driven machine learning and design strategies with a feedback loop to experiments. Strategy I considers learning and property prediction on all the compounds, and strategy II learns to preselect compounds in the crossover region on which prediction is carried out. By performing only two active learning loops via strategy II, the compound (Ba0.86Ca0.14)(Ti0.79Zr0.11Hf0.10)O3 is synthesized with the largest energy storage density ≈73 mJ cm-3 at a field of 20 kV cm-1 , and an insight into the relative performance of the strategies using varying levels of knowledge is provided.

36 MATERIALS SCIENCE↗

Probing the Impact of Vacancy Diffusion on Void Dynamics at the Lithium Metal–Solid Electrolyte Interface

Lithium (Li) metal-based solid-state batteries (SSBs) are considered promising candidates for next-generation energy storage due to their superior energy density and enhanced safety compared to conventional Li-ion systems. However, their practical application is limited by challenges such as void formation at the Li-solid electrolyte (SE) interface, which disrupts ion transport and accelerates interfacial degradation. This work investigates how the coupled effects of electro-dissolution kinetics and surface diffusion at the Li metal surface govern the evolution of interfacial morphology during stripping. This work examines the influence of three distinct surface diffusion modes, which are terrace diffusion, step diffusion, and interlayer diffusion, on maintaining interfacial stability. In addition, how the dominant surface diffusion mechanism can overcome the contact loss due to high reaction kinetics is explored. Furthermore, the roughness of the Li metal anode surface is quantified, and the influence of different diffusion mechanisms on the evolution of the dynamic solid–solid interface is examined. The critical role of temperature in enhancing Li surface diffusivity and expanding the regime of stable contact is highlighted. By identifying distinct regimes of interface stability, this study analyzes how non-uniform electrochemical dynamics dictate void morphology evolution and interfacial contact. These insights offer guiding principles for engineering robust Li–SE interfaces in SSBs.

lithium metal anode↗

Effects of Molecular Structure and Packing Order on the Stretchability of Semicrystalline Conjugated Poly(Tetrathienoacene-diketopyrrolopyrrole) Polymers

The design of polymer semiconductors possessing high charge transport performance, coupled with good ductility, remains a challenge. Understanding the distribution and behavior of both crystalline domains and amorphous regions in conjugated polymer films, upon an applied stress, shall provide general guiding principles to design stretchable organic semiconductors. Structure–property relationships (especially in both side chain and backbone engineering) are investigated for a series of poly(tetrathienoacene-diketopyrrolopyrrole) polymers. It is observed that the fused thiophene diketopyrrolopyrrole-based polymer, when incorporated with branched side chains and an additional thiophene spacer in the backbone, exhibits improved mechanical endurance and, in addition, does not show crack propagation until 40% strain. Furthermore, this polymer exhibits a hole mobility of 0.1 cm2 V -1 s -1 even at 100% strain or after recovered from strain, which reveals prominent continuity and viscoelasticity of the polymer thin film. In conclusion, it is also observed that the molecular packing orientations (either edge-on or face-on) significantly affect the mechanical compliance of the polymer films. The improved stretchability of the polymers is attributed to both the presence of soft amorphous regions and the intrinsic packing arrangement of its crystalline domains.

36 MATERIALS SCIENCE↗

Biomaterial–Based Solid–Electrolyte Organic Electrochemical Transistors for Electronic and Neuromorphic Applications

In this work a systematic study of biomaterial–based solid–state organic electrochemical transistors (OECTs) is presented in which biogels consisting of gelatin and glycerol, two food–grade materials, are chosen as the model solid electrolyte. Such gels are fundamentally attractive for bioelectronics and wearable applications due to their superior and tunable electrical and mechanical properties, which allow one to fabricate solid–state organic transistors with high ON/OFF ratio and transconductance, possible millisecond–switching speed, and 6–month stability in ambient air. Next, the authors show a good control of the state–retention property of biogel OECTs, demonstrated herein by employing them as artificial synapses with various synaptic functions, such as frequency–based short–term plasticity. This study herein paves the way for the development of biomaterial–based electronics by providing guiding principles for future works that employ biomaterials in OECTs.

36 MATERIALS SCIENCE↗

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗

Non-Proliferation Regime and Export Control

The barriers required to counter the threat of proliferation of nuclear weapons are examined. The most important barriers are the nuclear weapons non-proliferation treaty, the IAEA safeguard system, and the guiding principles of the Zangger committee and the nuclear suppliers groups. The principles of monitoring for the switching of nuclear materials from peaceful to military uses are fundamental and are applicable for nuclear power based on thermal as well as fast reactors.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Quantitative Study of Plasmonic Gold Nanostar Geometry Toward Optimal SERS Detection

Abstract Complex shapes of gold nanostars (GNS) have been the major obstacle to the comprehensive understanding of the rich plasmonic phenomena of GNS. We conducted extensive, systematic numerical study of far-field and near-field spectral responses of GNS for varying geometrical parameters (e.g., number of spikes, spike tip angle, and spike-to-core ratio) to elucidate the relationship between the optical property and the geometry of GNS. We found that symmetric configurations of GNS spikes generated both dipole and quadrupole localized surface plasmon (LSP) modes, their hybridization resulted in the final near-field intensity at the spike tips, and there existed a specific GNS geometry that optimized the hybridization and thus the E-field intensity for any given wavelength. From these results, we further identified the shapes of GNS that generated the strongest Surface Enhanced Raman Scattering (SERS) enhancement factors in the visible and NIR spectral range. Hence, our results provide guiding principles in determining the optimal geometry of GNS for SERS applications with any choice of excitation wavelength.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A level-of-details framework for representing occupant behavior in agent-based models

We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.

42 ENGINEERING↗

Discovery and engineering of enzymes for new-to-nature photobiocatalysis

Photobiocatalysis integrates enzymatic catalysis with photochemistry, enabling challenging radical transformations with high selectivity under mild conditions. Early developments in this field were largely driven by the discovery that enzyme-bound cofactors can form photoactive charge–transfer complexes with substrates, thereby initiating radical chemistry upon light irradiation. Recent advances, however, have substantially expanded the mechanistic landscape of photobiocatalysis through diverse mechanisms. This review summarizes major developments in photobiocatalysis reported since 2024. Rather than cataloging individual reactions, we focus on the fundamental mechanisms of radical generation and interception within enzyme active sites, and discuss how these mechanistic principles guide the discovery, engineering, and design of enzymes for new-to-nature photobiocatalysis.

Bai, Zibo [University of Illinois Urbana-Champaign↗

Rate Limiting Regimes in Photochemical H2 Generation by Complexes of Colloidal CdS Nanorods and Hydrogenase

Driving redox enzyme catalysis with photoexcited semiconductor nanocrystals is a compelling approach for chemical conversion. We examined how the interplay of the many chemical steps involved determines the rates of photochemical H2 production with complexes of colloidal CdS nanorods and an [FeFe]-hydrogenase. We elucidated the roles of three critical and previously elusive processes-scavenging of photoexcited holes from nanorods, back-electron transfer, and H2 oxidation. Kinetic Monte Carlo simulations and fitting to experimental data revealed that hole transfer becomes the rate-limiting step at high illumination intensities. Comparisons of simulations to experimental H2 production showed that both back-electron transfer and H2 oxidation play an efficiency-limiting role at high catalyst loadings. This work provides guiding principles for tuning experimental parameters to minimize energy-wasting pathways and optimize photochemical product formation. More broadly, we demonstrate how critical but elusive chemical steps in photochemical reactions can be probed with a combination of experiments and simulations.

08 HYDROGEN↗

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗

Toward sustainable, cell-free biomanufacturing

Industrial biotechnology is an attractive approach to address the need for low-cost fuels and products from sustainable resources. Unfortunately, cells impose inherent limitations on the effective synthesis and release of target products. One key constraint is that cellular survival objectives often work against the production objectives of biochemical engineers. Additionally, industrial strains release CO2 and struggle to utilize sustainable, potentially profitable feedstocks. Cell-free biotechnology, which uses biological machinery harvested from cells, can address these challenges with advantages including: (i) shorter development times, (ii) higher volumetric production rates, and (iii) tolerance to otherwise toxic molecules. In this review, we highlight recent advances in cell-free technologies toward the production of non-protein products beyond lab-scale demonstrations and describe guiding principles for designing cell-free systems. Specifically, we discuss carbon and energy sources, reaction homeostasis, and scale-up. Expanding the scope of cell-free biomanufacturing practice could enable innovative approaches for the industrial production of green chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Simplified models for dark matter searches at the LHC

This document a outlines a set of simplified models for dark matter and its interactions with Standard Model particles. It is intended to summarize the main characteristics that these simplified models have when applied to dark matter searches at the LHC, and to provide a number of useful expressions for reference. The list of models includes both s-channel and t-channel scenarios. For s-channel, spin-0 and spin-1 mediations are discussed, and also realizations where the Higgs particle provides a portal between the dark and visible sectors. The guiding principles underpinning the proposed simplified models are spelled out, and some suggestions for implementation are presented.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimal design of microseismic monitoring network: Synthetic study for the Kimberlina CO2 storage demonstration site

Microseismic monitoring can play a crucial role to ensure safe long-term geological carbon storage. For reliable long-term monitoring for CO2-injection-induced microseismic events, a surface seismic array is desirable in addition to borehole geophone sensors. Optimal design of surface seismic network is of great interest to achieve cost-effective monitoring. We develop a methodology to determine the optimal number of surface seismic stations with a geometrically satisfactory distribution for given monitoring regions. We design an optimal microseismic monitoring network based on widely-accepted guiding principles, and the relationship between the location accuracy of microseismic events and the total number of seismic stations. We determine the optimal number of seismic stations based on the trade-off curve of the event location accuracy vs. the total number of seismic stations. We apply our optimal design method to the Kimberlina carbon storage site in California. We use a synthetic Kimberlina model to show that approximately 20 surface seismic stations with a geometrically satisfactory distribution are preferred for the best trade-off between the cost and the event location accuracy.

58 GEOSCIENCES↗