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At least 253 records · Page 14

A meta-analysis of semantic classification of citations

The aim of this literature review is to examine the current state of the art in the area of citation classification. In particular, we investigate the approaches for characterizing citations based on their semantic type. We conduct this literature review as a meta-analysis covering 60 scholarly articles in this domain. Although we included some of the manual pioneering works in this review, more emphasis is placed on the later automated methods, which use Machine Learning and Natural Language Processing (NLP) for analyzing the fine-grained linguistic features in the surrounding text of citations. The sections are organized based on the steps involved in the pipeline for citation classification. Specifically, we explore the existing classification schemes, data sets, pre-processing methods, extraction of contextual and non-contextual features, and the different types of classifiers and evaluation approaches. The review highlights the importance of identifying the citation types for research evaluation, the challenges faced by the researchers in the process, and the existing research gaps in this field.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Ultrafast Bragg coherent diffraction imaging of epitaxial thin films using deep complex-valued neural networks

Abstract Domain wall structures form spontaneously due to epitaxial misfit during thin film growth. Imaging the dynamics of domains and domain walls at ultrafast timescales can provide fundamental clues to features that impact electrical transport in electronic devices. Recently, deep learning based methods showed promising phase retrieval (PR) performance, allowing intensity-only measurements to be transformed into snapshot real space images. While the Fourier imaging model involves complex-valued quantities, most existing deep learning based methods solve the PR problem with real-valued based models, where the connection between amplitude and phase is ignored. To this end, we involve complex numbers operation in the neural network to preserve the amplitude and phase connection. Therefore, we employ the complex-valued neural network for solving the PR problem and evaluate it on Bragg coherent diffraction data streams collected from an epitaxial La 2-x Sr x CuO 4 (LSCO) thin film using an X-ray Free Electron Laser (XFEL). Our proposed complex-valued neural network based approach outperforms the traditional real-valued neural network methods in both supervised and unsupervised learning manner. Phase domains are also observed from the LSCO thin film at an ultrafast timescale using the complex-valued neural network.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Tokamak Energy’s pre-concept design for a fusion power plant: an overview of ST-E1

Climate change and rapidly rising energy demand, driven in part by artificial intelligence and data-centre growth, create an urgent need for stable, low-carbon, and abundant power. Fusion is a promising long-term solution, yet its commercialisation faces a fundamental paradox in today’s investment environment: pilot plants are essential to de-risk physics, engineering, and operations, but their limited lifetime energy output and high upfront costs make them difficult to finance. This paper presents Tokamak Energy’s response: ST-E1, a pre-concept design for a low-aspect-ratio tokamak power plant engineered specifically to overcome this challenge. ST-E1 is designed from the outset for phased operation—pilot and commercial phases, with an upgrade phase in between—with emphasis on commercial viability, maintainability, nuclear engineering, modularity, and upgradability. A key design principle is the deliberate separation of long-lived assets, such as the magnet cage and vacuum vessel, from replaceable in-vessel systems. This provides an attractive and credible investment approach to generate operational data and de-risk key technologies while preserving most capital-intensive assets for later commercial phases. The architecture supports continuous optimisation toward high net electric power (targeting 800–1000 MW net electric), a normalised capital expenditure of $\$$ 12–14k/kW of net electric power, and high availability (targeting > 80%). A tokamak core with a 5 m major radius, aspect ratio of 2.3, and on-plasma axis toroidal field of 5.25 T was selected to meet these objectives. This paper summarises the ST-E1 design philosophy, principal features, and development methodology. It introduces a Focus Collection of 11 papers detailing the pre-concept design of the entire tokamak and corresponding plant.

ST-E1↗

Engineering Self-Assembled Domain Asymmetry in Solvent Vapor Annealed Block Copolymer–Homopolymer Blend Films

Thin-film block copolymer (BCP) self-assembly is a powerful approach to generate highly uniform nanopatterns across large areas, yet the symmetries of these nanopatterns are constrained by the relative volume occupied by each polymer block. Here, we present a conceptually new approach to circumvent this limitation by combining homopolymer (HP) blending with solvent vapor annealing (SVA), demonstrated here for ternary blends of a near-symmetric BCP with athermal, low molar mass HPs. Screening of BCP–HP interactions by a weakly selective solvent promotes entropically driven delocalization of HP throughout both blocks and enables assembly of metastable lamellae for volume fractions as high as 0.78. Subsequent brief thermal annealing induces HPs to withdraw to their enthalpically favored domains, sharpening domain interfaces on a time scale much shorter than pattern coarsening. This renders lamellar nanopatterns with tunable widths that can be transferred to other materials with high fidelity. Furthermore, the persistence of the metastable asymmetric lamellae upon thermal annealing is sensitive to film confinement, as they are preserved in submonolayer films but transition to horizontal cylinders in films more than one monolayer thick. SVA using a strongly selective solvent results in assembled morphologies aligned closely with expectations based on the total polymer blend composition, underscoring the key role of BCP–HP interactions in dictating domain asymmetry. Overall, this work details important principles for using SVA to mediate BCP–HP interactions in thin films, thereby presenting opportunities to engineer pathways for the assembly of well-ordered nanopatterns with designer feature asymmetry for lithographic or nanotexturing applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Blockchain for Fault-Tolerant Grid Operations

Radial topology and vast geographic coverage make distribution systems prone to widespread power outages upon the failure of a single (or multiple) upstream component. Fault-handling algorithms depend heavily on correct estimations of the system’s state to effectively isolate the affected area and reduce the number of affected customers while maintaining operational safety. The work described here leverages the core features of distributed, consensus-based decision-making processes and the immutability of blockchain, and demonstrates their value in improving fault-tolerant grid operations. In this work, blockchain was used to create a trusted data-sharing platform that enables independent actors to reconstruct the system state; this enables distributed resources to make intelligent decisions with limited knowledge. Although the process requires data sharing, its algorithms have been designed to limit the amount of private information that is exchanged, which helps preserve business-sensitive data and maintain customer privacy. In addition, by reducing the information that must be shared, the communication requirements are also reduced; (however, an in-depth analysis of the communication requirements is beyond the scope of this project). The proposed use cases are intended to represent a foundational basis for third parties to develop functional solutions that can eventually be deployed in the field. To further provide guidance, the envisioned use cases have incorporated design requirements that consider the blockchain characteristics and a need to limit information from surrounding resources, which preserve the assumption and the possibility that such resources could belong to different entities. This report presents a detailed design of the three use cases with the tools needed to enable the analysis being tested. The implemented gross error detection method can detect mismatches when the error exceeds 3.8 times the sensor’s rated accuracy. Detection of the circuit breaker state successfully identified the correct states across all simulation tests. A distribution-system power-flow solution in the simulator OpenDSS generally possesses a convergency tolerance of 0.01% on the voltage magnitude. The evaluation of possible reconnection using voltage magnitude—preserving the data ownership—has a voltage magnitude difference smaller than 0.001% from the OpenDSS result. The results preserving data ownership have a difference within the expected power flow tolerance with full knowledge of the system, which surpasses expectations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Supersymmetry and superstrata in three dimensions

We analyze the supersymmetry transformations of gauged SO(4) supergravity coupled to extra hypermultiplets in three dimensions, and find large families of smooth BPS solutions that preserve four supersymmetries. These BPS solutions are part of the consistent truncation of some families of six-dimensional superstrata. From the three-dimensional perspective, these solutions give rise to “smoothly-capped BTZ” geometries. We show how the twisting of the spin connection, the holomorphy of the fields, and the Chern-Simons connections all play an essential role in the existence of these supersymmetric solutions. This paper also closes the circle on the consistent truncation of superstrata, showing precisely how every feature of the superstratum enters into the three-dimensional BPS structure.

79 ASTRONOMY AND ASTROPHYSICS↗

Utility Regulation Through Legislation: A Cautionary Tale for Legislators, Regulators, Stakeholders, and Utilities

State legislatures in the U.S. are becoming increasingly involved in utility regulation. While state utility legislation can expand regulator authority, for example in the case of renewable energy or energy efficiency standard administration, it can also reduce it. Given the challenging nature of for-profit monopoly regulation, state utility legislation often reduces regulator authority unintentionally. This editorial begins with an examination of the outcomes of state legislation related to baseload generation in the U.S. and the resulting impacts to customers, shareholders, and state economies. The record indicates that utility regulation through state legislation has caused significant economic harm, generally by encouraging for-profit utilities to make riskier investments. A description of more recent state legislation involving distribution grids is presented, along with evidence that increases in grid investment encouraged by state legislation has not improved the reliability of U.S. for-profit utilities. The authors claim that features common to state utility legislation, particularly the requirement that utilities provide investment plans to regulators in advance, practically eliminates cost disallowance risk. This, in turn, reduces regulator authority despite legislative provisions intended to protect consumers. The authors hypothesize that the practical elimination of cost disallowance risk, combined with information and expertise asymmetry among regulators and stakeholders, encourages for-profit monopoly utilities to make grid investments that are not cost effective. The editorial concludes that legislators should avoid utility regulation through legislation, thereby preserving regulator authority, whenever possible. The authors also present their fifth annual Customer Value Ranking of U.S. investor-owned electric utilities. The ranking represents a comparison of the benefits utilities deliver to customers (measured by reliability performance and customer satisfaction) to the costs customers pay (measured by O&M and capital spending per customer).

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

Accomplishments of Thermal Neutron Scattering Research at North Carolina State University [Slides]

Thermal neutron scattering law (TSL) data evaluations have been completed and contributed to ENDF. New evaluations are underway. FLASSH is developing as a modern platform for thermal neutron data analysis featuring an enhanced user experience and low learning overhead. Advanced TSL techniques in combination with Doppler analysis have been developed, which were incorporated into FLASSH. ML/DL NeTS method development has been initiated. Experimental capabilities for validation have been developed at the PULSTAR reactor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Library of Advanced Materials for Engineering (LAMÉ) 5.18

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗

Nodeless superconductivity in the noncentrosymmetric compound ThIrSi

The superconductor ThIrSi, with Tc=6.5K, is expected to show unusual features in view of its noncentrosymmetric structure and the presence of heavy elements featuring a sizable spin-orbit coupling. Here, we report a comprehensive study of its electronic properties by means of magnetization, muon-spin rotation and relaxation (μ⁢SR) and nuclear magnetic resonance (NMR) measurements. Both the superfluid density ρ sc ⁡(T) (determined via transverse-field μ⁢SR) and the spin-lattice relaxation rate T–1 1⁡(T) (determined via NMR) suggest a nodeless superconductivity. Furthermore, the absence of spontaneous magnetic fields below T c , as evinced from zero-field μ⁢SR measurements, indicates a preserved time-reversal symmetry in the superconducting state of ThIrSi. Finally, temperature-dependent upper critical fields as well as field-dependent superconducting muon-spin relaxations suggest the presence of multiple superconducting gaps in ThIrSi.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Library of Advanced Materials for Engineering (LAMÉ) 5.16

Accurate and efficient constitutive modeling remains a cornerstone issue for solid mechanics analysis. Over the years, the LAMÉ advanced material model library has grown to address this challenge by implementing models capable of describing material systems spanning soft polymers to stiff ceramics including both isotropic and anisotropic responses. Inelastic behaviors including (visco)plasticity, damage, and fracture have all incorporated for use in various analyses. This multitude of options and flexibility, however, comes at the cost of many capabilities, features, and responses and the ensuing complexity in the resulting implementation. Therefore, to enhance confidence and enable the utilization of the LAMÉ library in application, this effort seeks to document and verify the various models in the LAMÉ library. Specifically, the broader strategy, organization, and interface of the library itself is first presented. The physical theory, numerical implementation, and user guide for a large set of models is then discussed. Importantly, a number of verification tests are performed with each model to not only have confidence in the model itself but also highlight some important response characteristics and features that may be of interest to end-users. Finally, in looking ahead to the future, approaches to add material models to this library and further expand the capabilities are presented.

36 MATERIALS SCIENCE↗

Pushing the limits: Resolving paleoseawater signatures in nanoscale fluid inclusions by atom probe tomography

New insight into the geochemistry of ancient environments can be gained through structural and chemical analyses of nanometer-scale features within minerals. Here, we present recent developments using atom probe tomography (APT) enabling direct visualization of nanoscale fluid inclusions trapped within pyrite (FeS 2 ) and thereby chemical characterization of remnant seawater. Pyrite framboids (spherical clusters of nanocrystals) were sampled from the Middle Devonian Leicester Pyrite Member (New York). Scanning transmission electron microscopy shows low density regions distributed within the pyrite consistent with nanoscale pores (<4 nm in size). APT 3D visualization and compositional mapping reveals that the nanopores are filled with water. The inclusions appear to preserve the elemental signature of the water column in which the framboids formed, specifically seawater components including Na, K, Mg, and Ca. Mg/Ca ratios within the pyrite were generally measured to be within 0.6±0.2 – consistent with calcite-dominated seawater conditions existing in the Middle Devonian. Furthermore, this study demonstrates the potential for a novel approach to reconstruct paleoenvironmental conditions from coupled elemental and structural analyses of nanoscale fluid inclusions.

54 ENVIRONMENTAL SCIENCES↗

Dynamics of McMillan mappings III. Symmetric map with mixed nonlinearity

This article extends the study of the dynamical properties of the symmetric McMillan map, emphasizing its utility in understanding and modeling complex nonlinear systems. Although the map features six parameters, we demonstrate that only two are irreducible: the linearized rotation number at the fixed point and a nonlinear parameter representing the ratio of terms in the biquadratic invariant. Through a detailed analysis, we classify regimes of stable motion, provide exact solutions to the mapping equations, and derive a canonical set of action-angle variables, offering analytical expressions for the rotation number and nonlinear tune shift. We further establish connections between general standard-form mappings and the symmetric McMillan map, using the area-preserving Hénon map and accelerator lattices with thin sextupole magnet as representative case studies. Our results show that, despite being a second-order approximation, the symmetric McMillan map provides a highly accurate depiction of dynamics across a wide range of system parameters, demonstrating its practical relevance in both theoretical and applied contexts.

43 PARTICLE ACCELERATORS↗

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data

Abstract Background The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potential of machine learning models for understanding the connections between soil and biological phenotypes. We investigate an integrative framework performing accurate machine learning-based prediction of plant performance from biological, chemical, and physical properties of the soil via two models: random forest and Bayesian neural network. Results Prediction improves when we add environmental features, such as soil properties and microbial density, along with microbiome data. Different preprocessing strategies show that human decisions significantly impact predictive performance. We show that the naive total sum scaling normalization that is commonly used in microbiome research is one of the optimal strategies to maximize predictive power. Also, we find that accurately defined labels are more important than normalization, taxonomic level, or model characteristics. ML performance is limited when humans can’t classify samples accurately. Lastly, we provide domain scientists via a full model selection decision tree to identify the human choices that optimize model prediction power. Conclusions Our study highlights the importance of incorporating diverse environmental features and careful data preprocessing in enhancing the predictive power of machine learning models for soil and biological phenotype connections. This approach can significantly contribute to advancing agricultural practices and soil health management.

Aghdam, Rosa↗

Performance and Feature Improvements in Parareal-based Power System Dynamic Simulation

In recent years, a novel Parareal-based approach has been developed for fast transient simulations of large power system interconnections. Parareal belongs to the class of Parallel-in-time algorithms for solution of systems of differential-algebraic equations in parallel over an interval of time. The selection of a reasonably fast and accurate coarse solution is crucial to improve the performance of Parareal algorithm. Semi-analytical solution methods are one promising approach to achieve this goal. They have been investigated, and some preliminary results are presented here. In addition, Parareal-based simulator has been expanded to enable co-simulation with OpenDSS, a widely used open-source distribution system simulator. Preserving the parallel nature of the Parareal approach and taking advantage of the parallel capabilities of the latest versions of OpenDSS, each distribution system can be solved in their entirety on different processors in parallel within the main Parareal simulator. This paper also presents the structure of the transmission and distribution co-simulation and some results with different dynamic models of inverter-based resources in the distribution systems.

Park, Byungkwon↗

Mitigation for Removal of Building 01-103 in the Area 1 Subdock, Nevada National Security Site, Nye County, Nevada

Building 01-103, the Drill Bit Repair Building was originally recorded as SHPO Resource No. B18848 in 2020 during an architectural survey of the Area 1 Subdock (Collins et al. 2022). It was recommended individually eligible for listing in the NRHP under Criteria A and C and contributing to the significance of the Area 1 Subdock Historic District. The SHPO concurred with these determinations in a letter dated April 29, 2022 (Reed 2022). The Drill Bit Repair Building retains all seven aspects of integrity. The location, materials, workmanship, feeling, and association have not changed since its original construction. The design was modified slightly in 1996 with the addition of a removable and non-destructive chain-link fence. Nearby buildings 01-101 and 01-102 were removed (Collins and Menocal 2020) but the other buildings and storage yards remain. Therefore, the integrity of setting has been changed, but not to the degree that the building no longer conveys its significance (see Figures 4 and 5 for comparison). Building 01-103 was constructed in 1985 to coincide with the relocation of the Area 3 Subdock to Area 1. The design for the new Subdock provided a centralized cluster of buildings surrounded by two large storage yards. The buildings included administrative and engineering office space, warehouses, a radiograph building, and Building 01-103 as the drill bit maintenance and repair building, among others. The Drill Bit Repair Building was critical to the success of underground nuclear testing and is eligible under Criterion A for its contribution to broad patterns of history by maintaining specially designed equipment for underground nuclear testing at the NNSS. It is also eligible under Criterion C as it is the only recorded example of a facility built specifically for the maintenance of big-hole drill bits on the NNSS. As it retains both significance and integrity, it remains individually eligible under Criteria A and C. In addition to its individual significance, the Drill Bit Repair Building also contributes to the significance of the Area 1 Subdock Historic District as a representative of a big-hole drilling support facility necessary for underground nuclear testing. The building and the equipment therein were designed specifically for testing at the NNSS, where much of the early technology and methods for big-hole drilling were developed. Its removal will result in not only the demolition of a contributing element but also a change in the physical features of the district’s setting that contribute to its historic significance. The change in setting will diminish the district’s integrity. However, the district still contains numerous examples of other buildings constructed for the purpose of supporting big-hole drilling and remains eligible under Criteria A and C.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Bubbling Balanced Proactive CO 2 Capture and Reduction on a Triple-Phase Interface Nanoporous Electrocatalyst

The formation and preservation of the active phase of the catalysts at the triple-phase interface during CO 2 capture and reduction is essential for improving the conversion efficiency of CO 2 electroreduction toward value-added chemicals and fuels under operational conditions. Designing such ideal catalysts that can mitigate parasitic hydrogen generation and prevent active phase degradation during the CO 2 reduction reaction (CO 2 RR), however, remains a significant challenge. Herein, we developed an interfacial engineering strategy to build a new SnO x catalyst by invoking multiscale approaches. This catalyst features a hierarchically nanoporous structure coated with an organic F-monolayer that modifies the triple-phase interface in aqueous electrolytes, substantially reducing competing hydrogen generation (less than 5%) and enhancing CO 2 RR selectivity (~90%). This rationally designed triple-phase interface overcomes the issue of limited CO 2 solubility in aqueous electrolytes via proactive CO 2 capture and reduction. Concurrently, we utilized pulsed square-wave potentials to dynamically recover the active phase for the CO 2 RR to regulate the production of C1 products such as formate and carbon monoxide (CO). This protocol ensures profoundly enhanced CO 2 RR selectivity (~90%) compared with constant potential (~70%) applied at -0.8 V (V vs RHE). We further achieved a mechanistic understanding of the CO 2 capture and reduction processes under pulsed square-wave potentials via in situ Raman spectroscopy, thereby observing the potential-dependent intensity of Raman vibrational modes of the active phase and CO 2 RR intermediates. Finally, this work will inspire material design strategies by leveraging triple-phase interface engineering for emerging electrochemical processes, as technology moves toward electrification and decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Higher-order topology induced by structural buckling

Abstract Higher-order topological insulator (HOTI) states, such as two-dimension (2D) HOTI featured with topologically protected corner modes at the intersection of two gapped crystalline boundaries, have attracted much recent interest. However, the physical mechanism underlying the formation of HOTI states is not fully understood, which has hindered our fundamental understanding and discovery of HOTI materials. Here we propose a mechanistic approach to induce higher-order topological phases via structural buckling of 2D topological crystalline insulators (TCIs). While in-plane mirror symmetry is broken by structural buckling, which destroys the TCI state, the combination of mirror and rotation symmetry is preserved in the buckled system, which gives rise to the HOTI state. We demonstrate that this approach is generally applicable to various 2D lattices with different symmetries and buckling patterns, opening a horizon of possible materials to realize 2D HOTIs. The HOTIs so generated are also shown to be robust against buckling height fluctuation and in-plane displacement. A concrete example is given for the buckled $\beta $-Sb monolayer from first-principles calculations. Our finding not only enriches our fundamental understanding of higher-order topology, but also opens a new route to discovering HOTI materials.

42 ENGINEERING↗