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At least 415 records · Page 23

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

60 APPLIED LIFE SCIENCES↗

Energy Assets Transformation Web Mapping Application

This submission contains the link and geospatial materials used in the Energy Assets Transformation Web Mapping Application. The zip file contains 19 geospatial layers in a file geodatabase called EAT.gdb to be grouped in the following categories. 1. Industrial Assets: Coal Generation Units Retirements 2012-2040 (EIA); Examples of Repurposing Projects (32 projects in total); Abandoned Coal Mines (CORD, SkyTruth); Abandoned or Orphaned Wells (for ten states only). 2. Energy Transition Communities: 48C (e) Tax Credits - Designated Energy Communities (IRA); Index of Deep Disadvantage; Local Energy Action Program (LEAP); EJ Index for Proximity to Hazardous Waste (EPA). 3. Regional Landscape: State-Level Funding Programs (relevant to repurposing projects, for 2022 and 2023 only); Coal Flows from Mine to Plant 2021 (EIA), Variable Renewable Energy Shares (Wind and Solar, 2021, EIA). 4. Supporting Infrastructure: Railroads (HIFLD), Electric Power Transmission Lines (HIFLD), Major Highways (NHPN, DOT), Major Ports (National Atlas of the U.S.); Independent System Operators (HIFLD), NERC Regions and Subregions (HIFLD).

abandoned coal mines↗

Estimation of Participation Factors Using the Synchrosqueezed Wavelet Transform

This paper proposes a data-driven approach for estimating participation factors for a power system using only simulation results on selected disturbances. The approach is purely response-based and does not need a linearized system model for eigen-analysis, which makes it applicable to systems whose detailed, complete mathematical models are not available. Considering the unavoidable nonlinearity as exhibited in the transient period of a system response, the Synchrosqueezed Wavelet Transform is applied to simulated responses for modal analysis to obtain participation factors. Based on simulations of Kundur's two-area system using both the electromagnetic transient model and phasor model, the participation factors estimated by the proposed approach are compared with two other signal processing tools, the Prony analysis and continuous wavelet transform, and are also benchmarked with conventional model-based participation factors.

participation factor↗

An electrified boom actuation system with energy regeneration capability driven by a novel electro-hydraulic unit

This paper presents a novel electrified solution for linear actuation systems, which has undergone a successful in-vehicle demonstration, marking a significant advancement in this field. Aligned with the growing trend towards electrification, this solution holds promise for a wide range of off-road applications. The showcased electrohydraulic actuation architecture enables efficient four-quadrant operation and incorporates energy recovery capabilities. At the core of the system lies a distinctive electro-hydraulic unit, integrating a fixed hydraulic pump and a variable-speed electric motor into a compact and powerful entity. A specialized hydraulic system is designed to efficiently transform electrical energy from the electro-hydraulic unit into boom cylinder actuation. The sizing of the system is determined by the boom operation of a commercial compact loader. The maximum power output of the electro-hydraulic system is approximately 15 kW. The components of the proposed system are integrated into the reference vehicle, and comprehensive performance tests are conducted. The results of the tests performed on the vehicle with the boom lifting and lowering cycle indicate an overall system efficiency of 60%. The electrified solution consumes only about one-third of the energy used by the conventional boom actuation system on the reference machine, while exhibiting energy savings exceeding 75% during specific work phases. The energy savings come mainly from energy regeneration and minimal loss from throttling through the specialized hydraulic circuit design. Finally, the successful demonstration on the reference vehicle underscores the practicality and effectiveness of the proposed electrified solution in current mobile hydraulic applications

42 ENGINEERING↗

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗

Generation of lognormal synthetic Lyman-α forest spectra for P 1 D analysis

The one-dimensional flux power spectrum (P 1 D ) of the Lyman-α forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include the amplitude and shape of the matter power spectrum, the thermal history of the IGM, the sum of neutrino masses, and potential small-scale fluctuations due to the nature of dark matter. However, P 1 D is also highly sensitive to observational and instrumental systematics, making accurate synthetic spectra essential for validating analyses and quantifying these effects, especially in high-volume surveys like the Dark Energy Spectroscopic Instrument (DESI). We present an efficient lognormal mock framework for generating one-dimensional Lyman-α forest spectra tailored for P 1 D analysis. Our method captures the redshift evolution of the mean transmitted flux and the scale-dependent shape and amplitude of the one-dimensional flux power spectrum by tuning Gaussian field correlations and transformation parameters. Across the DESI Early Data Release (EDR) redshift range (2.0 ≤ z ≤ 3.8), and a wide range of scales (10 -4 s km -1 ≤ k ≤ 1.0 s km -1 ), our mocks recover the mean flux evolution with redshift to sub-percent accuracy, and the P 1 D at the percent level. Additionally, we discuss potential extensions of this framework, such as the incorporation of astrophysical contaminants, continuum uncertainties, and instrumental effects. Such improvements would expand its utility in ongoing and upcoming surveys and enable a broader range of validation efforts and systematics studies for P 1 D inference and precision cosmology.

Lyman alpha forest↗

Investigation of thermal hydraulic behavior of the High Temperature Test Facility's lower plenum via large eddy simulation

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High–Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next–generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds–averaged Navier–Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

97 MATHEMATICS AND COMPUTING↗

Measurement of the small-scale 3D Lyman- α forest power spectrum

Small-scale correlations measured in the Lyman-α (Lyα) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, P 3D , of the Lyα forest at wavenumbers k corresponding to small, ~ Mpc scales. In order to estimate P 3D from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Lyα forest, P 1D . Further, this methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Lyα forest sample, providing as a proof of principle, a first P 3D measurement averaged over two redshift bins z = 2.2 and z = 2.4. This work highlights the potential for forthcoming P 3D measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of P 1D .

79 ASTRONOMY AND ASTROPHYSICS↗

Topological Machine Learning Methods for Power System Responses to Contingencies

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remains untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topology-based system that depends on a neural network architecture for impact metric classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn more about the complex relationships between electrical properties and local topological measurements on their simulated response to contingencies for the NREL-SIIP power system.

contingency analysis↗

Broadband Fourier-Transform Optical Photothermal Infrared Spectroscopy and Imaging

Infrared (IR) spectroscopy is a powerful method for mapping chemical heterogeneity on the microscale. Synchrotron IR radiation uniquely provides a high brightness and broad bandwidth to further extend the capabilities of IR spectroscopic imaging. However, the diffraction-limited spatial resolution of IR spectroscopy is insufficient for studies requiring submicrometer spatial differentiation. Optical photothermal IR (O-PTIR) microscopy is a powerful, emerging method that overcomes the IR diffraction limit in IR hyperspectral imaging by employing a modulated IR beam and a visible probe laser beam to detect local temperature-induced modulation at the visible diffraction limit. In this work, we extend the spectral range of photothermal infrared measurements by incorporating a synchrotron IR source, demonstrating a combined synchrotron-based O-PTIR modality that enables high spatial resolution far-field chemical imaging spanning the entire mid-IR range. Both optical- and fluorescence-detected photothermal modalities were performed using a step-scan interferometer, demonstrating improved spectral range (541-4000 cm-1) when compared to optical photothermal microscopy with commercial laser sources (800-1800 cm-1 for this particular source) and improved spatial resolution, when compared to synchrotron microspectroscopy measurements. Following these initial validation studies, synchrotron Fourier-transform fluorescence-detected photothermal IR spectroscopy in combination with synchrotron microspectroscopy measurements was used to differentiate cells in mouse brain tissue sections, which requires submicron spatial resolutions beyond those accessible by IR spectroscopy alone.

Razumtcev, Aleksandr↗

Distributed water desalination and purification systems: perspective and future directions

Distributed water treatment and desalination (DWTD) systems are critical for the development of a diverse water portfolio of the desired quality and intended use at the target location. Widespread adoption of DWTD has been hampered given the need for round-the-clock monitoring and the lack of local technical expertise for system management. However, self-adaptive operation, real-time remote monitoring, supervisory control, and asset management of DWTD systems are now feasible with the implementation of advanced local system control, cyberinfrastructure that facilitates real-time cloud-based analytics, data management, and artificial intelligence–powered decision support. Such an approach will introduce transformative virtual networks of DWTD systems to provide needed water to locations that are not served by centralized and satellite water treatment and desalination systems.

Cohen, Yoram [University of California, Los Angele↗

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗

Dynamic Nanoscale Spatial Heterogeneity in a Perovskite-to-Brownmillerite Topotactic Phase Transformation

Phase transitions are omnipresent in modern condensed matter physics and its applications. In solids, first-order phase transformations typically occur by nucleation and growth under nonequilibrium conditions. Under constant external conditions, e.g., constant annealing temperature and pressure, the nucleation and growth dynamics are often thought of as spatially and temporally independent. Here, in situ Bragg X-ray photon correlation spectroscopy (XPCS) reveals nanoscale spatial and dynamical heterogeneity in the perovskite-to-brownmillerite topotactic phase transformation in La 0.7 Sr 0.3 CoO 3 thin films annealed under constant reducing conditions over a time span of multiple hours. Specifically, a time scale associated with domain growth remains stable, with a corresponding domain wall speed of v d = 6 ± 0.5 × 10 –4 nm/s (2 ± 0.2 nm/h), while a slower time scale, associated with temperature-driven depinning of domains, leads to accelerating dynamics with time scales following an aging power law with exponent −2.2 ± 0.5. This experiment demonstrates that Bragg XPCS is a powerful tool to study nanoscale dynamics in structural phase transformations, with the ability to extract quantitative average values related to nanodomain motion in situ. Furthermore, the results are relevant for phase engineering of phase-change devices, as they show that nanoscale dynamics, linked to domain and domain-wall motion, can continuously evolve and speed up with time, even hours after the initiation of the phase transformation, with potential repercussions on electrical performance.

X-ray photon correlation spectroscopy↗

Switching speed limits in electrically driven VO 2 structural Mott–Peierls transition

Mott materials are archetypal quantum systems actively explored as next-generation electronic and photonic platforms, with potential applications spanning non-Von Neumann computing, robotics, energy storage, and microwave technologies. Among these, vanadium dioxide (VO 2 ) has emerged as one of the most intensively studied compounds, owing to its sharp, near-room-temperature insulator-to-metal phase transition. VO 2 also serves as a benchmark system for testing cutting-edge theories and experimental techniques. Here, we directly visualize the electrically driven transition dynamics in VO 2 using a microwave-driven, frequency-tunable pulsed transmission electron microscope that combines nanometer spatial and picosecond temporal resolution. Under high-frequency (MHz–GHz) excitation, we capture the ultrafast nucleation, propagation, and dissolution of metallic domains within an operating device over millions of reversible cycles. We observe the ultrafast formation of consistent metallic nuclei beneath the electrodes, followed by the propagation of a structural phase front at 4.54 nm/ns. Our experiments show that phonon-mediated structural recovery ultimately limits reversible switching of VO 2 at GHz frequencies, and that a tunable regime for reversible operation spans from kHz to GHz through device engineering. Beyond VO 2 , our approach provides a powerful framework for probing non-equilibrium structural transformations in correlated and functional materials under realistic electrical stimuli.

36 MATERIALS SCIENCE↗

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗

Roadmap on basic research needs for laser technology

Motivated by the profound impact of laser technology on science, arising from an increase in focused light intensity by seven orders of magnitude and flashes so short electron motion is visible, this roadmap outlines the paths forward in laser technology to enable the next generation of science and applications. Despite remarkable progress, the field confronts challenges in developing compact, high-power sources, enhancing scalability and efficiency, and ensuring safety standards. Future research endeavors aim to revolutionize laser power, energy, repetition rate and precision control; to transform mid-infrared sources; to revolutionize approaches to field control and frequency conversion. These require reinvention of materials and optics to enable intense laser science and interdisciplinary collaboration. The roadmap underscores the dynamic nature of laser technology and its potential to address global challenges, propelling progress and fostering sustainable development. Ultimately, advancements in laser technology hold promise to revolutionize myriad applications, heralding a future defined by innovation, efficiency, and sustainability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Variational Self-Consistent Theory for Beam-Loaded Cavities

A new variational theory is presented for beam loading in microwave cavities. The beam{field interaction is formulated as a dynamical interaction whose stationarity according to Hamilton’s principle will naturally lead to steady-state solutions that indicate how a cavity’s resonant frequency, Q and optimal coupling coefficient will detune as a result of the beam loading. A driven cavity Lagrangian is derived from first principles, including the effects of cavity wall losses, input power and beam interaction. The general formulation is applied to a typical klystron input cavity to predict the appropriate detuning parameters required to maximize the gain (or modulation depth) in the average Lorentz factor boost, (Δ γ). Numerical examples are presented, showing agreement with the general detuning trends previously observed in the literature. The developed formulation carries several advantages for beam-loaded cavity structures. It provides a self-consistent model for the dynamical (nonlinear) beam{field interaction, a procedure for maximizing gain under beam-loading conditions, and a useful set of parameters to guide cavity-shape optimization during the design of beam-loaded systems. Enhanced clarity of the physical picture underlying the problem seems to be gained using this approach, allowing straightforward inclusion or exclusion of different field configurations in the calculation and expressing the final results in terms of measurable quantities. Two field configurations are discussed for the klystron input cavity, using finite magnetic confinement or no confinement at all. Formulating the problem in a language that is directly accessible to the powerful techniques found in Hamiltonian dynamics and canonical transformations may potentially carry an additional advantage in terms of analytical computational gains, under suitable conditions

43 PARTICLE ACCELERATORS↗

Metastability of Liquid Water Freezing into Ice VII under Dynamic Compression

The ubiquitous nature and unusual properties of water have motivated many studies on its metastability under temperature- or pressure-induced phase transformations. Here, nanosecond compression by a high-power laser is used to create the nonequilibrium conditions where liquid water persists well into the stable region of ice VII. Through our experiments, as well as a complementary theoretical/computational analysis based on classical nucleation theory, we report that the metastability limit of liquid water under nearly isentropic compression from ambient conditions is at least 8 GPa, higher than the 7 GPa previously reported for lower loading rates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗