POWER: Data Transparency Tools via the New PaRameter Uncertainty ViEwer (PRUVE)
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Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures
Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.
Abstract Cholesteric liquid crystal elastomers (CLCEs) hold great promise for mechanochromic applications in anti‐counterfeiting, smart textiles, and soft robotics, thanks to the structural color and elasticity. While CLCEs are printed via direct ink writing (DIW) to fabricate free‐standing films, complex 3D structures are not fabricated due to the opposing rheological properties necessary for cholesteric alignment and multilayer stacking. Here, 3D CLCE structures are realized by utilizing coaxial DIW to print a CLC ink within a silicone ink. By tailoring the ink compositions, and thus, the rheological properties, the cholesteric phase rapidly forms without an annealing step, while the silicone shell provides encapsulation and support to the CLCE core, allowing for layer‐by‐layer printing of self‐supported 3D structures. As a demonstration, free‐standing bistable thin‐shell domes are printed. Color changes due to compressive and tensile stresses can be witnessed from the top and bottom of the inverted domes, respectively. When the domes are arranged in an array and inverted, they can snap back to their base state by uniaxial stretching, thereby functioning as mechanical sensors with memory. The additive manufacturing platform enables the rapid fabrication of 3D mechanochromic sensors thereby expanding the realm of potential applications for CLCEs.
NASA's scientific expertise and data products are enhancing cities' environmental monitoring activities by pioneering applications of remote sensing and model-based Earth Observations at the urban scale. The above activities have greatly benefitted from engaging stakeholders and city practitioners from the start. Further, NASA's collaborations with cities have: Advanced NASA science, in testing new products and validating of satellite datasets, while meeting the needs of city governments. Broadened Rio de Janeiro's regional viewpoint and strengthened its relationships with neighboring cities. Scientific collaborations with cities benefit from: Selecting city partners with a high level of technical capacity and willing to make strong investments in joint projects. Sustained communication and face-to-face interactions. Well-defined deliverables, with dedicated resources and personnel. Pairing global datasets and projections with in situ measurements and local knowledgeSensitivity to local working culture and politics.
Beginning with the launch of the European Columbus module planned for December 2007, we approach a transition in the assembly of the International Space Station (ISS) that is of great importance for the sciences. During the following 18 months, we will operate the first experiments in Columbus physical science resource facilities and also launch and commission the Japanese Kibo module. In addition, two Multi-purpose Logistics Module (MPLM) flights will deliver the U.S. Combustion Integrated Rack (CIR) and Fluids Integrated Rack (FIR) along with their first science experiments. These facilities provide significant new capabilities for basic and applied physical science research in microgravity. New life support technologies will come online throughout 2008, and we will reach the milestone of a 6-person crew planned for April 2009. A larger crew enables significant more scientific use of all the facilities for the life of ISS. Planning for the use of the International Space Station as a national laboratory is also maturing as we near the completion of assembly, enabling access to ISS as a research platform for other government agencies and the private sector. The latest updates on National Laboratory implementation will also be provided in this presentation. At the same time as these significant increases in scientific capability, there have been significant ongoing accomplishments in NASA's early ISS research both exploration related and fundamental research. These accomplishments will be reviewed in context as harbingers of the capabilities of the International Space Station when assembly is complete. The Vision for Space Exploration serves to focus NASA's applied investigations in the physical sciences. However, the broader capability of the space station as a National Laboratory and as a nexus for international collaboration will also influence the study of gravity-dependent processes by researchers around the world.
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This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.
JSNS 2 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment that is searching for sterile neutrinos via the observation of $\overline{ν}$ μ → $\overline{ν}$ e appearance oscillations using neutrinos from muon decay-at-rest. For this search, rejecting cosmic-ray-induced neutron events by Pulse Shape Discrimination (PSD) is essential because the JSNS2 detector is located above ground, on the third floor of the building. We have achieved 94.95% ± 0.15% rejection of neutron events while keeping 92.82% ± 1.77% of signal, electron-like events using a data-driven likelihood method. This article will report the PSD technique using the full fiducial volume of the JSNS2 detector.
The U.S. Department of Energy's Advanced Photon Source (APS) is one of the world’s most productive x-ray light source facilities. Each year, the APS provides high-brightness x-ray beams to a diverse community of more than 5,000 researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. Researchers using the APS produce over 2,000 publications each year detailing impactful discoveries, and solve more vital biological protein structures than users of any other x-ray light source research facility. APS x-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. The APS occupies an 80-acre site on the Argonne campus, about 25 miles from downtown Chicago, Illinois. It shares a site with the Center for Nanoscale Materials and the Advanced Protein Characterization Facility.
The U.S. Department of Energy's Advanced Photn Source (APS) is one of the world’s most productive x-ray light source facilities. Each year, the APS provides high-brightness x-ray beams to a diverse community of more than 5,000 researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. Researchers using the APS produce over 2,000 publications each year detailing impactful discoveries, and solve more vital biological protein structures than users of any other x-ray light source research facility. APS x-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. The APS occupies an 80-acre site on the Argonne campus, about 25 miles from downtown Chicago, Illinois. It shares a site with the Center for Nanoscale Materials and the Advanced Protein Characterization Facility.
The objective of the North American meeting of the International Society for Microbial Electrochemistry and Technology (NA-ISMET 2021, postponed from 2020 due to COVID-19) was to provide a welcoming space for an interdisciplinary group of researchers, primarily based in North America, to discuss their latest discoveries and innovative ideas on both basic science and applied technology in the field of microbial electrochemistry. After two years of limited travel and research interactions due to COVID-19, an in-person meeting was urgently needed to facilitate conversations and collaborations that help move the field forward. NA-ISMET 2021 was co-organized by Moh El-Naggar from the University of Southern California (USC) and Orianna Bretschger from Aquacycl Inc. The meeting took place on November 17 – 19, 2021 at the Michelson Center for Convergent Biosciences of USC. We hosted a total number of 65 registered participants from across the United States and several international participants. Thanks to the generous support from the Department of Energy, Air Force Office of Scientific Research, Office of Naval Research, the Army Research Office, the ISMET organization, and Gamry Instruments Inc., we were able to waive registration fees for all participants and reduce travel cost for several early-career researchers. The scientific program included 28 talks (16 from early-career researchers) and 24 posters that highlighted recent advances in microbial electrochemistry.
We present the first nuclear cross-section measurements of (p,$\gamma$) and (p,n) reactions on 118 Te at energies relevant for the $\gamma$-process nucleosynthesis. Absolute cross-section values for center-of-mass energies of 6, 7 and 10 MeV are provided, together with a theoretical extrapolation to the Gamow window. This experiment marks the first time that direct proton-induced reactions have been measured on a radioactive ion beam at the Experimental Storage Ring (ESR) at GSI, Darmstadt. This paves the way for a large variety of measurements, delivering new constraints for explosive nucleosynthesis and for physics beyond nuclear stability.
Space research and effect on other branches of science, especially applied mechanics
We report the application of the new elimination of Rutherford elastic scattering technique for the measurement of proton-induced reaction cross sections utilizing stored ions decelerated to astrophysical energies. This approach results in a background reduction factor of about 1 order of magnitude, enabling the first measurement of a (p, n) cross section in a storage ring. Here, the reaction channels 124 Xe(p,n) and 124 Xe(p,γ) have been studied just above the neutron threshold energy. The new data provide valuable constraints for Hauser-Feshbach theory and extrapolation of the (p,γ) cross section to lower energies. Most importantly, for nuclei of limited availability, the method represents a powerful improvement to efficiently study proton-induced reactions at energies within or close to the astrophysical Gamow window, bringing many reaction measurements within reach that were previously inaccessible in the laboratory.
The Fast Beam Condition Monitor (FBCM) is a standalone luminometer for the High Luminosity LHC (HL-LHC) program of the CMS Experiment at CERN. The detector is under development and features a new, radiation-hard, front-end application-specific integrated circuit (ASIC) designed for beam monitoring applications. The achieved timing resolution of a few nanoseconds enables the measurement of both the luminosity and the beam-induced background. The ASIC, called FBCM23, features six channels with adjustable shaping times, enabling in-field fine-tuning. Each ASIC channel outputs a single binary asynchronous signal encoding time-of-arrival and time-over-threshold information. The FBCM is based on silicon-pad sensors, with two sensor designs presently being considered. This paper presents the results of tests of the FBCM detector prototype using both types of silicon sensors with hadron, muon, and electron beams. Irradiated FBCM23 ASICs and silicon-pad sensors were also tested to simulate the expected conditions near the end of the detector's lifetime in the HL-LHC radiation environment. Based on test results, direct bonding between the sensor and ASIC was chosen, and an optimal bias voltage and ASIC threshold for FBCM operation were proposed. The current design of the front-end test board was validated following the beam test and is now being used for the first front-end module, which is expected to be produced in summer 2025. These results represent a major step forward in validating the FBCM concept, first version of the firmware and establishing a reliable design path for the final detector.
Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.