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University Coalition for Fossil Fuel Energy Research

Following a nationwide open competition, the University Coalition for Fossil Energy Research (UCFER) was established in October 2015 through a cooperative agreement between Penn State and the Department of Energy (DOE) National Energy Technology Laboratory (NETL). Penn State lead UCFER with the objective of advancing basic and applied research for clean and low-carbon energy based on fossil fuels in support of the DOE’s mission. UCFER focused on research that improves the efficiency of production and use of fossil energy resources, while minimizing the environmental impacts and reducing greenhouse gas emissions. Penn State lead a team of nine universities (Massachusetts Institute of Technology, The Pennsylvania State University, Princeton University, Texas A&M University, University of Kentucky, University of Southern California, The University of Tulsa, University of Wyoming, and Virginia Polytechnic and State University) during the competition stage, adding seven more universities in 2017 (Carnegie Mellon University, Louisiana State University, The Ohio State University, University of North Dakota, University of Pittsburgh, University of Utah, and West Virginia University). This Coalition exhibited a wide geographical distribution across the U.S. bringing a wide variety of fossil energy expertise. This national university alliance was a major collaborative effort with NETL to address specific topics of R&D in NETL’s mission area, which involved one or more of NETL’s five core competencies (Geologic and Environmental Systems, Materials Engineering and Manufacturing, Energy Conversion Engineering, Systems Engineering and Analysis, and Computational Science and Engineering). The first five to six months of the project was the definitization stage. During this period, Penn State worked closely with NETL to finalize the Coalition organizational structure and By- Laws, prepare a statement of substantial involvement and a statement of project objectives, and develop operations and membership plans. A major component of this stage included preparing an execution plan to solicit research, evaluate proposals, recommend selected projects to NETL, and award projects. In addition, a plan was prepared to monitor projects, review projects, disseminate knowledge from research projects and develop an online system for Coalition research portfolio management. This included developing a website and several databases. The first of six rounds of solicitations started in mid-2016. Projects from the sixth solicitation started February 1, 2021, and ended January 31, 2023. Projects that were selected represented twelve technology lines. Approximately $16.6 million in funding was available for the six solicitations. Most of the funding was provided by DOE, Office of Fossil Energy (DOEFE) with the DOE Fuel Cells Technologies Office (DOE-FCTO) providing funding for a few projects. Coalition universities submitted 259 proposals in response to the solicitations, requesting approximately $67.0 million in funding, and forty-three projects were selected. However, one project withdrew after the principal investigator left the university. The management of the Coalition projects was a major activity by Penn State. Managing the Coalition projects consisted of monitoring the projects, reviewing the projects through annual technical review meetings, disseminating knowledge from the research projects, and developing an online system for Coalition research portfolio management. Penn State’s OMT monitored projects to ensure that all milestones (technical, schedule, budget) were met, expenditures were allowable, cost share (when applicable) were reported, and all technical reports were submitted. The OMT also posted the technical reports electronically on a secure members-only website for access and review by the Coalition members. Disseminating knowledge from the research projects was done through a website, newsletters, various meetings, conferences, journal articles, publicity/press releases, and project summaries that were prepared after each project was completed. Penn State kept NETL apprised of UCFER progress through quarterly reports (thirtyone were submitted by Penn State), verbal and written communications, yearly updates at the annual technical review meetings, and cost accrual reports. The UCFER project had a significant impacty. The UCFER program established the first national university alliance in fossil energy research with a major collaboration effort with DOE NETL that addressed specific topics in NETL’s research and development mission areas. It generated inter-university collaborations, which was another program interest. Twenty-two out of 259 proposals contained collaborations (≈8.5%) and three of forty-two funded projects involved inter-university collaborations (≈7.0%). The forty-two funded projects provided support at fourteen universities involving 269 personnel. Research was conducted by 106 faculty, 115 graduate and undergraduate students, forty-six research staff and post-doctoral scholars, and two visiting scholars. Students and post-doctoral scholars were also on-site at NETL through CRADAs. In addition, non-Coalition participants included six universities and sixteen companies and national laboratories. The non-Coalition participants were involved as subcontractors, providers of cost share, performed unpaid consultation and sample analysis, served as advisory board members, or were providers of samples and materials for testing. UCFER also produced visibility in that fifty-six refereed journal articles were published, fifty-seven conference papers and twenty-three posters were prepared, 190 presentations were given, eight patent applications were filed, two books/book chapters were written, and ten software codes were developed. Collaboration between NETL and the individual projects was a major requirement for all funded projects. This included NETL staff time to support collaboration, consultation, technical guidance, sample preparation and analysis, internships at NETL, on-site testing and equipment usage by Coalition participants at NETL, co-mentoring students, and coauthoring journal articles and conference papers. Collaboration was impacted by COVID-19 in that not all on-site activities could be performed. NETL personnel were coauthors on eight of the conference papers (fourteen percent of the conference papers that were prepared) and seventeen of the journal articles (thirty percent of the journal articles that were prepared). A website was developed for an online proposal solicitation and review process and to provide exposure to UCFER. A website analysis highlighted the large amount of member and general public interest in UCFER by interpreting access statistics from March 2016 through June 2023. Visitors to the site originated from many different organizations, businesses, and countries. The website provided a means to disseminate information to both the general public and the UCFER members and was successfully used for outreach activities. In addition, NETL required that RFP release, proposal submission, and proposal reviews all be performed online. Penn State successfully developed these capabilities in a secure section of the website, which were used throughout the UCFER project. It is recognized that each project had its technical successes. In addition, highlighted successes were compiled and summarized from the research projects. Information was requested from the PIs of completed projects. In addition, Penn State’s Operations Management Team reviewed subcontract reports to identify project successes. Examples of information requested from PIs included (not all-inclusive): new projects that have been funded as a result of UCFER funding; new commercial products; establishment of a new center; new patent; new software; best paper awards; highly-cited work; and graduate student successes. A total of forty-eight highlighted successes were reported.

01 COAL, LIGNITE, AND PEAT↗

Educating HPC Users in the use of advanced computing technology

We examine a multi-modal approach to educating and training users of an advanced computing technology testbed at the Institute for Advanced Computational Science at Stony Brook University. Ookami provides researchers worldwide with access to 176 Fujitsu A64FX compute nodes, this being the same processor technology powering the Japanese Fugaku supercomputer, the fastest computer in the world since June 2020. However, achieving high-performance on this Arm-based, leadership computing technology requires that users be familiar with details of computer architecture, performance analysis and modeling, and high-performance programming models that are commonly omitted in introductory programming courses. Indeed, regardless of their seniority, many of the testbed users are surprisingly unfamiliar with basic concepts such as vectorization, pipelining, latency/bandwidth, roofline models, computing energy/power, threads, and non-uniform memory access. These same concepts also pervade mainstream x86 technologies, so this is of widespread concern. Due to the national/global nature of our user community that is also very diverse in both discipline and experience, the inability to offer formal classes, and our experience that most people do not tend to read online documentation or training materials in sufficient depth, we have consciously employed multiple approaches that heavily emphasize (online) personal interactions and transfer of skills. Online documentation has been organized around best-practices and FAQs; twice-weekly hackathons and office hours via Zoom enable deep dives by both the team and the user community with multiple broad benefits; a Slack channel provides both real time and archived answers and discussions; and workshops, training and webinars target community needs as they arise. Furthermore, the perspective that these tools are being used in an educational setting rather than just for project communication makes them more effective and contributes to community success.

A64FX↗

Detecting Process Equipment Failures Using Acoustic Data and Machine Learning

Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence

Historically, neuroscience principles have heavily influenced artificial intelligence (AI), for example the influence of the perceptron model, essentially a simple model of a biological neuron, on artificial neural networks. More recently, notable recent AI advances, for example the growing popularity of reinforcement learning, often appear more aligned with cognitive neuroscience or psychology, focusing on function at a relatively abstract level. At the same time, neuroscience stands poised to enter a new era of large-scale high-resolution data and appears more focused on underlying neural mechanisms or architectures that can, at times, seem rather removed from functional descriptions. While this might seem to foretell a new generation of AI approaches arising from a deeper exploration of neuroscience specifically for AI, the most direct path for achieving this is unclear. Here we discuss cultural differences between the two fields, including divergent priorities that should be considered when leveraging modern-day neuroscience for AI. For example, the two fields feed two very different applications that at times require potentially conflicting perspectives. We highlight small but significant cultural shifts that we feel would greatly facilitate increased synergy between the two fields.

60 APPLIED LIFE SCIENCES↗

Interactive Web Application for Traffic Simulation Data Management and Visualization

As traffic simulation software becomes more effective for realistically simulating and analyzing traffic dynamics and vehicle interactions on the mesoscopic and microscopic level, the management, dissemination, and collaborative visualization of traffic simulation results produced by individual transportation planners presents a significant challenge. Existing online content management systems have a very limited capability in allowing users to query specific traffic simulation scenarios and geospatially visualize simulation results through shareable and interactive web interfaces. This paper presents a web-based application for promoting the archiving, sharing, and visualization of large-scale traffic simulation outputs. The application is developed to enhance cyber-physical controls, communications, and public education for collaborative transportation planning. Unique features of the web application include: (a) allowing users to upload their new traffic simulation scenarios (parameters and outputs), as well as search existing scenarios using easily accessible interfaces; (b) optimizing simulation output files with heterogeneous data formats and projected coordinate systems for web-based storage and management using a scalable and searchable data/metadata standard; (c) standardizing user-uploaded simulation outputs using web interfaces and data processing libraries with parallel computing capacity; and (d) providing shareable web visual interfaces for visualizing the traffic flow and signal information stored in simulation outputs (e.g., regional traffic patterns and individual vehicle interactions) and visually comparing multiple simulation outputs both spatially and temporally. Furthermore, the paper presents the conceptual design and implementation of this application, and demonstrates the application’s performance for sharing, comparing, and visualizing simulation outputs from VISSIM and SUMO, two commonly used traffic simulation software programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Ab initio evaluation of the electronic and optical properties of V B C B defect in wurtzite boron nitride as promising single-photon emitter

Single-photon emitters (SPEs) in the near-infrared (NIR) range with sharp and intense zero-phonon lines (ZPLs) of emission are critical for quantum communications. Certain local defects in wide-bandgap semiconductors create isolated occupied and unoccupied states within the bandgap of the host semiconductor and thus exhibit sharp ZPLs of emission. We designed and studied a defect in the wurtzite boron nitride as a potential SPE. It consists of a boron vacancy and a carbon atom substituting another boron atom (V B C B defect). The density of states is obtained within the GW method to identify favorable local defect states that may dominate optical transitions. The dielectric function and oscillator strength of the V B C B defect are obtained using the Bethe-Salpeter equation method to identify the optical excitations of the V B C B defect, from which we conclude that the defect could be a source of NIR emission with a narrow bright ZPL peak, thus an efficient SPE.

36 MATERIALS SCIENCE↗

Ultra-light antennas via charge programmed deposition additive manufacturing

Abstract The demand for lightweight antennas in 5 G/6 G communication, wearables, and aerospace applications is rapidly growing. However, standard manufacturing techniques are limited in structural complexity and easy integration of multiple material classes. Here we introduce charge programmed multi-material additive manufacturing platform, offering unparalleled flexibility in antenna design and the capability for rapid printing of intricate antenna structures that are unprecedented or necessitate a series of fabrication routes. Demonstrating its potential, we present a transmitarray antenna composed of an interconnected, multi-layered array of dielectric/conductive S-ring unit cells, reducing 94% mass of conventional antenna configurations. A fully printed circular polarized transmitarray system fed by a source and a Risley prism antenna system operating at 19 GHz both show close alignment between testing results and numerical simulations. This printing method establishes a universal platform, propelling discovery of new antenna designs and enabling data-driven design and optimizations where rapid production of antenna designs is crucial.

Science & Technology - Other Topics↗

Efficient hybrid explicit-implicit learning for multiscale problems

Splitting method is a powerful method to handle application problems by splitting physics, scales, domain, and so on. Many splitting algorithms have been designed for efficient temporal discretization. Here, in this paper, our goal is to use temporal splitting concepts in designing machine learning algorithms and, at the same time, help splitting algorithms by incorporating data and speeding them up. We propose a machine learning assisted splitting scheme which improves the efficiency of the scheme meanwhile preserves the accuracy. We consider a recently introduced multiscale splitting algorithms, where the multiscale problem is solved on a coarse grid. To approximate the dynamics, only a few degrees of freedom are solved implicitly, while others explicitly. This splitting concept allows identifying degrees of freedom that need implicit treatment. In this paper, we use this splitting concept in machine learning and propose several strategies. First, the implicit part of the solution can be learned as it is more difficult to solve, while the explicit part can be computed. This provides a speed-up and data incorporation for splitting approaches. Secondly, one can design a hybrid neural network architecture because handling explicit parts requires much fewer communications among neurons and can be done efficiently. Thirdly, one can solve the coarse grid component via PDEs or other approximation methods and construct simpler neural networks for the explicit part of the solutions. We discuss these options and implement one of them by interpreting it as a machine translation task. This interpretation of the splitting scheme successfully enables us using the Transformer since it can perform model reduction for multiple time series and learn the connection between them. We also find that the splitting scheme is a great platform to predict the coarse solution with insufficient information of the target model: the target problem is partially given and we need to solve it through a known problem which approximates the target. Our machine learning model can incorporate and encode the given information from two different problems and then solve the target problems. We conduct four numerical examples and the results show that our method is stable and accurate.

97 MATHEMATICS AND COMPUTING↗

Ultranarrow bright single-photon emitters in diamond with strong broadband phonon decoupling

Single-photon emitters are fundamental building blocks for quantum information processing, communication and sensing. However, unwanted interactions with bulk phonons in their host environment strongly limit their coherence and controllability. We report single color centers in nanodiamonds that are strongly and comprehensively decoupled from the bulk phononic environment. The color centers feature record-narrow linewidths down to 0.3 nm at room temperature and stable, bright emission, exceeding 10 Mcps in saturation. Notably, the bulk phonon sideband is almost entirely suppressed, revealing the presence of a single localized vibrational mode outside the diamond phonon band. Our observations and simulations point towards a unique mechanism for phonon decoupling in common wide-gap materials, based on a strongly radiative orbital transition coupled to a localized vibrational mode. The new color center enables qualitatively higher performance for applications in quantum networks and nanoscale sensing, and the exploration of new physical resources associated with vibrational states.

Sahoo, Swetapadma [ORNL]↗

Improving the creation of SiV centers in diamond via sub-μs pulsed annealing treatment

Silicon-vacancy (SiV) centers in diamond are emerging as promising quantum emitters in applications such as quantum communication and quantum information processing. Here, we demonstrate a sub-μs pulsed annealing treatment that dramatically increases the photoluminescence of SiV centers in diamond. Using a silane-functionalized adamantane precursor and a laser- heated diamond anvil cell, the temperature and energy conditions required to form SiV centers in diamond were mapped out via an optical thermometry system with an accuracy of ±50 K and a 1 μs temporal resolution. Annealing scheme studies reveal that pulsed annealing can obviously minimize the migration of SiV centers out of the diamond lattice, and a 2.5-fold increase in the number of emitting centers was achieved using a series of 200-ns pulses at a 50 kHz repetition rate via acousto-optic modulation. Our study provides a novel pulsed annealing treatment approach to improve the efficiency of the creation of SiV centers in diamond.

36 MATERIALS SCIENCE↗

Very-Low-Frequency transmitters bifurcate energetic electron belt in near-earth space

Very-Low-Frequency (VLF) transmitters operate worldwide mostly at frequencies of 10–30 kilohertz for submarine communications. While it has been of intense scientific interest and practical importance to understand whether VLF transmitters can affect the natural environment of charged energetic particles, for decades there remained little direct observational evidence that revealed the effects of these VLF transmitters in geospace. Here we report a radially bifurcated electron belt formation at energies of tens of kiloelectron volts (keV) at altitudes of ~0.8–1.5 Earth radii on timescales over 10 days. Using Fokker-Planck diffusion simulations, we provide quantitative evidence that VLF transmitter emissions that leak from the Earth-ionosphere waveguide are primarily responsible for bifurcating the energetic electron belt, which typically exhibits a single-peak radial structure in near-Earth space. Since energetic electrons pose a potential danger to satellite operations, our findings demonstrate the feasibility of mitigation of natural particle radiation environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗

Cryo-EM structures of engineered active bc 1- cbb 3 type CIII 2 CIV super-complexes and electronic communication between the complexes

Respiratory electron transport complexes are organized as individual entities or combined as large supercomplexes (SC). Gram-negative bacteria deploy a mitochondrial-like cytochrome (cyt) bc 1 (Complex III, CIII 2 ), and may have specific cbb 3 -type cyt c oxidases (Complex IV, CIV) instead of the canonical aa 3 -type CIV. Electron transfer between these complexes is mediated by soluble ( c 2 ) and membrane-anchored ( c y ) cyts. Here, we report the structure of an engineered bc 1 - cbb 3 type SC (CIII 2 CIV, 5.2Å resolution) and three conformers of native CIII 2 (3.3 Å resolution). The SC is active in vivo and in vitro, contains all catalytic subunits and cofactors, and two extra transmembrane helices attributed to cyt c y and the assembly factor CcoH. The cyt c y is integral to SC, its cyt domain is mobile and it conveys electrons to CIV differently than cyt c 2 . The successful production of a native-like functional SC and determination of its structure illustrate the characteristics of membrane-confined and membrane-external respiratory electron transport pathways in Gram-negative bacteria.

42 ENGINEERING↗

Efficient and Robust p-Type Transistor Based on Ultrawide-Bandgap Semiconductor

The p-type transistor is an indispensable component of semiconductor technology, enabling a complementary operation with n-channel transistors for computation, storage, and communication. Achieving both high robustness and high efficiency is highly desirable but challenging for p-type transistors due to the limited semiconductors with reliable hole transport and their high activation energies. Here, in this study, we achieved a robust yet efficient p-type transistor by heterogeneously integrating an ultrawide-bandgap semiconductor and a high-κ dielectric layer through van der Waals integration. The p-type transistor employs a two-dimensional hole channel on hydrogenated diamond (bandgap 5.6 eV) combined with a high-κ (30.5) SrTiO 3 perovskite membrane. At room temperature, the transistor exhibits stable operation with a high on-current (∼200 mA/mm), low subthreshold swing (70 mV/dec), high hole mobility (566 cm 2 /(V·s) to 572 cm 2 /(V·s)), and high on–off ratio (∼10 9 ). Furthermore, tuning the annealing temperature allows operation in either enhancement or depletion mode. The robust p-type transistor with high efficiency holds great potential for future power electronics, ultraviolet (UV) optoelectronics, and harsh-environment electronic applications.

high-κ membrane↗

Mass Spectral Imaging to Map Plant–Microbe Interactions

Plant–microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced Recovery Opportunities in the Appalachian Basin

The Midwest Regional Carbon Sequestration Partnership (MRCSP) has incorporated the work of geologic research teams (Geoteams) in its regional characterization, project planning and carbon dioxide (CO2) injection implementation work since the partnership was established by the U.S. Department of Energy (DOE) in 2003. Over this 16-year period, the cohort of Geoteams has grown from five to ten states and has contributed to the characterization of geologic sequestration opportunities, refinement of reservoir and seal data, and supported injection efforts through both predictive and post-injection assessments. The regional characterization work conducted by the Geoteams during the MRCSP Phase III project period (2010 – 2019) focused on the following tasks: (1) refinement of geologic seals/reservoir systems; (2) assessment of Atlantic Coastal Plain and offshore opportunities; (3) expanded assessments of oil and gas fields, particularly as they relate to enhanced recovery opportunities; (4) regional support for implementation of carbon capture utilization and storage (CCUS) in the partnership area; and (5) communication and data sharing. The findings of this work are summarized in the final report entitled Final Report of Geologic Carbon Capture Utilization and Storage Opportunities in the form of a state-by-state presentation for the MRCSP Region. In addition to the capstone deliverable mentioned above, the Geoteams have also prepared a series of topical reports to elaborate on specific geologic intervals and/or geographic areas of study completed during the Phase III project period. Specifically, these topical reports address: (1) the Atlantic Coastal Plain and adjacent offshore; (2) Cambro-Ordovician reservoirs/seals in the region; (3) enhanced oil and gas recovery opportunities in the Appalachian Basin; and (4) enhanced oil recovery (EOR) in the Michigan Basin. The remainder of this topical report presents our findings relative to enhanced recovery opportunities in the Appalachian Basin.

54 ENVIRONMENTAL SCIENCES↗

Radiation Effects on Network on Chips (NoC) Laboratory Directed Research and Development (LDRD) project

This project was motivated by State-of-the-Art (SOTA) technology that incorporates Network on Chips (NOC) for efficient data communication across the various computer kernels. For example, on the AMD Versal Field Programmable Gate Arrays (FPGA), an NoC has been incorporated for fast data communication from the programmable logic and other computer kernels (processing system, adaptable intelligence engines, etc.). The radiation effects on the legacy technology of this FPGA, such as the programmable logic, are well understood, and established methods exist to measure cross-sections when new families/generations are released; however, newly incorporated technologies, such as the NoC, are not fully understood and could introduce new failure points into the mission space.

36 MATERIALS SCIENCE↗

Ultrafast Jahn‐Teller Photoswitching in Cobalt Single‐Ion Magnets

Abstract Single‐ion magnets (SIMs) constitute the ultimate size limit in the quest for miniaturizing magnetic materials. Several bottlenecks currently hindering breakthroughs in quantum information and communication technologies could be alleviated by new generations of SIMs displaying multifunctionality. Here, ultrafast optical absorption spectroscopy and X‐ray emission spectroscopy are employed to track the photoinduced spin‐state switching of the prototypical complex [Co(terpy) 2 ] 2+ (terpy = 2,2′:6′,2″‐terpyridine) in solution phase. The combined measurements and their analysis supported by density functional theory (DFT), time‐dependent‐DFT (TD‐DFT) and multireference quantum chemistry calculations reveal that the complex undergoes a spin‐state transition from a tetragonally elongated doublet state to a tetragonally compressed quartet state on the femtosecond timescale, i.e., it sustains ultrafast Jahn‐Teller (JT) photoswitching between two different spin multiplicities. Adding new Co‐based complexes as possible contenders in the search for JT photoswitching SIMs will greatly widen the possibilities for implementing magnetic multifunctionality and eventually controlling ultrafast magnetization with optical photons.

36 MATERIALS SCIENCE↗