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At least 73 records · Page 4

AmeriFlux FLUXNET-1F US-UiC University of Illinois Maize-Soy

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UiC University of Illinois Maize-Soy. This is the FLUXNET version of the carbon flux data for the site US-UiC University of Illinois Maize-Soy produced by applying the standard ONEFlux (1F) software. Site Description - Agricultural field planted with maize in a three year rotation with soy (maize-maize-soy). The first soy rotation year was 2010. This field is typically planted in May and harvested in October. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [USDA/ARS]↗

Reimagining DOE Lab-University Partnership for the AI Era

This report describes observations and suggestions from a workshop on needs for partnerships between national laboratories and universities in the AI era. The workshop took place over two days in March of 2024 at Texas A&M University’s Bush School of Government and Public Service Washington, D.C., teaching site. Through good fortune this happened to be at the peak of cherry blossom season and the weather was beautiful. In attendance were professors and leadership from universities across the nation, members of four national laboratories, and a representative of the Office of Critical and Emerging Technologies in Department of Energy (DOE). This group spanned a broad range of disciplines—applied mathematics, materials science, nuclear security, intelligence, and more. The workshop also had the benefit of insights from Charlie McMillan, former director of Los Alamos National Laboratory, and retired Air Force Lieutenant General Jack Shanahan, who led AI efforts at the Pentagon.

42 ENGINEERING↗

Environmental Extremes: Building a New Research Partnership between the University of Nevada Reno and the Pacific Northwest National Laboratory (Final Report)

This project focused on strengthening research partnership and collaboration between the University of Nevada, Reno (UNR) and the Pacific Northwest National laboratory (PNNL) in two focused areas: wildfires and hydrology in the context of environmental extremes. The goal was to overcome barriers and bring UNR university researchers, students, and postdocs up to speed and entrained into DOE/SC/BER /Earth and Environmental System Science Division’s (EESSD) environmental research enterprise. UNR continues to work with the Earth and Biological Sciences Directorate (EBSD) at PNNL to create a broad new collaborative research program connecting scientists and research faculty at the two institutions. This research partnership has been designed to increase the capabilities and velocities of both institutions by developing long-term relationships between researchers from each institution, exposing university researchers to the deep capabilities in the DOE National Laboratories and user facilities, and establishing a pipeline of skilled and experienced graduate students and postdoctoral researchers ready to work alongside DOE scientists to take on grand challenge science problems. These collaborations are intended to ultimately benefit the public by advancing scientific discovery, unleashing the scientific potentials through collaboration and connection, enriching the technical and scientific competitiveness of our nation, and enabling the development of a skilled workforce to tackle the critical scientific challenges that face our nation’s security, infrastructure, and prosperity.

54 ENVIRONMENTAL SCIENCES↗

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗

University Data Management Pilot Utilizing the Nuclear Research Data System

Background In 2022, the Office of Science and Technology Policy (OSTP) issued a memo that significantly reshaped the landscape of access to federally funded research. The memo mandated that all taxpayer-funded research be made available to the public without delay upon publication, without an embargo period, superseding the 2013 OSTP public access policy. This public access policy promotes transparency and the democratization of knowledge, ensuring that the fruits of scientific endeavors funded by federal agencies could be immediately accessed and built upon by scientists, educators, students, and the public at large. To implement the requirements of the OSTP guidance and DOE Public Access Plan, the Office of Nuclear Energy (NE) has implemented public access plan guidance and has identified several areas where better data management practices would further expand public access to important nuclear energy related scientific data, reports, and other technical products. Significant NE supported efforts are already underway for data management and public access to important nuclear energy related data.1 2 To address gaps in data management practices, and improve retention and accessibility of data, NE is actively exploring enhanced data management options utilizing its high-performance computing resources administered by its Nuclear Scientific User Facility Program. A newly piloted system, the Nuclear Research Data System (NRDS) acts as a portal for data collection and dissemination. Nuclear Energy University Program Research and Development Portfolio According to Web of Science, NEUP has produced 2,345 journal publication that have been cited more than 61,000 times3 and countless conference proceedings. These publications are publicly available through OSTI.gov and in the open literature. Additional scientific and technical products including project milestones that are not publications and NEUP project final reports are vetted through OSTI.gov and released once reviewed and approved by DOE. Since 2009, NEUP has awarded close to 1,000 different R&D projects in technical areas across the NE research programs. As of June 2023, 512 NEUP reports are publicly available on OSTI. The underlying data for projects is still held at universities, and data transfer, co-location, and dissemination has not occurred in a systematic way. NEUP data is currently accessible through myriad university-based data repositories, or through direct requests to PIs. The program identified this patchwork of repositories, or often lack of publicly available data, as a significant barrier to an organized, accessible, and comprehensive solution to sharing data with the larger nuclear energy community. Approach The goal of this pilot project is to establish a pathway to a consolidated long-term repository for NEUP project data. To accomplish this goal, the pilot strives to accomplish the following objectives: Establish data collection standards, including a standard set of required supplementary information to contextualize and support raw data files. Work with the HPC group collect and upload information and to modify the NRDS system, as needed, to support a standardized approach. Resolve potential barriers to successful roll out of an expanded data collection strategy, including modifying data management plan guidelines and establishing a document and data release process that accounts for potential intellectual property and/or export control concerns. Results Overall, the pilot was successful in collecting 8,982 raw and processes data files, 220 reports, 56 calibration files, and 5,931 other supplementary documents. Supplementary documents included experimental plans, methods, journal publications and conference proceedings, milestone reports, and final reports. Figure 2 shows the number of data sets and supplementary project information provided by each project. Projects has significantly different input, depending on experimental data produced and completeness of the datasets provided.

Data collection↗

A Printed Microscopic Universal Gradient Interface for Super Stretchable Strain‐Insensitive Bioelectronics

Abstract Stretchable electronics capable of conforming to nonplanar and dynamic human body surfaces are central for creating implantable and on‐skin devices for high‐fidelity monitoring of diverse physiological signals. While various strategies have been developed to produce stretchable devices, the signals collected from such devices are often highly sensitive to local strain, resulting in inevitable convolution with surface strain‐induced motion artifacts that are difficult to distinguish from intrinsic physiological signals. Here all‐printed super stretchable strain‐insensitive bioelectronics using a unique universal gradient interface (UGI) are reported to bridge the gap between soft biomaterials and stiff electronic materials. Leveraging a versatile aerosol‐based multi‐materials printing technique that allows precise spatial control over the local stiffnesses with submicron resolution, the UGI enables strain‐insensitive electronic devices with negligible resistivity changes under a 180% uniaxial stretch ratio. Various stretchable devices are directly printed on the UGI for on‐skin health monitoring with high signal quality and near‐perfect immunity to motion artifacts, including semiconductor‐based photodetectors for sensing blood oxygen saturation levels and metal‐based temperature sensors. The concept in this work will significantly simplify the fabrication and accelerate the development of a broad range of wearable and implantable bioelectronics for real‐time health monitoring and personalized therapeutics.

Song, Kaidong [Department of Aerospace and Mechani↗

Universal Magnetic Phases in Twisted Bilayer MoTe 2

Twisted bilayer MoTe 2 (tMoTe 2 ) has emerged as a robust platform for exploring correlated topological phases, yet the evolution of its magnetism and topology with twist angle remains an open question. Here, we systematically map the magnetic phase diagram of tMoTe 2 by using local optical spectroscopy and scanning nanoSQUID-on-tip magnetometry. We identify spontaneous ferromagnetism at filling factors ν = −1 and −3 across twist angles from 2.1° to 3.7°, revealing a universal, twist-angle-insensitive ferromagnetic phase. At 2.1°, we further observe robust ferromagnetism at ν = −5, absent at larger twist angles. Temperature-dependent measurements reveal a contrasting twist-angle dependence of the Curie temperatures between ν = −1 and −3, indicating a distinct interplay between the exchange interactions and bandwidth for the two Chern bands. Despite broken time-reversal symmetry, no topological gap is detected at ν = −3. Furthermore, our results establish a global framework for understanding and controlling magnetic order in tMoTe 2 .

Insulators↗

A Universal Design of Lithium Anode via Dynamic Stability Strategy for Practical All‐Solid‐State Batteries

Abstract All‐solid‐state Li‐metal battery (ASSLB) chemistry with thin solid‐state electrolyte (SSE) membranes features high energy density and intrinsic safety but suffers from severe dendrite formation and poor interface contact during cycling, which hampers the practical application of rechargeable ASSLB. Here, we propose a universal design of thin Li‐metal anode (LMA) via a dynamic stability strategy to address these issues. The ultra‐thin LMA (20 μm) is in situ constructed with uniform highly Li‐ion conductive solid‐electrolyte interphase and composite‐polymer interphase (CPI) via electroplating process. As a result, the passivation layer with poor Li‐ion conduction on Li anode can be dissolved and small surface resistance can be achieved due to the good compatibility of CPI to SSEs. The cycling of Li symmetric cell with Li 6 PS 5 Cl thin film electrolyte (<100 μm) shows a high critical current density of >2.0 mA cm −2 with excellent cycling stability at 1.0 mA cm −2 . The ASSLBs paring with Ni‐rich LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathode demonstrated the feasibility of engineered LMA design by presenting good rate capability from 0.1 C to 1.0 C at room temperature, as well as long‐term cycling stability (81 % retention after 100 cycles). This work represents a general pathway to make thin dendrite‐free LMA available for high‐energy‐density ASSLBs.

Deng, Tao [Department of Chemical and Biomolecular↗

A Universal Design of Lithium Anode via Dynamic Stability Strategy for Practical All‐Solid‐State Batteries

Abstract All‐solid‐state Li‐metal battery (ASSLB) chemistry with thin solid‐state electrolyte (SSE) membranes features high energy density and intrinsic safety but suffers from severe dendrite formation and poor interface contact during cycling, which hampers the practical application of rechargeable ASSLB. Here, we propose a universal design of thin Li‐metal anode (LMA) via a dynamic stability strategy to address these issues. The ultra‐thin LMA (20 μm) is in situ constructed with uniform highly Li‐ion conductive solid‐electrolyte interphase and composite‐polymer interphase (CPI) via electroplating process. As a result, the passivation layer with poor Li‐ion conduction on Li anode can be dissolved and small surface resistance can be achieved due to the good compatibility of CPI to SSEs. The cycling of Li symmetric cell with Li 6 PS 5 Cl thin film electrolyte (<100 μm) shows a high critical current density of >2.0 mA cm −2 with excellent cycling stability at 1.0 mA cm −2 . The ASSLBs paring with Ni‐rich LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathode demonstrated the feasibility of engineered LMA design by presenting good rate capability from 0.1 C to 1.0 C at room temperature, as well as long‐term cycling stability (81 % retention after 100 cycles). This work represents a general pathway to make thin dendrite‐free LMA available for high‐energy‐density ASSLBs.

Deng, Tao [Department of Chemical and Biomolecular↗

Single-Cell Universal Logic-in-Memory Using 2T-nC FeRAM: An Area and Energy-Efficient Approach for Bulk Bitwise Computation

This work presents a novel approach to configure 2T-nC ferroelectric RAM (FeRAM) for performing single cell logic-in-memory operations, highlighting its advantages in energy-efficient computation over conventional DRAM-based approaches. Unlike conventional 1T-1C dynamic RAM (DRAM), which incurs refresh overhead, 2T-nC FeRAM offers a promising alternative as a non-volatile memory solution with low energy consumption. Our key findings include the potential of quasi-nondestructive readout (QNRO) sensing in 2T-nC FeRAM for logic-in-memory (LiM) applications, demonstrating its inherent capability to perform inverting logic without requiring external modifications, a feature absent in traditional 1T-1C DRAM. We successfully implement the MINORITY function within a single cell of 2T-nC FeRAM, enabling universal NAND and NOR logic, validated through SPICE simulations and experimental data. Additionally, the research investigates the feasibility of 3D integration with 2T-nC FeRAM, showing substantial improvements in storage and computational density, facilitating bulk-bitwise computation. Our evaluation of eight real-world, data-intensive applications reveals that 2T-nC FeRAM achieves 2× higher performance and 2.5× lower energy consumption compared to DRAM. Furthermore, the thermal stability of stacked 2T-nC FeRAM is validated, confirming its reliable operation when integrated on a compute die. These findings emphasize the advantages of 2T-nC FeRAM for LiM, offering superior performance and energy efficiency over conventional DRAM.

36 MATERIALS SCIENCE↗

Weak localization and universal conductance fluctuations in large-area twisted bilayer graphene

We study diffusive magnetotransport in highly 𝑝-doped large-area twisted bilayer graphene in 1∘, 7∘, 9∘, and 20∘ samples. All samples exhibit weak localization, from which we extract the phase coherence length and intervalley scattering lengths, and from that determine that dephasing is caused by electron-electron scattering and intervalley scattering is caused by point defects. We observe signatures of universal conductance fluctuations in the 9∘ sample, which has high mobility and is near the van Hove singularity. Further improvements in sample quality and applications to large-area moiré materials will open new avenues to observe quantum interference effects.

Talkington, Spenser [University of Pennsylvania]↗

Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

AmeriFlux US-IAB Iowa State University NE tower

This is the AmeriFlux version of the carbon flux data for the site US-IAB Iowa State University NE tower. Site Description - This is a 4 ha (200 m x 200 m) crop rotation established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗

AmeriFlux US-IAM Iowa State University Miscanthus

This is the AmeriFlux version of the carbon flux data for the site US-IAM Iowa State University Miscanthus. Site Description - This is a 4 ha (200 m x 200 m) Miscanthus established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗

AmeriFlux US-UiE University of Illinois Sorghum-Soy

This is the AmeriFlux version of the carbon flux data for the site US-UiE University of Illinois Sorghum-Soy. Site Description - Agricultural field planted with photoperiod-sensitive ("energy") sorghum bicolor in a three year rotation with soy (sorghum-sorghum-soy). The first soy rotation was in 2019. This field is typically planted in May and harvested for biomass (sorghum) or grain (soy) in October. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗

AmeriFlux US-UiF University of Illinois Miscanthus 2

This is the AmeriFlux version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2. Site Description - Agricultural field planted with miscanthus x giganteus perennial C4 bioenergy feedstock as a control site for Us-UiB when basalt began to be applied to Us-UiB in 2017. This field is typically harvested in Febraury or March. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗

AmeriFlux US-UiG University of Illinois Maize-Soy 2

This is the AmeriFlux version of the carbon flux data for the site US-UiG University of Illinois Maize-Soy 2. Site Description - Agricultural field planted with maize in a three year rotation with soy (maize-maize-soy) as a control site for Us-UiC when basalt began to be applied to Us-UiC in 2017. The first soy rotation was in 2019. This field is typically planted in May and harvested in October. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗

AmeriFlux US-IAC Iowa State University SE tower

This is the AmeriFlux version of the carbon flux data for the site US-IAC Iowa State University SE tower. Site Description - This is a 4 ha (200 m x 200 m) sorghum-corn-soybean rotation established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗