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DOE OSTI2023

Abstract for CRADA between NETL and the University of Massachusetts Lowell (AGMT-1275)

The demand for printed electronics over conventional electronics is growing each year due to their low costs, low material waste during manufacturing, and compatibility with flexible substrates. The development of inks for printed electronics is a challenge because each printing technology requires different viscosities and curing behaviors to create devices with controlled structures at the micron scale, or smaller. Carbon is a great candidate for fabricating printed electronics devices because it is inexpensive and earth abundant, easily functionalized to impart miscibility with solvent systems, and has electrical properties that can be tuned from insulating to conducting. Despite these advantages, carbons are rarely used for printed electronics because there is a scarcity of inks available for non-contact printing technologies. To address these challenges, the National Energy Technology Laboratory (NETL) will collaborate with the University of Massachusetts Lowell (Participant) through its Printed Electronics Research Collaborative (PERC) to develop engineered carbons and ink formulations optimized specifically for printing radio- and microwave-frequency electronic devices using ink jet, aerosol jet, syringe dispensing, and other additive manufacturing techniques. NETL will process coal, petroleum, and other carbon feedstocks to make engineered carbons with the appropriate composition, microstructure, surface functionalization, and particle morphologies needed to stabilize ink suspensions and impart useful electronic properties to printed devices. The University of Massachusetts Lowell will utilize these engineered carbons to determine which solvent systems and ink additives are needed to achieve the appropriate viscosity, stability, and printability to make useful ink formulations. The University of Massachusetts Lowell will then utilize these inks to manufacture printed resistors and conductors using inkjet, aerosol jet, and syringe dispensing printing methods and will characterize device performance using four-point probe resistivity measurements, contact angle measurements to assess wettability, adhesion evaluation to various substrates, and focused ion beam and scanning electron microscopy for surface and density investigations of printed devices.

36 MATERIALS SCIENCE↗

DOE OSTI2024

NUCLEI (SciDAC-4) effort at The University of Tennessee, Knoxville

This Report summarizes the accomplishments of NUCLEI researchers at The University of Tennessee, Knoxville (UTK) and those supported via subcontracts at the University of North Carolina at Chapel Hill (UNC) and Iowa State University (ISU). The SciDAC-4 NUCLEI collaboration had the goal to advance the computation of atomic nuclei and to make reliable predictions including uncertainty estimates for observables of interest. These goals were achieved by developing improved nuclear interactions and currents that are input to the computations, and by advancing the algorithms and techniques used for computing nuclear observables of interest. The computed results advanced our understanding of how nuclei work; they helped to guide and interpret experiments at existing low-energy nuclear physics facilities, the Facility for Rare Isotope Beams, Jefferson Laboratory, and neutrino experiments. In addition, predictions were made that await confrontation with experimental results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

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↗

DOE OSTI2026

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↗

DOE OSTI2024

COVID-19 trends at the University of Tennessee: predictive insights from raw sewage SARS-CoV-2 detection and evaluation and PMMoV as an indicator for human waste

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring the prevalence of SARS-CoV-2 on university campuses. However, concerns about effectiveness of raw sewage as a COVID-19 early warning system still exist, and it’s not clear how useful normalization by simultaneous comparison of Pepper Mild Mottle Virus (PMMoV) is in addressing variations resulting from fecal discharge dilution. This study aims to contribute insights into these aspects by conducting an academic-year field trial at the student residences on the University of Tennessee, Knoxville campus, raw sewage. This was done to investigate the correlations between SARS-CoV-2 RNA load, both with and without PMMoV normalization, and various parameters, including active COVID-19 cases, self-isolations, and their combination among all student residents. Significant positive correlations between SARS-CoV-2 RNA load a week prior, during the monitoring week, and the subsequent week with active cases. Despite these correlations, normalization by PMMoV does not enhance these associations. These findings suggest the potential utility of SARS-CoV-2 RNA load as an early warning indicator and provide valuable insights into the application and limitations of WBE for COVID-19 surveillance specifically within the context of raw sewage on university campuses.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Methodology to Implement a Microgrid in a University Campus

This paper presents the method we followed to design a microgrid at a university campus based on available resources. Due to introduction of renewable resources to produce energy, a methodology that allows design a microgrid in a university campus is very useful. Hence, we present a series of steps that must be carried out to estimate the resource to be used, the installation, area needed, and the capacity of the systems needed are also described. In addition, the models of the distributed resources that constitutes the microgrid are presented and explained. To validate the proposed methodology, simulations were performed using Opal-RT-LAb. As a test scenario we selected the Mayagüez campus of the University of Puerto Rico where we conducted analysis of the available resource and capacity of the systems is needed to satisfy demand of critical loads, considering a predetermined number of days of austerity. Our study results in determination of dimensions, cost and effectiveness of the microgrid. Simulations results also show that the proposed microgrid satisfy demand with the same reliability, or better, than the traditional electrical network. Additionally, the best options for this purpose are photovoltaic, batteries, and combined heat and power, if the technological advances and availability of resources to the date for Puerto Rico are considered.

36 MATERIALS SCIENCE↗

DOE OSTI2026

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↗

DOE OSTI2025

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↗

DOE OSTI2025

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↗

DOE OSTI2025

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↗

DOE OSTI2021

Constraints on dark matter to dark radiation conversion in the late universe with DES-Y1 and external data

We study a phenomenological class of models where dark matter converts to dark radiation in the low redshift epoch. This class of models, dubbed DMDR, characterizes the evolution of comoving dark-matter density with two extra parameters, and may be able to help alleviate the observed discrepancies between early and late-time probes of the Universe. We investigate how the conversion affects key cosmological observables such as the cosmic microwave background (CMB) temperature and matter power spectra. Combining 3x2pt data from Year 1 of the Dark Energy Survey, Planck-2018 CMB temperature and polarization data, supernovae (SN) Type Ia data from Pantheon, and baryon acoustic oscillation (BAO) data from BOSS DR12, MGS and 6dFGS, we place new constraints on the amount of dark matter that has converted to dark radiation and the rate of this conversion. The fraction of the dark matter that has converted since the beginning of the Universe in units of the current amount of dark matter, ζ, is constrained at 68% confidence level to be <0.32 for DES-Y1 3x2pt data, <0.030 for CMB+SN+BAO data, and <0.037 for the combined dataset. The probability that the DES and CMB+SN+BAO datasets are concordant increases from 4% for the ΛCDM model to 8% (less tension) for DMDR. The tension in S8=σ8Ωm/0.3 between DES-Y1 3x2pt and CMB+SN+BAO is slightly reduced from 2.3σ to 1.9σ. We find no reduction in the Hubble tension when the combined data is compared to distance-ladder measurements in the DMDR model. The maximum-posterior goodness-of-fit statistics of DMDR and ΛCDM model are comparable, indicating no preference for the DMDR cosmology over ΛCDM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

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↗

DOE OSTI2025

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

Deng, Tao [Department of Chemical and Biomolecular↗

DOE OSTI2025

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↗

DOE OSTI2026

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]↗

DOE OSTI2025

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↗

DOE OSTI2022

Universal correlation for falling film evaporation on a horizontal plain tube

Falling film evaporators are widely used in many industrial sectors, such as desalination, refrigeration & air-conditioning, and chemical processes. The heat transfer correlations suitable for wider operating conditions and various refrigerants are useful for designing falling film evaporators. Although many researchers developed the correlation for their own experimental data, there is a limited universal correlation for falling film evaporators. In addition, the dry-out effects were not considered in the available universal correlations. Here, therefore, this study proposes a new correlation for falling film evaporation on a single horizontal plain tube, which includes nucleate boiling, film evaporation, and dry-out effects. The proposed correlation covers a wider range of operating conditions (Heat flux is of 2.5–168kWm -2 , and film Reynolds number is up to 3500), various refrigerants (R134a, R245fa, R1234ze(E), R123, R32, R410A, R290, and R600a), and the large number of experimental data (1101 data in total). The proposed correlation is validated against the available standard correlation with regard to mean absolute deviation (MAD) and R 2 values. The MAD of the new correlation is about 10%, respectively, which is the lowest among other correlations. Similarly, the R 2 showed a value of 0.92, which is the highest compared to the existing correlations. A simplified correlation is also proposed.

42 ENGINEERING↗

DOE OSTI2025

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↗