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DOE OSTI2020

GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} for Fukushima Daiichi Water Treatment Secondary Wastes - 20212

The Japanese government is supporting development work implemented jointly by Veolia subsidiaries Kurion Japan, K.K., Veolia Nuclear Solutions (VNS), Inc., and Veolia Nuclear Solutions Federal Services, LLC for treating radioactive waste generated from Fukushima Daiichi Nuclear Power Station (NPS) water treatment using the GeoMelt{sup TM} In-Container Vitrification (ICV){sup TM} technology. The initial work consisted of glass formulation and engineering-scale testing which was completed in 2018, in the frame of an IRID (International Research Institute for Nuclear Decommissioning) program as part of a project subsidized by Japan's Ministry of Economy, Trade and Industry (METI). The Fukushima Daiichi NPS Mid- and Long-Term Road-map requires investigation of methods to stabilize solid wastes (and to immobilize radioisotopes in the wastes) generated as a result of emergency response and decommissioning activities. Cooling water treatment has resulted in a significant amount of solid and slurry secondary wastes (mostly adsorbents and ion-exchange materials) which will require processing at some point. GeoMelt{sup R} ICV{sup TM} is a joule-heated melter technology which uses a refractory-lined single-use container combining the melter and disposal container. There is no pouring required nor concerns with refractory corrosion which allows the process to accommodate a wide range of waste chemistries and high waste loadings. The testing described here consisted of three engineering-scale melts, each processing between 212 kg and 240 kg of waste simulants, glass formers, and non-radioactive cesium (Cs) and strontium (Sr) tracers. Continuous isokinetic stack sampling of off-gas emissions was performed for each test in order to calculate Cs and Sr retention in the glass wasteform. Single-pass retention of Cs in the final glass wasteform ranged from 91.46 to 99.30%, and single-pass retention of Sr ranged from 99.76 to 100%. Planned particulate recycle will increase these retention levels. Melt 1 processed a mixture of KUR-EH (a zeolite-based ion-exchange material), simulated Advanced Liquid Processing System (ALPS) Carbonate and Iron Slurries, and glass additives. Melt 2 processed a mixture of KUR-EH, KUR-TSG (a titanate-based adsorbent), and glass additives. Melt 3 processed a mixture of KUR-EH, simulated barium sulfate/iron ferrocyanide sludge (AREVA sludge), and glass additives. Waste loadings for these melts ranged from 70 weight percent (wt%) to 82 wt%. Vitrification produces a waste form much denser than the stored water treatment secondary waste wastes, resulting in significant volume reduction. Volume reductions for the three tests ranged from 74 to 79 vol%. Vitrification produces a chemically durable wasteform. Pacific Northwest National Laboratory (PNNL) tested three glass samples from each engineering-scale melt) by the Materials Characterization Center 1 (MCC-1) test, an international standard leach test of the chemical durability of nuclear waste glasses. PNNL also obtained one U.S. reference glass (EA Glass) and two Japan reference glasses P0798) and tested these under the same MCC-1 conditions (90 deg. C, 10 m-1, DIW, and 7, 14, 28-day) as the GeoMelt{sup R} ICV{sup TM} glasses. The GeoMelt{sup R} ICV{sup TM} glasses exhibited lower total normalized releases and 14- to 28-day normalized release rates than the three reference glasses. These results suggest that the GeoMelt{sup R} ICV{sup TM} glasses have durabilities on par with high-level waste glasses under standard test conditions. Post-melt process sampling and analysis indicated no Cs migration into the melter refractory materials and very little deposition of Cs or Sr onto the melter hood or off-gas piping internals. The results of the testing indicated good Cs retention in the glass, high volume reduction and waste loadings, and excellent chemical durability. These factors are important to minimize treatment costs and to protect workers and the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Concurrency Supply Chain Optimization (Final Report)

Brunswick is experiencing unprecedented volume for engines and fully produced boats. Supply Chain (parts) has difficulty accurately forecasting demand needs which presents problems in the manufacturing process. Streamline ordering process enabling the Brunswick Boat Group (BBG) to more efficiently forecast part demand for the Mercury Engine Group by setting up an AI/ML model. Initial focus will be 15 SKUs with inaccurate demand forecasting based on current manual processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Facile alignment estimation in carbon nanotube films using image processing

Whether a macroscopic assembly of carbon nanotubes can exhibit the one-dimensional properties expected from individual nanotubes critically depends on how well the nanotubes are aligned inside the assembly. Therefore, a simple and accurate method for assessing the degree of alignment is desired for the rapid characterization of carbon nanotube films and fibers. Here, we present an end-to-end solution for determining the global and local spatial orientation of carbon nanotubes in films within a short amount of time using a fast, precise, and economical approach based on an image processing method applied to scanning electron microscopy images. Further, we first use Laplacian edge enhancement filtering for improving the appearance of edge regions, which is followed by image partitioning into multiple blocks to capture the nanoscale orientation characteristics and total variation-based image decomposition of these image blocks. We then perform a 2D-fast Fourier transform on the image decomposed textural components of these edge-enhanced image blocks to determine the orientation distribution, which is utilized to estimate the 2D nematic order parameter. To show the effectiveness of our method, we corroborated our results against results obtained with other state-of-the-art image processing and experimental techniques.

2D-FFT↗

DOE OSTI2025

Flat nonlinear optics with intersubband polaritonic metasurfaces

Nonlinear intersubband polaritonic metasurfaces produce some of the strongest second- and third-order nonlinear optical responses reported for condensed matter systems at infrared frequencies. These metasurfaces are fabricated as two-dimensional arrays of nanoresonators from multi-quantum-well semiconductor heterostructures, designed to produce strong nonlinear responses associated with intersubband transitions. By optimally coupling the optical modes of the nanoresonators to vertically polarized intersubband transitions in semiconductor heterostructures, one can boost the nonlinear response associated with intersubband transitions, make intersubband transitions interact with free-space radiation at normal incidence, and hence produce optically thin flat nonlinear optical elements compatible with free-space optical setups. As a result of the strong nonlinear response in these systems, significant nonlinear conversion efficiencies (>0.1 %) can be attained in deeply subwavelength optical films using modest pumping intensities of only 10–100 kW/cm 2 . Subwavelength metasurface thickness relaxes phase-matching constraints limiting the operation of bulk nonlinear crystals. Furthermore, the amplitude and phase of the nonlinear optical response in intersubband polaritonic metasurfaces can be tailored for a specific pump wavelength and a nonlinear process of interest through the co-optimization of quantum engineering of electron states in semiconductor heterostructures and photonic engineering of the metasurface nanoresonators design. Additionally, an applied voltage can dynamically control the amplitude and phase of the nonlinear optical response at a nanoresonator level. Here, we review the current state of the art in this rapidly expanding field, focusing on nonlinear processes supporting second-harmonic generation, saturable absorption, and optical power limiting.

flat optics↗

DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

The objective of this project is to improve the prediction of engine knock by developing a new combustion modeling framework. Engine knock is a limiting factor to constrain the increase of fuel efficiency for spark ignition (SI) engines in most passenger cars. Efforts to increase fuel efficiency, increasing the compression ratio or downsizing, lead to the increase in the tendency of the knock occurrence. The knock is an undesired ignition of the end-gas, unburned fuel/air mixture ahead of the spark-ignited premixed flame, resulting in rapid in-cylinder pressure rises and engine damages. The combustion modeling framework developed in this project can consider turbulence-chemistry interactions during end-gas ignition, while using a reasonably detailed chemical mechanism developed for ignition and combustion reactions under engine relevant conditions, and the subtle characteristics of spark-ignited flame propagation. It is developed in the context of large eddy simulation (LES), which can capture stochastic in-cylinder processes. The developed model is incorporated into a commercial software for engine simulation, CONVERGE CFD, as a user defined function, and validated. Engine knock and knock-free experiments as well as direct numerical simulation (DNS) of end-gas ignition in homogeneous turbulence are performed to help model development and provide data sets for model validation. With further validation, the developed model is expected to advance the predictive capability for engine knock simulations and thus contribute to improving the fuel efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Effect of the grain arrangements on the thermal stability of polycrystalline nickel-rich lithium-based battery cathodes

One of the most challenging aspects of developing high-energy lithium-based batteries is the structural and (electro)chemical stability of Ni-rich active cathode materials at thermally-abused and prolonged cell cycling conditions. Here, we report in situ physicochemical characterizations to improve the fundamental understanding of the degradation mechanism of charged polycrystalline Ni-rich cathodes at elevated temperatures (e.g., ≥ 40 °C). Using multiple microscopy, scattering, thermal, and electrochemical probes, we decouple the major contributors for the thermal instability from intertwined factors. Our research work demonstrates that the grain microstructures play an essential role in the thermal stability of polycrystalline lithium-based positive battery electrodes. We also show that the oxygen release, a crucial process during battery thermal runaway, can be regulated by engineering grain arrangements. Furthermore, the grain arrangements can also modulate the macroscopic crystallographic transformation pattern and oxygen diffusion length in layered oxide cathode materials.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Experimental Investigation of Gaseous Mixtures of Ethane, Methane, and Carbon Dioxide as an Alternative to Conventional Fuel in Spark Ignition Engines

This study investigates the viability and performance of certain synthetic fuels in spark ignition internal combustion engine based stationary power generation wherein the fuel comprises a mixture of methane and ethane in high dilutions of carbon dioxide (CO 2 ). The fuel of concern is a byproduct of a novel method for producing ethylene from ethane. The byproduct gas mixture has a concentration of approximately 41% CO 2 , 40% ethane, and 5% methane by weight along with other minor compounds. Varying mixtures of ethane and methane combined with between 42% and 46% by weight CO 2 were used to evaluate the viability and efficiency of this fuel to operate in existing internal combustion engines as a means of reducing emissions and increasing industrial process efficiency. A 13 hp gasoline generator was repurposed as a test stand by incorporating a modified fuel induction system and instrumentation for data collection. A gas metering and mixing system was installed to precisely control the mass flow of gases induced into the engine. Various instrumentations were installed to monitor in-cylinder pressure, temperature at various locations, emissions, and fuel and airflow rates. Varying fuel mixtures and loads were tested and compared to gasoline. It was found that under a high load, the mixed gas was able to generate comparable thermal efficiency and power to gasoline. But under no load or a part load condition the indicated thermal efficiency was found to be about 21% lower than that of gasoline. Further, the mixed gas also resulted in up to 50% reduction in CO and NOx emissions when compared to gasoline.

42 ENGINEERING↗

DOE OSTI2024

A miniaturized feedstocks-to-fuels pipeline for screening the efficiency of deconstruction and microbial conversion of lignocellulosic biomass

Sustainably grown biomass is a promising alternative to produce fuels and chemicals and reduce the dependency on fossil energy sources. However, the efficient conversion of lignocellulosic biomass into biofuels and bioproducts often requires extensive testing of components and reaction conditions used in the pretreatment, saccharification, and bioconversion steps. This restriction can result in a significant and unwieldy number of combinations of biomass types, solvents, microbial strains, and operational parameters that need to be characterized, turning these efforts into a daunting and time-consuming task. Here we developed a high-throughput feedstocks-to-fuels screening platform to address these challenges. The result is a miniaturized semi-automated platform that leverages the capabilities of a solid handling robot, a liquid handling robot, analytical instruments, and a centralized data repository, adapted to operate as an ionic-liquid-based biomass conversion pipeline. The pipeline was tested by using sorghum as feedstock, the biocompatible ionic liquid cholinium phosphate as pretreatment solvent, a “one-pot” process configuration that does not require ionic liquid removal after pretreatment, and an engineered strain of the yeast Rhodosporidium toruloides that produces the jet-fuel precursor bisabolene as a conversion microbe. By the simultaneous processing of 48 samples, we show that this configuration and reaction conditions result in sugar yields (~70%) and bisabolene titers (~1500 mg/L) that are comparable to the efficiencies observed at larger scales but require only a fraction of the time. We expect that this Feedstocks-to-Fuels pipeline will become an effective tool to screen thousands of bioenergy crop and feedstock samples and assist process optimization efforts and the development of predictive deconstruction approaches.

09 BIOMASS FUELS↗

DOE OSTI2022

Rheo-Structural Spectroscopy: Fingerprinting the In Situ Response of Fluids to Arbitrary Flow Fields

The objectives of this project were to develop new sample environments, measurement methodologies and associated modeling tools for characterizing the structural response to arbitrarily complex processing flows using small angle scattering, and to apply these new tools for understanding the fundamental physics governing the structuring of anisotropic particulate and polymeric materials under flow histories and conditions relevant to industrial processing flows. The research resulted in the development and implementation of a new sample environment, the fluidic four roll mill (FFoRM), for in situ small angle neutron and X-ray scattering (SANS/SAXS) measurements. These measurements are capable of generating large data sets that “fingerprint” how a complex fluid responds to a wide range of flow histories involving time variations in deformation type and rate. New modeling tools were developed to extract detailed microstructural information from such data sets, including orientation distribution functions and interparticle correlation functions, as well as reduced-order parametric descriptors of these high-dimensional functions that can be used to readily map, visualize and interpret a fluid’s structural response to its flow history. These new tools were applied to a range of model materials involving elongated particle suspensions in order to provide new insights into the physics of how flow couples with orientational and structural order in complex flows, particularly under non-dilute conditions for which no accurate theories currently exist. Using these investigations, we elucidated a number of new insights into the fundamental phenomena driving such process-structure-property relationships. These findings provide guidance for the further development of rheological models, and ultimately can inform the rational and model-based design of flow processes to achieve optimized orientational ordering that is key to the properties and function of a wide range of energy-relevant materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Effects of process intensification on homogeneity of an IgG1:κ monoclonal antibody during perfusion culture

The pharmaceutical industry employs various strategies to improve cell productivity. These strategies include process intensification, culture media improvement, clonal selection, media supplementation and genetic engineering of cells. However, improved cell productivity has inherent risk of impacting product quality attributes (PQA). PQAs may affect the products’ efficacy via stability, bioavailability, or in vivo bioactivity. Variations in manufacturing process may introduce heterogeneity in the products by altering the type and extent of N-glycosylation, which is a PQA of therapeutic proteins. We investigated the effect of different cell densities representing increasing process intensification in a perfusion cell culture on the production of an IgG1-κ monoclonal antibody from a CHO-K1 cell line. This antibody is glycosylated both on light chain and heavy chain. Our results showed that the contents of glycosylation of IgG1-κ mAb increased in G0F and fucosylated type glycans as a group, whereas sialylated type glycans decreased, for the mAb whole protein. Overall, significant differences were observed in amounts of G0F, G1F, G0, G2FS1, and G2FS2 type glycans across all process intensification levels. G2FS2 and G2 type N-glycans were predominantly quantifiable from light chain rather than heavy chain. It may be concluded that there is a potential impact to product quality attributes of therapeutic proteins during process intensification via perfusion cell culture that needs to be assessed. Since during perfusion cell culture the product is collected throughout the duration of the process, lot allocation needs careful attention to process parameters, as PQAs are affected by the critical process parameters (CPPs).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗

DOE OSTI2024

Alternating conduction and convection drying of paper – an experimental analysis with a continuous data acquisition approach

In conventional multi-cylinder drying of paper and board, both conductive drying from steam-heated dryer cylinders and convective drying by flowing air over the paper surface in the pockets are used. Conductive drying from steam-heated drying cylinders is a critical component in providing the necessary thermal energy to paper and board as they dry. Steam temperature and internal and external resistances at the contacting surface are critical process parameters influencing the conductive drying process. An experimental setup was developed to study the alternating conductive and convective drying of paper and board. Paper sheet moisture, temperature, and temperature distribution within the heated platen and the instantaneous heat flux as the sheet was being dried were measured. The instantaneous heat flux, contact heat transfer coefficient, and drying rates were determined as drying proceeds. Experimental results, as well as comparisons to literature and commercial data, are presented. The conductive heat transfer coefficients determined were compared to traditional correlations normally used in the modeling of paper drying. Similarly, the convective heat and mass transfer coefficients are also determined and compared to literature data. In addition to the evaluation of alternating conductive and convective drying characteristics of paper and board, the potential inclusion of auxiliary energy components will also be included. Experimental results from the conduction and convection drying system are presented. Furthermore, this data will be useful in process development, intensification of manufacturing processes, and modeling and simulation of paper drying processes.

42 ENGINEERING↗

DOE OSTI2022

Sustainable conversion of biomass to rationally designed lithium-ion battery graphite

The carbon net negative conversion of bio-char, the low value byproduct of pyrolysis bio-oil production from biomass, to high value, very high purity, highly crystalline flake graphite agglomerates with rationally designed shape and size tailored for lithium-ion battery energy storage material is reported. The process is highly efficient, 0.41 g/Wh; the energy content of its co-product of the process, bio-oil, exceeds that needed to power the process. It is shown that the shape of the starting material is retained during the transformation, allowing the ultimate morphology of the graphite agglomerates to be engineered from relatively malleable biomass. In contrast to commercial graphite production, the process can be performed at small scale with low equipment costs, enabling individual research laboratories to produce Li-ion grade graphite with customizable shape, size and porosity for Si/graphite composite and other graphite involved anodes. The mechanism of the graphitization of bio-char, a “non-graphitizable” carbon, is explored, suggesting the molten metal catalyst is absorbed into the pore structure, transported through and transforming the largely immobile biochar. Finally, the transformation of biomass to rationally designed graphite morphologies with Li-ion anode performance that closely mimic commercial shaped graphite is demonstrated.

09 BIOMASS FUELS↗

DOE OSTI2022

Pseudo-halide anion engineering for efficient quasi-2D Ruddlesden-Popper tin perovskite solar cells

Quasi-two-dimensional (2D) organic-inorganic hybrid tin perovskites have emerged as promising alternatives to lead-based perovskites in thin-film photovoltaics because of their reduced toxicity and improved stability. However, the undesired small n-value 2D phases and disordered crystal orientation enormously restrict the efficiency of quasi-2D tin perovskite solar cells (PSCs) due to uncontrollable nucleation and crystal growth processes. Here, we propose a mixed pseudo-halide anion engineering approach by using acetate (Ac - ) and tetrafluoroborate (BF 4 - ) anions to make quasi-2D Ruddlesden-Popper perovskites with a target formula of PEA 2 FA 4 Sn 5 I 16 . We find that the mixed Ac - and BF 4 - anions can not only promote homogeneously distributed PEA + cations in the precursor by effectively breaking the PEA + ···PEA + stacking but also retard the crystallization process by coordinating with unbonded SnI 2 , thereby, significantly reducing small n-value 2D phases, improving the crystal orientation, and suppressing the Sn 2+ oxidation. The resulting PSC exhibits up to 9% power conversion efficiency and 400 h stability.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

DOE OSTI2026

Non-classical ion-indiffusion processes in quasi-one-dimensional ionic conductor KTiOPO4

Developments in coercive field engineering and waveguide writing via ion-exchange in the ferroelectric ionic-conductor KTiOPO4 (KTP) have led to breakthroughs within the field of nonlinear optics and quantum photonics. However, the microscopic diffusion dynamics of ion-exchange in KTP are poorly understood and show signs of non-classical diffusion dynamics. The precise control of ion-exchange gradients is critical for developing KTP into a mature, integrated nonlinear optical material but requires a level of control that, in turn, demands a deeper understanding of the ion-exchange process. We employ direct ToF-SIMS mapping to untangle the complex diffusion dynamics of the commonly used ion-exchange dopant ions: Rb, Ba, and K. We map periodic diffusion gradients of two exchanges, one dominated by Rb-ions and the other by Ba-ions. For the first time, we show the interdependent nature of the Ba- and Rb ion in the ion-exchange diffusion gradient. The low incorporation of the Ba ion is mapped and quantified, and dopant–crystal interactions are identified. This work highlights the complex diffusion dynamics of dopants in the KTP structure and lays the foundation for deterministic control of diffusion gradients for the next generation of integrated nonlinear and quantum photonic devices.

Barrett, Laura [ORNL]↗