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197 records · Page 11

Design and Preparation of Nematic Colloidal Particles

Colloidal systems are abundant in technology, in biomedical settings, and in our daily life. The so-called “colloidal atoms” paradigm exploits interparticle interactions to self-assemble colloidal analogs of atomic and molecular crystals, liquid crystal glasses, and other types of condensed matter from nanometer- or micrometer-sized colloidal building blocks. Nematic colloids, which comprise colloidal particles dispersed within an anisotropic nematic fluid host medium, provide a particularly rich variety of physical behaviors at the mesoscale, not only matching but even exceeding the diversity of structural and phase behavior in conventional atomic and molecular systems. This feature article, using primarily examples of works from our own group, highlights recent developments in the design, fabrication, and self-assembly of nematic colloidal particles, including the capabilities of preprogramming their behavior by controlling the particle’s surface boundary conditions for liquid crystal molecules at the colloidal surfaces as well as by defining the shape and topology of the colloidal particles. Here recent progress in defining particle-induced defects, elastic multipoles, self-assembly, and dynamics is discussed along with open issues and challenges within this research field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Simplification of the purification of heat stable recombinant low molecular weight proteins and peptides from GST-fusion products

The synthesis and purification of peptides of importance in the fields of research and medicine continue to be a challenging task. Chemical synthesis of oligopeptides, especially those greater than 25 amino acids, is cost prohibitive. On the other hand, several bottlenecks exist in the production of recombinant short peptides in heterologous expression hosts such as Escherichia coli (E. coli). In this paper, a rapid, cost-effective, and reliable method for the production and singlestep-purification of peptides and small proteins was developed. Five peptides and small proteins were overexpressed in E. coli as GST-fusion products in high yields. The recombinant peptides or proteins were successfully purified after enzymatic cleavage with selective heat-induced precipitation of the GST-affinity tag. Qualitative and quantitative analysis using SDS-PAGE and mass spectrometric methods suggest that the recombinant peptides/ proteins were purified to >95% homogeneity. Results of biophysical experiments, including multi-dimensional NMR spectroscopy, show that the purified proteins/ peptides retain their native conformation. Isothermal titration calorimetry studies indicate no significant change in the binding affinity of the heattreated purified product to their interacting partner(s) compared to the recombinant peptides purified by conventional chromatographic procedures without subjecting to heat treatment. In our opinion, the results reported render the purification of recombinant proteins/ peptides of biomedical relevance using our proposed method easy and reliable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Can portable glucose and lactate meters be a useful tool in quantifying stress of juvenile Chinook salmon?

Blood plasma analyses can provide researchers, aquaculture facilities and fisheries managers with valuable insights into the physiological state and welfare of fish. For example, glucose and lactate are part of the secondary stress response system, and elevated concentrations are indicators of stress. However, analysing blood plasma in the field can be logistically difficult and typically involves sample storage and transport to quantify concentrations in a laboratory setting. Portable glucose and lactate meters offer an alternative to laboratory assays and have shown to be relatively accurate in fish, but these tools have only been validated for a few fish species. The objective of this study was to investigate if portable meters could be reliably used in Chinook salmon (Oncorhynchus tshawytscha). As part of a larger stress response study, juvenile Chinook salmon (157 ± 17 mm fork length [mean ± standard deviation; SD]) were exposed to stress-inducing treatments and sampled for blood. Laboratory reference glucose concentrations (milligrams per deciliter; mg/dl; n = 70) were positively correlated with the Accu-Check Aviva meter (Roche Diagnostics, Indianapolis, IN) measurements (R 2 = 0.79), although glucose values were 1.21 ± 0.21 (mean ± SD) times higher in the laboratory than with the portable meter. Lactate concentrations (milliMolar; mM; n = 52) of the laboratory reference were also positively correlated (R 2 = 0.76) with the Lactate Plus meter (Nova Biomedical, Waltham, MA) and were 2.55 ± 0.50 times higher than portable meter. Our results indicate both meters could be used to measure relative glucose and lactate concentrations in Chinook salmon and provide fisheries professionals with a valuable tool, particularly in remote field settings.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Neuromorphic ionic computing in droplet interface synapses

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

Li, Zhongwu [Lawrence Livermore National Laborator↗

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32 x 32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

47 OTHER INSTRUMENTATION↗

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. The report below summarizes the work done at UC Davis, which is complemented by work done at BYU (Woodfield) and Virginia Tech (Ross).

36 MATERIALS SCIENCE↗

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. This research was a collaboration between UC Davis (A. Navrotsky) BYU (B. Woodfield) and Virginia Tech (N. Ross).

36 MATERIALS SCIENCE↗

A distinct subpopulation of membrane vesicles in Pseudomonas putida is enriched in enzymes for lignin catabolism

Bacterial membrane vesicles (MVs) mediate diverse microbial processes and are emerging as powerful biomedical tools, but MV population heterogeneity remains an open question. Here, we separate, enumerate, and characterize two MV populations from the soil bacterium Pseudomonas putida during growth with or without lignin-derived carbon, a major carbon source from plant cells in the rhizosphere. Small MVs (MV-S, diameter ~100 nm) were produced from all cultures, whereas large MVs (MV-L, diameter ~300 nm) were observed during the late stationary phase of lignin cultivations. MV-S contained selectively packaged proteins with diverse physiological functions, whereas the MV-L proteome was smaller and largely enriched in outer membrane proteins. Interestingly, enzymes known to mediate the catabolism of lignin-derived aromatic compounds were enriched in MV-S. Overall, this study highlights the need for careful consideration of MV populations in microbial systems.

59 BASIC BIOLOGICAL SCIENCES↗

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ontologizing health systems data at scale: making translational discovery a reality

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Supporting Information for manuscript: “A latitudinal gradient in S/G lignin monomer ratio driven by laccase in natural poplar variants”

Lignin composition plays a crucial role in plant structural integrity and environmental adaptation. However, the genetic and molecular mechanisms underlying natural variation in lignin composition remain poorly understood. This study investigates the syringyl-to-guaiacyl (S/G) lignin monomer ratio across a natural population of Populus trichocarpa spanning a latitudinal gradient along the Northwest coast of North America. By integrating biochemical, genomic, and geographic analysis, we identify key gene variants associated with S/G ratio differences. These datasets provide valuable insights into the evolutionary and functional genomics of lignin composition and serve as a resource for developing poplar variants optimized for forestry and bioenergy applications.

Poplar, lignin composition, laccases, latitude, ad↗

Revisions of ORNL 188 W Process Based on Nonradiological Experiments

Tungsten-188 is in widespread use in the 188 W(t 1/2 = 69 d)/ 188 Re(t 1/2 =16.9 h) biomedical generator. Oak Ridge National Laboratory (ORNL) has been providing this product to the world since 1999. At ORNL, 188 W is produced via irradiation in ORNL’s High Flux Isotope Reactor (HFIR). Enriched 186 W targets in the form of sintered metallic pellets or rings achieve a compact loading in the irradiation vessel, providing a high yield per unit target. The enrichment of the target is >90% 186 W and this isotope undergoes double neutron capture to produce the desired 188W product. While 188 W is produced by neutron bombardment, 191 Os(t 1/2 = 15.4 d) is simultaneously produced as a byproduct requiring separation from 188 W by post irradiation treatment. In the current processing pathway, the irradiated W metal pellets or rings are first converted into an oxide form of WO 3 by heating the irradiated W metal target at 750°C in a quartz reaction vessel inside a vertical furnace under a constant flow of air. During heating, W metal reacts with oxygen in the air to produce WO 3 , which is soluble in 6 M NaOH for later purification process. This oxidation process also converts 188 Os (the decay daughter of 188 W) and 191 Os (the irradiation produced byproduct) into OsO 4 , a highly volatile and toxic gas. The gaseous effluents driven from the quartz reaction vessel are passed through a scrubbing array to remove OsO 4 before the air is discharged from the process. This heterogeneous oxidation method simultaneously achieves two goals: 1). converting metal target to a soluble oxide form and 2). separating volatile OsO 4 away from the solid WO 3 product, although harmful 191 OsO 4 is unfavorable but being taken care of by the down road scrubbing array. In the past twenty years the existing OsO 4 scrubbing array served well in preventing OsO 4 from being released into the environment, until July of 2020 when a minor amount of 191 Os was found to have been released into the environment which resulted in a standby of building 4501 from July 2020 to February 2021.Since October 20 of 2020 a team of researchers from groups of RSTD and NEFD were organized to work for the following tasks: (1) Fully understand the root causes of the July incident of 191 Os release and create a redesigned 191 Os scrubbing array to eliminate the possibility of 191 Os release in future 188 W processes; (2) In Phase-1 tests, select a correct air (O 2 ) flow rate in 188 W process, that provides sufficient oxygen for the oxidation of tungsten metal, while still allowing sufficient resonance time for 191 Os removal by the scrubbers; (3) In Phase-2 tests, confirm the efficiency of the redesigned scrubbing array to absorb excessive amount of non-rad OsO 4 (generated from Os metal powder) at the selected air flow; (4) In Phase-3 tests, simulate the hot cell 188 W process by heating pressed non-rad W-Os pellets in a quartz vessel of new design and the new array under operation parameters selected in Phase-1 and -2; (5) Complete a new operation procedure for 188 W process in hot cell and a TM report as a summary of the Os Mitigation Project. This TM report summarizes the investigation on root causes from technical aspects in July 191 Os release and the correspondent improvement towards the redesigned 191 Os scrubbing system. The report presents the efforts made on selection of optimal operational parameter with the new scrubbing array and the quartz vessel of new design, based on experiment data obtained in Phase-1, -2 and -3 tests. Further renovations for 188 W process and additional improvement of W target treatment will also be discussed.

07 ISOTOPE AND RADIATION SOURCES↗

Protein Adhesion on Semi-Fluorinated Polystyrene Surfaces in Static and Dynamic Measurements

Reducing protein adhesion is a critical strategy in fouling-resistant material innovation, with broad applications spanning biomedical and healthcare devices, biosensors, industrial and environmental systems, and other important technological domains. Here, in this study, we elucidated protein adhesion behavior on polystyrene-based thin films by neutron reflectometry (NR) and quartz crystal microbalance with dissipation (QCM-D), using both lysozyme and bovine serum albumin (BSA) as model proteins. To this end, semifluorinated polystyrene thin films with gradient wettability and surface energy were fabricated through dry processing using plasma oxidation and gas-phase deposition. Although it is believed that a fully fluorinated alkyl chain offers extremely low surface energy, thus rejecting foulants, and has been used in many fouling-resistant surface designs, enhanced protein–surface interactions were observed consistently in NR and QCM-D results, due to the combined effects of surface morphology and chemistry. On the contrary, depositing shorter fluorinated silane onto a hydrophilic PS surface contributed to a more homogeneous nanoscale fluorine coating, resulting in less initial protein adsorption and improved surface recovery. Comparative analysis of proteins with different sizes on the nanopatterned semifluorinated surface revealed the influence of molecular characteristics on surface interactions. Lysozyme, being smaller and more compact, showed faster adsorption kinetics and higher surface coverage but largely reversible binding, whereas BSA, with its larger and more flexible structure, formed broader and more stable interfacial layers. This study fills the gap in understanding protein adhesion within the range of hydrophobicity (water contact angle ∼90°), as current strategies often associate with extreme hydrophilic and superhydrophobic surfaces due to hydration or low-surface-energy rejection mechanisms, respectively. It also provides in-depth insights into current combinatorial fouling-resistant surface design.

Yuan, Yue [Oak Ridge National Laboratory (ORNL), O↗

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗