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DOE OSTI2020

Emerging technologies and radical collaboration to advance predictive understanding of watershed hydrobiogeochemistry

Increasing population and resource-intensive lifestyles are driving enhanced demands for clean water, food, and energy. In parallel, land-use change, climate change, and perturbations—including drought, floods, fires, and early snowmelt—are significantly reshaping interactions within watersheds throughout the world. While watersheds are the Earth's key functional unit for assessing and managing water resources, hydrological processes in watersheds also mediate biogeochemical interactions that support terrestrial life on Earth (Kaushal, Gold, Bernal, & Tank, 2018; National Research Council, 2012). Although society is dependent upon clean water availability, tractable prediction of watershed hydrobiogeochemical behavior, including watershed response to perturbations, remains a challenge. Central to the challenge are complex, multiscale interactions between plants, microorganisms, organic matter, minerals, dissolved constituents, and migrating fluids, which occur within and across bedrock-to-canopy compartments and along extensive lateral gradients of a watershed. Several recent community reports have synthesized formidable challenges associated with watershed science and technology (AGU, 2018; Blöschl et al., 2019). Here, we discuss emerging technologies and collaboration modes that are critical for developing generalizable insights about and predictive understanding of complex watershed hydrobiogeochemical behavior, which are important for underpinning optimized natural resource management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Genomic adaptations of the green alga Dunaliella salina to life under high salinity

Life in high salinity environments poses challenges to cells in a variety of ways: maintenance of ion homeostasis and nutrient acquisition, often while concomitantly enduring saturating irradiances. Dunaliella salina has an exceptional ability to thrive even in saturated brine solutions. This ability has made it a model organism for studying responses to abiotic stress factors. Here we describe the occurrence of unique gene families, expansion of gene families, or gene losses that might be linked to osmoadaptive strategies. We discovered multiple unique genes coding for several of the homologous superfamily of the Ser-Thr-rich glycosyl-phosphatidyl-inositol-anchored membrane family and of the glycolipid 2-alpha-mannosyltransferase family, suggesting that such components on the cell surface are essential to life in high salt. Gene expansion was found in families that participate in sensing of abiotic stress and signal transduction in plants. One example is the patched family of the Sonic Hedgehog receptor proteins, supporting a previous hypothesis that plasma membrane sterols are important for sensing changes in salinities in D. salina. We also investigated genome-based capabilities regarding glycerol metabolism and present an extensive map for core carbon metabolism. We postulate that a second broader glycerol cycle exists that also connects to photorespiration, thus extending the previously described glycerol cycle. Further genome-based analysis of isoprenoid and carotenoid metabolism revealed duplications of genes for 1-deoxy-D-xylulose-5-phosphate synthase (DXS) and phytoene synthase (PSY), with the second gene copy of each enzyme being clustered together. Moreover, we identified two genes predicted to code for a prokaryotic-type phytoene desaturase (CRTI), indicating that D. salina may have eukaryotic and prokaryotic elements comprising its carotenoid biosynthesis pathways. In brief, our genomic data provide the basis for further gene discoveries regarding sensing abiotic stress, the metabolism of this halophilic alga, and its potential in biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Nuclear Structure and Decay Data for A=167 Isobars

Experimental nuclear spectroscopic data are compiled and evaluated for 17 known nuclides of mass 167 (Sm, Eu, Gd, Tb, Dy, Ho, Er Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt), 23 years after the previous full evaluation by 2000Ba65. Detailed information is presented for each reaction and decay experiment. Combining all the available data, recommended values are provided for energies, spins and parities, and half-lives of levels, with energies, branching ratios and multipolarities of γ radiations, and characteristics of β and α radiations in radioactive decays. Here, the α decays of A=171 nuclei to A=167 daughters are included in this work, while for α decays of A=167 nuclei to A=163 daughters, consult Nuclear Data Sheets (2010Re03) or the ENSDF database for A=163. 167 Er, 167 Tm, 167 Yb, 167 Lu and 167 Ta are among the most extensively studied nuclides via decay and high-spin gamma-ray spectroscopy measurements, followed by 167 Ho, 167 Hf, 167 W, and 167 Os. Information for excited states in 167 Dy, 167 Re, and 167 Ir are limited; no excited states have yet been identified in 167 Sm, 167 Eu, 167 Gd, 167 Tb and 167 Pt, with the ground-state half-life of 167 Sm remaining unknown. This work supersedes the earlier evaluation of A=167 nuclei by 2000Ba65.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Scalable and Energy-Efficient Methods for Interactive Exploration of Scientific Data

The main scientific contributions of this project are the following novel concepts for multidimensional arrays: shape-based similarity join (SIGMOD 2016), incremental view maintenance (SIGMOD 2017), user-defined stencil functions (HPDC 2017), and distributed caching for in-situ processing (SSDBM 2018). Building on our collaboration with the astrophysics group at LBNL, we applied these techniques to the data generated in the Palomar Transient Factory (PTF) astronomical survey. They played a pivotal role in the first-ever observation of a neutron star merger, which produces gravitational waves and turns out to be the origin of heavy elements, including gold. This has lead to a Science magazine article that has received extensive media coverage on ACM TechNews, Slashdot, FiveThirtyEight, and Quanta Magazine, among others. Additionally, two other articles detailing related aspects of the same discovery have been published in the Astrophysical Journal Letters journal. These publications have more than 3,000 citations according to Google Scholar (as of February 2022). This cross-disciplinary collaboration provided very good opportunities to apply database techniques to real-life scientific problems. The fact that they facilitated major discoveries in astrophysics proves the importance of our research. In addition to the work on multidimensional array databases, this project has also developed stochastic gradient descent (SGD) optimization algorithms for training large scale machine learning models, methods for querying in-situ data, and a database query optimizer based on sketch synopses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Incremental approach for the life-cycle greenhouse gas analysis of carbon capture and utilization

Electro-fuels (e-fuels) are examples of carbon capture and utilization (CCU) hydrocarbon products that are derived from captured carbon dioxide (CO 2 ), while using renewable electricity as the energy feedstock. The environmental impacts of CCU products (e.g., e-fuel) are systematically quantified through life-cycle analysis (LCA). Previous studies evaluating LCA of e-fuels proposed frameworks with an expanded system boundary approach that included the entire supply chain of the production process generating the CO 2 for CCU, in addition to the supply chain of the CCU product. This expanded system boundary approach evaluates two system boundaries, and uses deduction methods to calculate the carbon intensity (CI) of the CCU product (e-fuel). This paper proposes a simpler system boundary using an incremental approach that can calculate identical CI of the CCU product (e-fuel), while avoiding the extensive calculations in the expanded system boundary framework. The proposed incremental approach allocates the burdens of the CO 2 capturing process to the CO 2 feedstock supplying the CCU production process (e.g., e-fuel production). The CI of the captured CO 2 supplied to CCU process is determined by the energy and material requirements for the CO 2 capturing process and transportation to the CCU plant. Thus, the CI of CO 2 supplied to CCU process can be directly linked to the CI of e-fuel without the need to conduct LCA of the preceding process that generates the CO 2 for CCU.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Xanthohumol Microbiome and Signature in Healthy Adults (the XMaS Trial): Safety and Tolerability Results of a Phase I Triple-Masked, Placebo-Controlled Clinical Trial

Scope Xanthohumol, a prenylflavonoid from hops, has been extensively studied preclinically but has undergone limited research in human subjects. A triple-masked, placebo-controlled phase I clinical trial was conducted to examine the safety and tolerability of xanthohumol. Methods and results Thirty healthy volunteers were randomized to 24?mg/day xanthohumol (99.8% pure) or placebo for eight weeks. Comprehensive metabolic panels, complete blood counts, body weight, vital signs, and health-related quality of life questionnaires were assessed every two weeks. Participants were interviewed for adverse events (AEs) throughout the trial. Thirteen of 14 (93%) and 14 of 16 (88%) participants completed the trial in Group A and B respectively. There were no withdrawals due to AEs. There were no clinically relevant, between-group differences in laboratory biomarkers, body weight, vital signs, or health-related quality of life. There were no severe or FDA-defined serious AEs, but non-serious AEs were documented in both Group A (n=42) and Group B (n=58). Conclusion Over an eight-week period, 24 mg daily xanthohumol was safe and well-tolerated by healthy adults.

Langley, Blake↗

DOE OSTI2024

Battery Energy Storage Systems: A Review of Energy Management Systems and Health Metrics

With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.

Nazaralizadeh, Solmaz (ORCID:0009000737004039)↗

DOE OSTI2021

edxia: Microstructure characterisation from quantified SEM-EDS hypermaps

The characterisation of cement paste microstructure is an important step towards understanding durability mechanisms in cementitious materials. Scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) is a widely used technique to analyse the microstructure at the micron-scale. However, it is challenging, notably because the characteristic size of many phases is found on a scale smaller than the EDS interaction volume. This work presents a new image analysis framework to identify phases and quantify the microstructure of cementitious materials from SEM-EDS hypermaps. By leveraging domain knowledge, representative points are attributed to phases and mixtures of phases based on ratio plots. Then, quantitative analysis of the microstructure can be carried out (chemical composition, particle size distributions, volume fractions, …). We demonstrate the abilities of the framework, and we present possible applications and extensions of the method. The framework is available as both a graphical interface and a Python code.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Cooperative Research and Development Agreement With Georgetown University Report: National Institutes of Health, National Center for Advancing Translational Sciences Clinical and Translational Science Award

Oak Ridge National Laboratory (ORNL) is participating with Georgetown University (GU) as a subrecipient in response to the National Institutes of Health (NIH), National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) (U54 Clinical Trial Optional) funding opportunity announcement. This Cooperative Research and Development Agreement is put in to place to facilitate the development and implementation of clinical interventions that demonstrably improve human health is currently a complex, recursive, and inefficient process that leads to delays of years or decades before discoveries in biomedical research result in health benefits for patients and communities. NCATS conducts and supports research in the science of translation, to discover the mechanistic and operational principles of the intervention development and dissemination process, thereby providing the scientific foundation for improvements in translational efficiency that will accelerate the realization of interventions that improve human health. Under NCATS’ leadership, the CTSA Program supports a national network of medical research institutions called hubs. GU is the lead institution in one of the NIH hubs that was created as a result of a previous NIH CTSA. The missions of the GU have historically included the advancement of health through research in the clinical and biomedical sciences, the education of future leaders in medical and nursing practice and academia, and the provision of compassionate and scientifically competent patient care and service to the Washington, DC community and the nation. GU is the lead institution for the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS), a multi-institutional partnership of medical research institutions forged from a desire to promote clinical research and translational science. Through multiple collaborations among these institutions, GHUCCTS is transforming clinical research and translational science in order to bring new scientific advances to health care. Oak Ridge National Laboratory is the Department of Energy's (DOE) largest science and energy laboratory. Managed since April 2000 by a partnership of the University of Tennessee and Battelle, ORNL was established in 1943 as a part of the secret Manhattan Project to pioneer a method for producing and separating plutonium. During the 1950s and 1960s, ORNL became an international center for the study of nuclear energy and related research in the physical and life sciences. With the creation of DOE in the 1970s, ORNL's mission broadened to include a variety of energy technologies and strategies. Today the laboratory supports the nation with a peacetime science and technology mission that is just as important as, but very different from, its role during the Manhattan Project. ORNL is home to the world's premier center for high performance supercomputing to enable scientific discovery. ORNL has extensive expertise in various areas of computer science that are uniquely situated to support GU. Additionally, ORNL’s leading computational user facilities present a unique opportunity to leverage the largest scale machines for open science in support of the stated mission of the NCATS CTSA. ORNL's partnership with GU will offer unparalleled opportunity in data analytics, deep-learning, artificial intelligence, and urban dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Multiscale astrobiology with the Vera C. Rubin Observatory Legacy Survey of Space and Time

The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) presents an unprecedented opportunity to advance the search for astrobiologically relevant data across diverse astronomical environments. Through its extensive imaging capabilities, LSST will enhance our inventory of Solar System objects and assess their potential astrobiological conditions. Beyond the Solar System, LSST will survey billions of stars, contributing to the detection of exoplanets, characterizing planetary atmospheres at a zeroth-order level, identifying transient phenomena, and exploring conditions within habitable zones. In this paper, we highlight LSST’s unique contribution to astrobiology, complementing other missions and expanding the search for life beyond Earth in the coming decades.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Sodium Rich Vanadium Oxy‐Fluorophosphate – Na 3.2 Ni 0.2 V 1.8 (PO 4 ) 2 F 2 O – as Advanced Cathode for Sodium Ion Batteries

Abstract Conventional sodium‐based layered oxide cathodes are extremely air sensitive and possess poor electrochemical performance along with safety concerns when operating at high voltage. The polyanion phosphate, Na 3 V 2 (PO 4 ) 3 stands out as an excellent candidate due to its high nominal voltage, ambient air stability, and long cycle life. The caveat is that Na 3 V 2 (PO 4 ) 3 can only exhibit reversible capacities in the range of 100 mAh g −1 , 20% below its theoretical capacity. Here, the synthesis and characterizations are reported for the first time of the sodium‐rich vanadium oxyfluorophosphate, Na 3.2 Ni 0.2 V 1.8 (PO 4 ) 2 F 2 O, a tailored derivative compound of Na 3 V 2 (PO 4 ) 3 , with extensive electrochemical and structural analyses. Na 3.2 Ni 0.2 V 1.8 (PO 4 ) 2 F 2 O delivers an initial reversible capacity of 117 mAh g −1 between 2.5 and 4.5 V under the 1C rate at room temperature, with 85% capacity retention after 900 cycles. The cycling stability is further improved when the material is cycled at 50 °C within 2.8–4.3 V for 100 cycles. When paired with a presodiated hard carbon, Na 3.2 Ni 0.2 V 1.8 (PO 4 ) 2 F 2 O cycled with a capacity retention of 85% after 500 cycles. Cosubstitution of the transition metal and fluorine in Na 3.2 Ni 0.2 V 1.8 (PO 4 ) 2 F 2 O as well as the sodium‐rich structure are the major factors behind the improvement of specific capacity and cycling stability, which paves the way for this cathode in sodium‐ion batteries.

25 ENERGY STORAGE↗

DOE OSTI2026

Effect of Specimen Thickness on Fracture Toughness and Plane Stress to Plane Strain Transition in Medium-Density Polyethylene

This study investigates the effect of specimen thickness on fracture toughness and the transition from plane stress to plane strain conditions in Medium-Density Polyethylene (MDPE) using Single Edge Notched Bend (SENB) specimens. Three thickness groups (7.5 mm, 9.0 mm, and 12.1 mm) were tested following ASTM D5045 protocol. Conditional stress intensity factors (KQ) increased from 2.2 MPavm to 2.8 MPavm with increasing thickness, demonstrating significant size dependency. Confocal microscopy revealed a 34% reduction in maximum crack tip opening displacement (CTOD) from 0.478 mm to 0.314 mm as thickness increased, with plastic zone lateral extent decreasing by 32%. This quantitative evidence validates Irwin's theoretical prediction of plastic zone size transition from plane stress r_y˜ (1/2p) (K_I/s_y )^2 to plane strain conditions r_y˜ (1/6p) (K_I/s_y )^2.Scanning electron microscopy confirmed progressive suppression of shear lips and evolution from ductile tearing with extensive polymer chain drawing in thin specimens to localized crazing in thick specimens. Despite all specimens satisfying the ASTM D5045 criterion (B = 2.5(KQ/s_y )^2 ) ,residual shear lips persisted even in the thickest specimens, demonstrating that nominal size requirements alone are insufficient for achieving complete plane strain conditions in highly ductile polymers. The findings emphasize the necessity of integrated analytical and morphological assessment for valid fracture toughness characterization, with critical implications for life assessment and integrity prediction in thick-section polymer components such as natural gas distribution pipelines.

Medium-Density Polyethylene↗

DOE OSTI2022

Radiolabeling and in vitro studies of scandium-44 with HOPO chelator for PET imaging

44 Sc has been attracting interest as a clinically viable PET (positron emission tomography) imaging radionuclide due to its high positron branching ratio, 3.97 hour half-life, ideal positron energy of 632 keV and ability to be produced from a generator as well as from a cyclotron. Scandium is also of interest since the coordination is similar to the lanthanides and Ga 3+ that have demonstrated labeling methods. Further, 47 Sc (a potential therapeutic radionuclide) can serve as a matched isotope pair for theranostic applications. While the labeling studies of 44 Sc with DOTA and DOTA derivatives are quite extensive, there is little data on complexation of scandium with the chelator 3,4,3-(LI-1,2-HOPO). This ligand has been used successfully to radiolabel 89 Zr where it was shown to have high stability in vivo. Additionally, preliminary studies with 86 Y, and non-radioactive scandium show promising complexation constants similar to those found with DOTA derivatives. One major advantage of using HOPO is that radiolabeling can be achieved at room temperature while DOTA requires elevated temperatures, that may be detrimental when radiolabeling biomolecules. Radiolabeling of generator produced 44 Sc versus cyclotron produced 44 Sc is also under investigation as there are currently several different post-elution purification methods of generator 44 Sc, and the potential radiolabeling complications of these eluents has not yet been studied. This work focuses on radiolabeling HOPO with generator produced 44 Sc and the in vitro and radioanalytical evaluation of the resulting complexes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Role of carboxysomes in cyanobacterial CO 2 assimilation: CO 2 concentrating mechanisms and metabolon implications

Many carbon-fixing organisms have evolved CO 2 concentrating mechanisms (CCMs) to enhance the delivery of CO 2 to RuBisCO, while minimizing reactions with the competitive inhibitor, molecular O 2 . These distinct types of CCMs have been extensively studied using genetics, biochemistry, cell imaging, mass spectrometry, and metabolic flux analysis. Highlighted in this paper, the cyanobacterial CCM features a bacterial microcompartment (BMC) called ‘carboxysome’ in which RuBisCO is co-encapsulated with the enzyme carbonic anhydrase (CA) within a semi-permeable protein shell. Further, the cyanobacterial CCM is capable of increasing CO 2 around RuBisCO, leading to one of the most efficient processes known for fixing ambient CO 2 . The carboxysome life cycle is dynamic and creates a unique subcellular environment that promotes activity of the Calvin–Benson (CB) cycle. The carboxysome may function within a larger cellular metabolon, physical association of functionally coupled proteins, to enhance metabolite channelling and carbon flux. In light of CCMs, synthetic biology approaches have been used to improve enzyme complex for CO 2 fixations. Research on CCM-associated metabolons has also inspired biologists to engineer multi-step pathways by providing anchoring points for enzyme cascades to channel intermediate metabolites towards valuable products.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Low-velocity repeated impact behaviors of Polymer Fiber Reinforced Plastics (PFRPs)

Modern fiber-reinforced composites have become ubiquitous across multiple industries due to their excellent weight-to-strength ratio. Typically glass or carbon fibers are widely used. While Glass or Carbon Fiber-Reinforced Plastics (GFPRs or CFPRs) have good stiffness, strength, and fatigue life, they are expensive and difficult to recycle. Researchers are exploring Polymer Fiber-Reinforced Plastics (PFRPs) as an alternative solution. PFRPs utilize polymer fibers and a polymer matrix. A wide range of materials options is available, including low-cost thermoplastics such as polyethylene or polypropylene. These thermoplastics are easy to handle and recyclable without special methods. Manufacturing parts using thermoplastics are well-established as well. However, their mechanical performances have not been extensively studied compared to GFRPs or CFRPs. This study examines the low-velocity impact resistance of PFRPs made of different thermoplastics. The low-velocity impacts are applied through a drop-weight tower. The experiment is divided into two cases: a single perforation impact and low-energy repeated impacts. Energy absorption and the number of impacts to failure are measured. The results are compared to traditional CFRPs which have a thermoset matrix. The PFRPs demonstrate energy absorption capabilities comparable to or greater than those of CFRPs with respect to specimen thickness and density. Additionally, the PFRPs show significantly higher impacts-to-failure than the CFRPs in low-energy repeated impact tests. This is particularly noteworthy considering that the PFRPs are much simpler and more economical to manufacture than CFRPs. To further

Ko, Seunghyun↗

DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Calibration of hyperelastic constitutive models: the role of boundary conditions, search algorithms, and experimental variability

The calibration of hyperelastic constitutive models of soft tissue and tissue surrogates is often treated as an exercise in curve-fitting to the average experimental response, and many of the complicating factors such as experimental boundary conditions and data variability are ignored. Here, we focus on three questions that arise in this area: the ramifications of ignoring the experimental boundary conditions, the use of local optimizers, and the role of data variability. Using data from a uniaxial extension experiment on a tissue surrogate, we study how these three factors affect the calibration of isotropic hyperelastic constitutive models. Our results show that even with the simplest of constitutive models, it is necessary to look beyond a "good fit" to the average.

60 APPLIED LIFE SCIENCES↗