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NASA NTRS2009

Desktop Application Program to Simulate Cargo-Air-Drop Tests

The DSS Application is a computer program comprising a Windows version of the UNIX-based Decelerator System Simulation (DSS) coupled with an Excel front end. The DSS is an executable code that simulates the dynamics of airdropped cargo from first motion in an aircraft through landing. The bare DSS is difficult to use; the front end makes it easy to use. All inputs to the DSS, control of execution of the DSS, and postprocessing and plotting of outputs are handled in the front end. The front end is graphics-intensive. The Excel software provides the graphical elements without need for additional programming. Categories of input parameters are divided into separate tabbed windows. Pop-up comments describe each parameter. An error-checking software component evaluates combinations of parameters and alerts the user if an error results. Case files can be created from inputs, making it possible to build cases from previous ones. Simulation output is plotted in 16 charts displayed on a separate worksheet, enabling plotting of multiple DSS cases with flight-test data. Variables assigned to each plot can be changed. Selected input parameters can be edited from the plot sheet for quick sensitivity studies.

Cuthbert, Peter↗

DOE OSTI2022

Electrochemical, thermodynamic, and physical properties of tetradecyltrihexylphosphonium ([P 6,6, 6,14 ] + ) and methyl-propyl piperidinium containing ionic liquids and their propylene carbonate solutions

Here, the viscosity, conductivity, electrochemical window and related thermodynamic properties such as excess volume and dynamic viscosity deviation of two phosphonium ionic liquids were measured and calculated for “as-supplied” and dried neat liquids and also v/v mixtures of 99/1, 95/5, 90/10, 75/25, and 50/50 of the ionic liquids with propylene carbonate (PC). Tetradecyltrihexylphosphonium dicyanamide ([P 6,6,6,14 ] + dicyanamide), Cyphos 105, and tetradecyltrihexylphosphonium bis(trifluororomethanesulfonyl)imide (called bistriflimide) ([P 6,6,6,14 ] + bistriflimide), Cyphos 109, ionic liquids were studied. Generally speaking, there were slight differences in the measured properties of the wet and dried IL solutions which were reflected in differences if the calculated properties. The measured and calculated properties were compared with those collected and derived from a piperidinium-based ionic liquid, methyl-propyl piperidinium bistriflimide. Arrhenius plots for both the viscosity and conductivity were linear, with the linearity of the Litovitz plots being slightly higher. The viscosity and conductivity of the phosphonium solutions yielded Walden Plots that differed from Walden plots of piperidinium solutions and other ionic liquid solutions. For the phosphonium based ionic liquids, the ionicity was found to increase with increasing dilution in propylene carbonate. The electrochemical windows of the ionic liquids were determined as a function of the concentration of the ionic liquid present in the solution. The size of the window generally initially decreased and then increased with the addition of PC for the [P 6,6,6,14 ] + dicyanamide ionic liquid increasing from 3.4 V in the 95/5 v/v (volume Cyphos 105) to volume of PC solvent) to 3.7 in the 50/50 dried IL case. The electrochemical windows of the dried liquids were slightly larger 3.5 V for the 95/5 v/v and 4.2 V for the 50/50 v/v Cyphos 105/PC solutions. The electrochemical window was larger and the conductivity was higher for the piperidinium IL solutions, but since the ionicity increases with dilution, the phosphonium based IL solutions may prove favorable for processes such as electrochemical reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Tropical Forest Soil Microbiome Modulates Leaf Heat Tolerance More Strongly Under Warming Than Ambient Conditions

ABSTRACT It is unclear how plants respond to increasing temperatures. Leaf heat tolerance (LHT) is often at its upper limit in tropical forests, suggesting that climate change might negatively impact these forests. We hypothesized that intraspecific variation in LHT might be associated with changes in the soil microbiome, which might also respond to climate. We hypothesized that warming would increase LHT through changes in the soil microbiome: we combined an in situ tropical warming experiment with a shade house experiment in Puerto Rico. The shade house experiment consisted of growing seedlings of Guarea guidonia , a dominant forest species, under different soil microbiome treatments (reduced arbuscular mycorrhizal fungi, reduced plant pathogens, reduced microbes, and unaltered) and soil inoculum from the field experiment. Heat tolerance was determined using chlorophyll fluorescence ( F V /F m ) on individual seedlings in the field and on groups of seedlings (per pot) in the shade house. We sequenced soil fungal DNA to analyze the impacts of the treatments on the soil microbiome. In the field, seedlings from ambient temperature plots showed higher F V /F m values under high temperatures (0.648 at 46°C and 0.067 at 52°C) than seedlings from the warming plots (0.535 at 46°C and 0.031 at 52°C). In the shade house, the soil microbiome treatments significantly influenced the fungal community composition and LHT ( T crit and F V /F m ). Reduction in fungal pathogen abundance and diversity altered F V /F m before T 50 for seedlings grown with soil inoculum from the warming plots but after T 50 for seedlings grown with soil inoculum from the ambient plots. Our findings emphasize that the soil microbiome plays an important role in modulating the impacts of climate change on plants. Understanding and harnessing this relationship might be vital for mitigating the effects of warming on forests, emphasizing the need for further research on microbial responses to climate change.

Hernandes Villani, Gabriela [Department of Plant B↗

DOE OSTI2021

Variation in hyphal production rather than turnover regulates standing fungal biomass in temperate hardwood forests

Abstract Soil fungi link above‐ and belowground carbon (C) fluxes through their interactions with plants and contribute to C and nutrient dynamics through the production, turnover, and activity of fungal hyphae. Despite their importance to ecosystem processes, estimates of hyphal production and turnover rates are relatively uncommon, especially in temperate hardwood forests. We sequentially harvested hyphal ingrowth bags to quantify the rates of Dikarya (Ascomycota and Basidiomycota) hyphal production and turnover in three hardwood forests in the Midwestern United States, where plots differed in their abundance of arbuscular (AM)‐ vs. ectomycorrhizal (ECM)‐associated trees. Hyphal production rates increased linearly with the percentage of ECM trees and annual production rates were 66% higher in ECM‐ than AM‐dominated plots. Hyphal turnover rates did not differ across the mycorrhizal gradient (plots varying in their abundance of AM vs. ECM trees), suggesting that the greater fungal biomass in ECM‐dominated plots relates to greater fungal production rather than slower fungal turnover. Differences in hyphal production across the gradient aligned with distinctly different fungal communities and activities. As ECM trees increased in dominance, fungi inside ingrowth bags produced more extracellular enzymes involved in degrading nitrogen (N)‐bearing relative to C‐bearing compounds, suggesting greater fungal (and possibly plant) N demand in ECM‐dominated soils. Collectively, our results demonstrate that shifts in temperate tree species composition that result in changes in the dominant type of mycorrhizal association may have strong impacts on Dikarya hyphal production, fungal community composition and extracellular enzyme activity, with important consequences for soil C and N cycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A comprehensive investigation on the properties of nanostructured cerium oxide

The structural, optical, magnetic and electrical properties of cerium oxide (CeO{sub 2}) nanoparticles prepared by hydrothermal route are analyzed by subjecting them to characterization techniques such as Powder X-ray diffraction (PXRD), High resolution scanning electron microscope (HRSEM), High resolution transmission electron microscope (HRTEM), Energy Dispersive X-ray Analysis (EDAX), Fourier transform infra red spectroscopy (FTIR), Raman spectroscopy, Ultraviolet–Visible analysis, Vibrating sample magnetometer (VSM) analysis and Dielectric measurements. The PXRD, FTIR, Raman and EDAX analyses confirm the formation of CeO{sub 2} nanoparticles. The PXRD studies reveal that the cerium oxide nanoparticles have crystalline nature and have Face Centered Cubic structure. The average crystallite size, estimated using Scherrer formula, is 7 nm. The HRSEM and HRTEM images reveal that the CeO{sub 2} nanoparticles have spherical morphology with an average particle size of 23 nm. The optical band gap energy of the cerium oxide nanoparticles, calculated from UV–Vis studies, is 3.4 eV which could be due to the substantial concentration of Ce{sup 3+} ions in the ceria nanoparticles. The Ferromagnetic behavior of CeO{sub 2} at room temperature is implied from VSM studies. The Dielectric analysis divulge that the dielectric constant of cerium oxide nanoparticles decreases as the frequency and temperature increases. The electrical behaviour, activation energy and relaxation time of electrons of CeO{sub 2} nanoparticles are studied by plotting Nyquist plot, Arrhenius plot and Bode plot respectively.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Soil fertility management for sustainable Miscanthus × giganteus production: Increased tiller weight from nitrogen management explains yield gains in aged miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha −1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha −1 , resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha −1 , forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m −2 ) and tiller weight (g tiller −1 ) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

09 BIOMASS FUELS↗

DOE OSTI2018

Corrosion properties of phase reversion induced nano/ultrafine grained AISI 304 metastable austenite stainless steel

Highlights: • AISI 304 stainless steel was cold rolled under 3 cryogenic temperatures and room temperature, after annealing bulk nano/ultrafine grained material was obtained. • Microstructure of samples was studied by TEM, −120 °C rolled sample had an equiaxed microstructure. • Corrosion resistance of samples was studied by polarization curve, EIS, and Mott-Schottky plot, −120 °C rolled sample had the best corrosion performance. • The distinctive polarization curve of −120 °C rolled sample indicated its passive film had peculiar feature, the M-S plot showed its abnormal semiconductor character. - Abstract: AISI 304 metastable austenite stainless steel was cold rolled under cryogenic temperature and transformed into martensite completely, after reverse transformation by annealing, bulk nano/ultrafine grained material was obtained. The material’s microstructure was observed by TEM, and the corrosion resistance was studied by polarization curve, EIS, and Mott-Schottky plot. Results showed that samples cold rolled at −120 °C had an equiaxed microstructure and displayed the best corrosion performance. The distinctive polarization curve shape indicated that its passive film had a peculiar feature, and the M-S plot showed its abnormal semiconductor character. XPS measurements are used to directly characterize the composition of passive film formed on specimens. Heterogeneous microstructures might help with the improvement on corrosion resistance of the nano/ultrafine grained stainless steel.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Soil Biogenic Volatile Organic Compound Flux in a Mixed Hardwood Forest: Net Uptake at Warmer Temperatures and the Importance of Mycorrhizal Associations

Abstract Biogenic volatile organic compounds (bVOCs) play important roles in ecological interactions and Earth system processes, yet the biological and physical processes that drive soil bVOC exchanges remain poorly understood. In temperate forests, nearly all tree species associate with arbuscular mycorrhizal (AM) or ectomycorrhizal (ECM) fungi. Given well‐established differences in soil biogeochemistry between AM‐dominated and ECM‐dominated stands, we hypothesized that bVOC exchanges with the atmosphere would differ between soils from the two stand types. We measured bVOC fluxes at the soil‐atmosphere interface in plots dominated by AM‐ and ECM‐associated trees in a deciduous forest in south‐central Indiana, USA during the early and late vegetative growing season. Soils in both AM‐ and ECM‐dominated plots were a net bVOC sink following leaf‐out and were a greater bVOC sink or smaller source at warmer soil temperatures ( T s ). The flux of different bVOCs from ECM plots was often related to soil water content in addition to T s . Methanol dominated total bVOC fluxes, and ECM soils demonstrated greater uptake relative to AM‐dominated plots, on the order of 170 nmol m −2 hr −1 during the early growing season. Our results demonstrate the importance of soil dynamics characterized by mycorrhizal associations to bVOC dynamics in forested ecosystems and emphasize the need to study bidirectional soil bVOC uptake and emission processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Radiocarbon Analyses Quantify Peat Carbon Losses With Increasing Temperature in a Whole Ecosystem Warming Experiment

Abstract Climate warming is expected to accelerate peatland degradation and release rates of carbon dioxide (CO 2 ) and methane (CH 4 ). Spruce and Peatlands Responses Under Changing Environments is an ecosystem‐scale climate manipulation experiment, designed to examine peatland ecosystem response to climate forcings. We examined whether heating up to +9 °C to 3 m‐deep in a peat bog over a 7‐year period led to higher C turnover and CO 2 and CH 4 emissions, by measuring 14 C of solid peat, dissolved organic carbon (DOC), CH 4 , and dissolved CO 2 (DIC). DOC, a major substrate for heterotrophic respiration, increased significantly with warming. There was no 7‐year trend in the DI 14 C of the ambient plots which remained similar to their DO 14 C. At +6.75 °C and +9 °C, the 14 C of DIC, a product of microbial respiration, initially resembled ambient plots but became more depleted over 7 years of warming. We attributed the shifts in DI 14 C to the increasing importance of solid phase peat as a substrate for microbial respiration and quantified this shift via the radiocarbon mass balance. The mass‐balance model revealed increases in peat‐supported respiration of the catotelm depths in heated plots over time and relative to ambient enclosures, from a baseline of 20%–25% in ambient enclosures, to 35%–40% in the heated plots. We find that warming stimulates microorganisms to respire ancient peat C, deposited under prior climate (cooler) conditions. This apparent destabilization of the large peat C reservoir has implications for peatland‐climate feedbacks especially if the balance of the peatland is tipped from net C sink to C source.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Dinitrogen Emissions Dominate Nitrogen Gas Emissions From Soils With Low Oxygen Availability in a Moist Tropical Forest

Lowland tropical forest soils are relatively N rich and are the largest global source of N 2 O (a powerful greenhouse gas) to the atmosphere. Despite the importance of tropical N cycling, there have been few direct measurements of N 2 (an inert gas that can serve as an alternate fate for N 2 O) in tropical soils, limiting our ability to characterize N budgets, manage soils to reduce N 2 O production, or predict the future role that N limitation to primary productivity will play in buffering against climate change. We collected soils from across macro‐ and micro‐topographic gradients that have previously been shown to differ in O 2 availability and trace gas emissions. We then incubated these soils under oxic and anoxic headspaces to explore the relative effect of soil location versus transient redox conditions. No matter where the soils came from, or what headspace O 2 was used in the incubation, N 2 emissions dominated the flux of N gas losses. In the macrotopography plots, production of N 2 and N 2 O were higher in low O 2 valleys than on more aerated ridges and slopes. In the microtopography plots, N 2 emissions from plots with lower mean soil O 2 (5%–10%) were greater than in plots with higher mean soil O 2 (10%–20%). We estimate an N gas flux of ∼37 kg N/ha/yr from this forest, 99% as N 2 . These results suggest that N 2 fluxes may have been systematically underestimated in these landscapes, and that the measurements we present call for a reevaluation of the N budgets in lowland tropical forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations

Abstract The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO 2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO 2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗

DOE OSTI2026

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗

DOE OSTI2021

Experimental warming and its legacy effects on root dynamics following two hurricane disturbances in a wet tropical forest

Abstract Tropical forests are expected to experience unprecedented warming and increases in hurricane disturbances in the coming decades; yet, our understanding of how these productive systems, especially their belowground component, will respond to the combined effects of varied environmental changes remains empirically limited. Here we evaluated the responses of root dynamics (production, mortality, and biomass) to soil and understory warming (+4°C) and after two consecutive tropical hurricanes in our in situ warming experiment in a tropical forest of Puerto Rico: Tropical Responses to Altered Climate Experiment (TRACE). We collected minirhizotron images from three warmed plots and three control plots of 12 m 2 . Following Hurricanes Irma and María in September 2017, the infrared heater warming treatment was suspended for repairs, which allowed us to explore potential legacy effects of prior warming on forest recovery. We found that warming significantly reduced root production and root biomass over time. Following hurricane disturbance, both root biomass and production increased substantially across all plots; the root biomass increased 2.8‐fold in controls but only 1.6‐fold in previously warmed plots. This pattern held true for both herbaceous and woody roots, suggesting that the consistent antecedent warming conditions reduced root capacity to recover following hurricane disturbance. Root production and mortality were both related to soil ammonium nitrogen and microbial biomass nitrogen before and after the hurricanes. This experiment has provided an unprecedented look at the complex interactive effects of disturbance and climate change on the root component of a tropical forested ecosystem. A decrease in root production in a warmer world and slower root recovery after a major hurricane disturbance, as observed here, are likely to have longer‐term consequences for tropical forest responses to future global change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Observed variation in soil properties can drive large variation in modelled forest functioning and composition during tropical forest secondary succession

Censuses of tropical forest plots reveal large variation in biomass and plant composition. This paper evaluates whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In Central America, soil-induced variation in plant biomass increased with mean annual precipitation because of changes in nutrient limitation. In Central America, large variation in plant biomass and ecosystem composition arises mechanistically from realistic variation in soil properties. Finally, the degree of biomass and compositional variation is climate sensitive. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

DOE OSTI2019

EMSL-Computing/fticRanalysis

fticRanalysis - a package to hand data formatting and storage of Fourier-transform ion cyclotron resonance (FTICR) data in a generalizable way. Additional functionality is available for manipulating and transforming the data, filtering the data based on different criteria, creating summary plots (e.g. Van Krevelen plots, Kendrick plots, etc.), summarizing group-level data, comparing treatment groups, and making complementary plotting functionality

White, Amanda↗

DOE OSTI2025

Data for Soil Fertility Management for Sustainable Miscanthus × giganteus Production: Increased Tiller Weight from Nitrogen Management Explains Yield Gains in Aged Miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha−1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha−1, resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha−1, forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m−2) and tiller weight (g tiller−1) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

miscanthus↗