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DOE OSTI2021

Machine learning assisted rediscovery of methane storage and separation in porous carbon from material literature

Porous carbon (PC) has been widely regarded as one of the most promising absorbents for methane storage. Studies show that its uptake capacity and selectivity highly depend on textural structures. Although much effort has been made, unveiling their detailed structure-performance relationship remains a challenge. Here, we propose an innovative study where, with the assistance of machine learning, the hidden relationship of the textural structures of PC with the methane uptake and separation can be derived from existing data in material literature. Machine learning models were trained by the data, including specific surface area, micropore volume, mesopore volume, temperature, and pressure as the input variables and methane uptake as the output variable for prediction. Among the tested models, the multilayer perceptron (MLP) shows the highest accuracy in predicting the methane uptake. In addition, the model enables to automatically construct a uptake performance map in terms of micropore volume and mesopore volume. The obtained MLP model was also extended to explore the CO 2 /CH 4 selectivity by retraining it with the data collected from literature of PC for the CO 2 uptake. Finally, the constructed 2D selectivity map shows that the high selectivity can be achieved in the low CH 4 uptake region.

42 ENGINEERING↗

DOE OSTI2014

Supervised detection of anomalous light curves in massive astronomical catalogs

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Quantitative trait loci (QTL) underlying biomass yield and plant height in switchgrass

Switchgrass (Panicum virgatum L.) biomass yield and feedstock quality improvement are priority research areas for bioenergy feedstock development. Identification of quantitative trait loci (QTL) underlying these traits and of trait-linked markers for application in marker-assisted selection (MAS) is of paramount importance in facilitating switchgrass breeding. Detection of QTL for biomass yield and plant height was conducted on parental linkage maps constructed using a heterozygous pseudo-F-1 population derived from a cross between lowland Alamo genotype AP13 and upland Summer genotype VS16. QTL analysis was performed with composite interval mapping. Four QTL for biomass yield and five QTL for plant height were identified using best linear unbiased predictors across ten and eight environments, respectively. The phenotypic variability explained (PVE) by QTL detected in the across environments analysis ranged from 4.9 to 12.4 % for biomass yield and 5.1 to 12.0 % for plant height. A total of 34 and 38 main effect QTL were detected for biomass yield and plant height, respectively, when data from each environment were analyzed separately. The PVE by individual environment QTL ranged from 3.3 to 15.3 % for biomass yield and from 4.3 to 17.4 % for plant height. In addition, 60 and 51 epistatic QTL were detected for biomass yield and plant height, respectively. Significant QTL by environment interactions were detected for QTL mapped in eight genomic regions for each of the two traits. Seven QTL affected both traits and may represent pleiotropic loci. Overall, 11 genomic regions were identified that were important in controlling biomass yield and/or plant height in switchgrass. Furthermore, the markers linked to the main effect and epistatic QTL may be used in MAS to maximize selection gain in switchgrass breeding, leading to a faster development of better biofuel cultivars.

09 BIOMASS FUELS↗

DOE OSTI2015

Monoamine oxidase: Radiotracer chemistry and human studies

Monoamine oxidase (MAO) oxidizes amines from both endogenous and exogenous sources thereby regulating the concentration of neurotransmitter amines such as serot onin, norepinephrine and dopamine as well as many xenobiotics. MAO inhibitor drugs are used in the treatment of Parkinson’s disease and in depression stimulating the development of radiotracer tools to probe the role of MAO in normal human biology and in disease. Over the past 30 since the first radiotracers were developed and the first PET images of MAO in humans were carried out, PET studies of brain MAO in healthy volunteers and in patients have identified different variables which have contributed to different MAO levels in brain and in peripheral organs. MAO radiotracers and PET have also been used to study the current and developing MAO inhibitor drugs including the selection of doses for clinical trials. In this article, we describe (1) the development of MAO radiotracers; (2) human studies including the relationship of brain MAO levels to genotype, personality, neurological and psychiatric disorders; (3) examples of the use of MAO radiotracers in drug research and development. We will conclude with outstanding needs to improve the radiotracers which are currently used and possible new applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2026

Model-independent measurement of the Higgs boson associated production with two jets and decaying to a pair of W bosons in proton-proton collisions at $\sqrt{s}=13$ TeV

A model-independent measurement of the differential production cross section of the Higgs boson decaying into a pair of W bosons, with a final state including two jets produced in association, is presented. In the analysis, events are selected in which the decay products of the two W bosons consist of an electron, a muon, and missing transverse momentum. The model independence of the measurement is maximized by employing a discriminating variable, developed through machine learning, that is agnostic to the signal hypothesis. The analysis is based on proton-proton collision data at $\sqrt{s}=13$ TeV collected with the CMS detector from 2016–2018, corresponding to an integrated luminosity of 138 fb −1 . The production cross section is measured as a function of the difference in azimuthal angle between the two jets. The differential cross section measurements are used to constrain Higgs boson couplings within the standard model effective field theory framework.

Hadron-Hadron Scattering↗

DOE OSTI2018

Parallel Integration and Chromosomal Expansion of Metabolic Pathways

Robust fermentation of biomass-derived sugars into bioproducts demands the reliable microbial expression of metabolic pathways. Plasmid-based expression systems may suffer from instability and result in highly variable titers, rates, and yields. An established mitigation approach, Chemical Induced Chromosomal Expansion (CIChE), expands a singly integrated pathway to plasmid-like copy numbers, while maintaining stability in the absence of antibiotic selection pressure. Here, we report Parallel Integration and Chromosomal Expansion (PIACE), extensions to CIChE that enable independent expansions of pathway components across multiple loci, use suicide vectors to achieve high-efficiency site-specific integration of sequence-validated multi-gene components, and introduce a heat-curable plasmid to obviate recA deletion post pathway expansion. We applied PIACE to stabilize an isopentenol pathway across three loci in E. coli DH1, and to then generate libraries of pathway component copy-number variants to screen for improved titers. Furthermore, polynomial regressor statistical modeling of the production screening data suggests that increasing copy numbers of all isopentenol pathway components would further improve titers.

09 BIOMASS FUELS↗

DOE OSTI2025

Anticathode effect on multimodal azimuthal oscillations in electron beam generated E×B plasma

Electron beam (e-beam) generated plasmas with applied crossed electric and magnetic (⁠E x B⁠) fields are promising for low-damage (gentle) material processing. However, these plasmas can be subject to the formation of plasma non-uniformities propagating in the ⁠E x B direction. These rotating plasma structures (or “spokes”) enhance the transport of charged species across the magnetic field, which can harm the gentle processing capability of the plasma. In this work, we investigate the role of electrostatically active boundaries on the spoke formation by incorporating a variable bias conducting boundary (known as an anticathode) placed on the axially opposite side of the cathode. Our findings indicate azimuthal mode suppression occurs when the anticathode is electron collecting. Furthermore, we show selective azimuthal mode suppression by biasing the anticathode to an intermediate potential between the cathode and anode potentials. In conclusion, these findings suggest a link between the axial electron confinement in the e-beam generated plasma and azimuthally propagating plasma structure formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Achieving 5,000-h and 8,000-h Low-PGM Electrode Durability on Automotive Drive Cycles

Whereas total Pt loading in anode and cathode catalysts below 0.125 mg cm −2 is required to meet the stringent cost target for automotive fuel cell systems (FCS) for light duty vehicles, low-loaded cathode catalysts are susceptible to unacceptable aging-related performance losses at high current densities. A framework model, validated by accelerated stress test data, has identified cell voltage, relative humidity (RH) and temperature as the key operating variables that affect degradation of a high-activity d-PtCo/C cathode catalyst with 0.1 mg cm −2 Pt loading. Drive cycle simulations indicate that these can be controlled by properly selecting the minimum FCS power, compressor-expander module (CEM) turndown, and stack coolant temperature. The optimum system parameters are 4-kW e minimum power for an 80-kW e FCS, CEM turndown of 12.5, and 66 °C average coolant exit temperature that combine to limit the maximum cell voltage to 850 mV and outlet RH to 90%–100%. Depending on Pt loading, the mismatch between actual and allowable degradation for 10% power loss over 5,000-h lifetime requires the stack to be oversized by 2.4%–5%, resulting in 8.4%–41% lower Pt utilization and 7.1%–20.5% penalty in stack cost. The corresponding results for 8,000-h lifetime are 10.3%-14% stack oversizing, 23%–51.8% lower Pt utilization, and 24.1%–35.4% stack cost penalty.

08 HYDROGEN↗

DOE OSTI2020

Interseasonal Connections between the Timing of the Stratospheric Final Warming and Arctic Sea Ice

Connections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.

Kelleher, Michael↗

DOE OSTI2017

The association between high birth weight and the risks of childhood CNS tumors and leukemia: an analysis of a US case-control study in an epidemiological database

Background: High birth weight (BW), 4000 g or larger, is an established risk factor for childhood leukemia. However, its association with central nervous system (CNS) tumor risk is yet unclear. The present study examined it, analyzing data obtained from a case-control study conducted among three states from the US. The association with childhood leukemia risk was also further examined. Methods: In this study, a data set provided by the Comprehensive Epidemiologic Data Resource was analyzed with an official permission. The original case-control study was conducted to examine the association between paternal preconception exposure to ionizing radiation and childhood cancer risk. Cases with childhood cancer were mainly ascertained from local hospitals, and controls were selected, matched with birth year (1-year category), county of residence, sex, ethnicity and maternal age (+/-2 years). Since the ID numbers were unavailable, conventional logistic analyses were conducted adjusting for those matching variables except for the county of residence. In addition to those variables, gestational age, age at diagnosis and study sites as covariables were included in the logistic models. Results: Analyzed subjects were 72 CNS tumor cases, 124 leukemia cases and 822 controls born from 1945 to 1989. The odds ratios (ORs) of CNS tumor risk for children with low BWs (<2500 g) and high BWs (>4000 g) were 2.0 (95% confidence interval [CI]) = 0.7, 5.9) and 2.5 (95%CI = 1.2, 5.2)], respectively. When high-BW children were restricted to those who were large for gestational age (LGA), the OR for high-BW children remained similar (OR = 2.7; 95%CI = 1.1, 6.2). On the other hand, the ORs of leukemia risk for children with low and high BWs were 0.8 (95%CI = 0.2, 3.0) and 1.4 (95%CI = 0.7, 2.6), respectively. In the normal range of BW (2500–4000 g), higher BW was positively associated with CNS tumor risk (beta = 0.0011, p for trend = 0.012). However, the association with leukemia risk was not significant (beta = -0.0002, p for trend = 0.475). Conclusion: High-BW and LGA children had an elevated childhood CNS tumor risk. In the normal BW range, the BW itself was positively related to CNS tumor risk. No significant association between BW and childhood leukemia risk was observed in this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Performance Evaluation of Three RTU Energy Efficiency Technologies

This project was part of an effort by CLEAResult and ComEd to evaluate the energy saving potential of emerging technologies in the Chicago area. This project focused on evaluating emerging technologies related to rooftop units (RTUs). An RTU with a single-stage compressor and a constant-speed fan with an induction motor was selected as the baseline for technology comparison. Three retrofit strategies were investigated. The first two involved replacing the single-stage compressor of an RTU by either a two-stage or variable-speed compressor and adding a variable frequency drive (VFD) to the constant speed fan. The use of a multi-/variable-stage compressor improves the part-load efficiency of the compressor which will ultimately result in annual energy savings as well as peak demand shaving in some cases where the design capacity of the RTU is larger than the maximum cooling load of the building space that it is serving. The third technology was the use of a high rotor pole switched reluctance motor (SRM) as a replacement for the constant-speed supply fan. The SRM was applied in single-speed, two-stage and variable-speed compressor RTUs. SRM motors run via reluctance torque. Their stator poles are driven by direct current (DC) power and require an inverter as well as active control when using alternating current (AC) power. This inherent property results in high efficiency over a range of operating conditions. It also exhibits higher efficiency compared to variable frequency drives (VFDs) since its switching frequency is much slower (SCE, 2018).The three technologies investigated are summarized below: 1) Replacing the single-speed compressor with a two-stage compressor and adding a VFD to the supply fan. 2)Replacing the single-speed compressor with a variable-speed compressor and adding a VFD to the supply fan. 3) Replacing the constant-speed induction motor of the supply fan with a high rotor pole SRM. DOE’s building simulation platform EnergyPlus and its graphical user interface OpenStudio were used to evaluate the energy-saving potential of upgrading RTUs, by leveraging experimental data from previous research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The Prospects for Pumped Storage Hydropower in Alaska

Key Takeaways: The resource mapping analysis confirmed that numerous locations in Alaska are suitable for the development of pumped storage hydropower (PSH) projects, both larger grid scale projects and smaller projects that could be suitable for remote communities; The resource assessment for larger, grid-scale projects showed the potential for more than 1,800 closed-loop systems in Alaska, with a total energy storage capacity of about 4 terawatt hours (TWh); Because of their small reservoir sizes and dam heights, many locations were identified as potentially suitable for small-scale PSH systems. Nearly 50% of the identified potentially suitable small-scale PSH sites are in Southeast Alaska; PSH candidate sites were part of the optimal capacity expansion solution in all scenarios analyzed for the Railbelt system. Depending on the scenario, the new PSH capacity that the model selected for the analysis period until 2046 ranged from 300 MW to 600 MW. The locations and timing of new PSH investments vary in different scenarios; Lithium-ion batteries were also selected a source of new generating capacity in all analyzed scenarios for the Railbelt system, indicating that the system will need a mix of short- and long-duration energy storage to support variable renewable energy sources and provide system reliability in the future; For rural communities, analysis results showed that PSH suitability is very site-specific; in addition to diesel fuel costs and PSH capital costs, suitability depends heavily on available renewable resources and existing infrastructure (e.g., reservoirs, transmission access and construction road access); The analysis for rural communities also showed that PSH projects with 10-hour energy storage are likely to be more economical for remote community applications in Alaska than those with larger reservoirs that could provide 10 days of energy storage; Lithium-ion batteries seem to be an economically more viable energy storage option for small, remote communities in Alaska.

13 HYDRO ENERGY↗

DOE OSTI2015

New opportunities for quasielastic and inelastic neutron scattering at steady-state sources using mechanical selection of the incident and final neutron energy

We propose a modification of the neutron wide-angle velocity selector (WAVES) device that enables inelastic (in particular, quasielastic) scattering measurements not relying on the neutron time-of-flight. The proposed device is highly suitable for a steady-state neutron source, somewhat similar to a triple-axis spectrometer, but with simultaneous selection of the incident and final neutron energy over a broad range of scattering momentum transfer. Both the incident and final neutron velocities are defined by the WAVES geometry and rotation frequency. The variable energy transfer is achieved through the natural variation of the velocity of the transmitted neutrons as a function of the scattering angle component out of the equatorial plane.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗

DOE OSTI2019

Underestimation of column NO 2 amounts from the OMI satellite compared to diurnally varying ground-based retrievals from multiple PANDORA spectrometer instruments

Retrievals of total column NO 2 (TCNO 2 ) are compared for 14 sites from the Ozone Measuring Instrument (OMI using OMNO2-NASA v3.1) on the AURA satellite and from multiple ground-based PANDORA spectrometer instruments making direct-sun measurements. While OMI accurately provides the daily global distribution of retrieved TCNO 2 , OMI almost always underestimates the local amount of TCNO 2 by 50 % to 100 % in polluted areas, while occasionally the daily OMI value exceeds that measured by PANDORA at very clean sites. Compared to local ground-based or aircraft measurements, OMI cannot resolve spatially variable TCNO 2 pollution within a city or urban areas, which makes it less suitable for air quality assessments related to human health. In addition to systematic underestimates in polluted areas, OMI's selected 13:30 Equator crossing timepolar orbit causes it to miss the frequently much higher values of TCNO 2 that occur before or after the OMI overpass time. Six discussed Northern Hemisphere PANDORA sites have multi-year data records (Busan,Seoul, Washington DC, Waterflow, New Mexico, Boulder, Colorado, and Mauna Loa),and one site in the Southern Hemisphere (Buenos Aires, Argentina). The first four of these sites and Buenos Aires frequently have high TCNO 2 (TCNO 2 > 0.5 DU). Eight additional sites have shorter-term data records in the US and South Korea. One of these is a 1-year data record from a highly polluted site at City College in New York City with pollution levels comparable to Seoul, South Korea. OMI-estimated air mass factor, surface reflectivity, and the OMI 24 km × 13 km FOV (field of view)are three factors that can cause OMI to underestimate TCNO 2 . Because of the local inhomogeneity of NO x emissions, the large OMI FOV is the most likely factor for consistent underestimates when comparing OMI TCNO 2 to retrievals from the small PANDORA effective FOV (measured in m 2 ) calculated from the solar diameter of 0.5°.

47 OTHER INSTRUMENTATION↗

DOE OSTI2015

Factors Affecting Seismic Velocity in Alluvium

Yucca Flat at the Nevada National Security Site has been selected as the Source Physics Experiment (SPE) Dry Alluvium Geology Phase II site. The alluvium in this part of Yucca Flat is typical of desert basin fill, with discontinuous beds that are highly variable in clast size and provenance. Detailed understanding of the subsurface geology will be needed for interpretation of the SPE seismic data. A 3D seismic velocity model, created for Yucca Flat using interval seismic velocity data, shows variations in velocity within alluvium near the SPE Phase II site beyond the usual gradual increase of density with depth due to compaction. In this study we examined borehole lithologic logs, geophysical logs, downhole videos, and laboratory analyses of sidewall core samples to understand which characteristics of the alluvium are related to these variations in seismic velocity. Seismic velocity of alluvium is generally related to its density, which can be affected by sediment provenance, clast size, gravel percentage, and matrix properties, in addition to compaction. This study presents a preliminary subdivision of the alluvial strata in the SPE Phase II area into mappable units expected to be significant to seismic modeling. Further refinements of the alluvial units may be possible when seismic data are obtained from SPE Phase II tests.

58 GEOSCIENCES↗

DOE OSTI2021

Fragmentation of jets containing a prompt J$/\psi$ meson in PbPb and pp collisions at $\sqrt{s_\mathrm{NN}} =$ 5.02 TeV

Jets containing a prompt J$/\psi$ meson are studied in lead-lead collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV, using the CMS detector at the LHC. Jets are selected to be in the transverse momentum range of 30 $\lt p_\mathrm{T} \lt$ 40 GeV. The J$/\psi$ yield in these jets is evaluated as a function of the jet fragmentation variable $z$, the ratio of the J$/\psi$$p_\mathrm{T} $ to the jet $p_\mathrm{T}$. The nuclear modification factor, $R_\mathrm{AA}$, is then derived by comparing the yield in lead-lead collisions to the corresponding expectation based on proton-proton data, at the same nucleon-nucleon center-of-mass energy. The suppression of the J$/\psi$ yield shows a dependence on $z$, indicating that the interaction of the J$/\psi$ with the quark-gluon plasma formed in heavy ion collisions depends on the fragmentation that gives rise to the J$/\psi$ meson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗