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Development of a Systematic and Extensible Force Field for Peptoids (STEPs)

Peptoids (N-substituted glycines) are a class of biomimetic polymers that have attracted significant attention due to their accessible synthesis and enzymatic and thermal stability relative to their naturally occurring counterparts (polypeptides). While these polymers provide the promise of more robust functional materials via hierarchical approaches, they present a new challenge for computational structure prediction for material design. The reliability of calculations hinges on the accuracy of interactions represented in the force field used to model peptoids. For proteins, structure prediction based on sequence and de novo design has made dramatic progress in recent years; however, these models are not readily transferable for peptoids. Current efforts to develop and implement peptoid-specific force fields are spread out, leading to replicated efforts and a fragmented collection of parameterized sidechains. Here, we developed a peptoid-specific force field containing 70 different side chains, using GAFF2 as starting point. The new model is validated based on the generation of Ramachandran-like plots from DFT optimization compared against force field reproduced potential energy and free energy surfaces as well as the reproduction of equilibrium cis/trans values for some residues experimentally known to form helical structures. In conclusion, equilibrium cis/trans distributions (Kct) are estimated for all parameterized residues to identify which residues have an intrinsic propensity for cis or trans states in the monomeric state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Narrow operator models of stellarator equilibria in Fourier Zernike basis

Numerical computation of the ideal magnetohydrodynamic (MHD) equilibrium magnetic field is at the base of stellarator optimisation and provides the starting point for solving more sophisticated partial differential equations like transport or turbulence models. Conventional approaches solve for a single stationary point of the ideal MHD equations, which is fully defined by three invariants and the numerical scheme employed by the solver. We present the first numerical approach that can solve for a continuous distribution of equilibria with fixed boundary and rotational transform, varying only the pressure invariant. This approach minimises the force residual by optimising parameters of multilayer perceptrons that map from a scalar pressure multiplier to the Fourier Zernike basis as implemented in the modern stellarator equilibrium solver DESC.

fusion plasma↗

Multiphysics FISPACT-II and TENDL-2019 simulation: neutron-induced damage metrics

Nuclear interactions can be the source of atomic displacement, irradiation-induced defects and transmutation in structural materials. Such quantities are derived from, or can be correlated to, nuclear kinematic simulations of primary atomic energy distributions spectra and the quantification of the numbers of secondary defects produced per primary as a function of the available recoils, residual and emitted, energies. Recoil kinematics of neutral, residual, gas, proton, alpha particle emissions are now more rigorously treated based on recent, complete and enhanced nuclear data parsed in state-of-the-art processing tools. Defect production metrics are the starting point in the complex problem of correlating and simulating the behaviour of materials under irradiation, as experimental information is rare or scattered. Detailed, segregated primary knock-on-atom metrics are now becoming available as the starting point of further simulation processes of isolated and clustered defects in material lattices. This allows more materials, lattices, neutron incident energy ranges, and irradiation conditions to be explored with sufficient data to adequately cover both standard and novel applications and materials: the broader reactor applications landscape. The damage metrics of of materials are systematically explored under typical but different reactor's type environment. The inventory code FISPACT-II combined with the enhanced nuclear data forms of the TENDL-2019 libraries allow one to not only calculate dpa from mostly scattering events but to also properly predict gas production, nuclear heating and transmutation under the same conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Moments of parton distribution functions of the pion from lattice QCD using gradient flow

We present a nonperturbative determination of the pion valence parton distribution function (PDF) moment ratios ⟨𝑥 𝑛−1 ⟩/⟨𝑥⟩ up to 𝑛 = 6, using the gradient flow in lattice quantum chromodynamics (QCD). As a testing ground, we employ SU(3) isosymmetric gauge configurations generated by the OpenLat initiative with a pseudoscalar mass of 𝑚 𝜋 ≃ 411 MeV. Our analysis uses four lattice spacings and a nonperturbatively improved action, enabling full control over the continuum extrapolation, and the limit of vanishing flow time, 𝑡 →0. The flowed ratios exhibit O(𝑎 2 ) scaling across the ensembles, and the continuum-extrapolated results, matched to the $\overline{MS}$ scheme at 𝜇 = 2 GeV using next-to-next-to-leading order matching coefficients, show only mild residual flow-time dependence. The resulting ratios, computed with a relatively small number of configurations, are consistent with phenomenological expectations for the pion’s valence distribution, with statistical uncertainties that are competitive with modern global fits. These findings demonstrate that the gradient flow provides an efficient and systematically improvable method to access partonic quantities from first principles. Future extensions of this work will target lighter pion masses toward the physical point, and applications to nucleon structure such as the proton PDFs and the gluon and sea-quark distributions.

lattice QCD↗

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

Performance Analysis and Optimal Node-aware Communication for Enlarged Conjugate Gradient Methods

Krylov methods are a key way of solving large sparse linear systems of equations but suffer from poor strong scalability on distributed memory machines. Furthermore, this is due to high synchronization costs from large numbers of collective communication calls alongside a low computational workload. Enlarged Krylov methods address this issue by decreasing the total iterations to convergence, an artifact of splitting the initial residual and resulting in operations on block vectors. In this article, we present a performance study of an enlarged Krylov method, Enlarged Conjugate Gradients (ECG), noting the impact of block vectors on parallel performance at scale. Most notably, we observe the increased overhead of point-to-point communication as a result of denser messages in the sparse matrix-block vector multiplication kernel. Additionally, we present models to analyze expected performance of ECG, as well as motivate design decisions. Most importantly, we introduce a new point-to-point communication approach based on node-aware communication techniques that increases efficiency of the method at scale.

97 MATHEMATICS AND COMPUTING↗

3D Multiresolution Velocity Model Fusion with Probability Graphical Models

ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.

Geochemistry & Geophysics↗

Delensing the CMB with the cosmic infrared background: the impact of foregrounds

ABSTRACT The most promising avenue for detecting primordial gravitational waves from cosmic inflation is through measurements of degree-scale cosmic microwave background (CMB) B-mode polarization. This approach must face the challenge posed by gravitational lensing of the CMB, which obscures the signal of interest. Fortunately, the lensing effects can be partially removed by combining high-resolution E-mode measurements with an estimate of the projected matter distribution. For near-future experiments, the best estimate of the latter will arise from co-adding internal reconstructions (derived from the CMB itself) with external tracers such as the cosmic infrared background (CIB). In this work, we characterize how foregrounds impact the delensing procedure when CIB intensity, I, is used as the matter tracer. We find that higher point functions of the CIB and Galactic dust such as 〈BEI〉c and 〈EIEI〉c can, in principle, bias the power spectrum of delensed B-modes. To quantify these, we first estimate the dust residuals in currently available CIB maps and upcoming, foreground-cleaned Simons Observatory CMB data. Then, using non-Gaussian simulations of Galactic dust – extrapolated to the relevant frequencies, assuming the spectral index of polarized dust emission to be fixed at the value determined by Planck – we show that the bias to any primordial signal is small compared to statistical errors for ground-based experiments, but might be significant for space-based experiments probing very large angular scales. However, mitigation techniques based on multifrequency cleaning appear to be very effective. We also show, by means of an analytical model, that the bias arising from the higher point functions of the CIB itself ought to be negligible.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatiotemporal mapping of microscopic strains and defects to reveal Li-dendrite-induced failure in all-solid-state batteries

Solid-state electrolytes (SSEs) are key to the success and reliability of all-solid-state lithium batteries, potentially enabling improvements in terms of safety and energy density over state-of-the-art lithium-ion batteries. However, there are several critical challenges to their implementation, including the interfacial instability stemming from the dynamic interaction of as-formed dendritic lithium during cycling. Here, we emphasize the importance of studying the spatial distribution and temporal evolution of strains and defects in crystalline solid-state electrolytes at the micro-scale, and how this affects dendrite growth. A proof-of-principle study is demonstrated using the synchrotron radiation based micro Laue X-ray diffraction method, and a custom-developed in-situ cycling device. Defects and residual strains are mapped, and the evolution of intragranular misorientation is observed. The feasibility of using this technique is discussed, and recommendations for micro-strain engineering to address the Li/SSEs interfacial issues are given. Additionally, work directions are pointed out with the consideration of combining multi-techniques for “poly-therapy”.

36 MATERIALS SCIENCE↗

Conical Intersection Accessibility Dictates Brightness in Red Fluorescent Proteins

Red fluorescent protein (RFP) variants are highly sought after for in-vivo imaging since longer wavelengths improve depth and contrast in fluorescence imaging. However, the lower energy emission wavelength usually correlates with a lower fluorescent quantum yield compared to their green emitting counterparts. To guide the rational design of bright variants, we have theoretically assessed two variants (mScarlet and mRouge) which are reported to have very different brightness. Using an α-CASSCF QM/MM framework (chromophore and all protein residues within 6 Å of it in the QM region, for a total of more than 450 QM atoms), we identify key points on the ground and first excited state potential energy surfaces. The brighter variant mScarlet has a rigid scaffold, and the chromophore stays largely planar on the ground state. The dimmer variant mRouge shows more flexibility and can accommodate a pre-twisted chromophore conformation which provides easier access to conical intersections. Notably, the main difference between the variants lies in the intersection seam regions, which appear largely inaccessible in mScarlet but partially accessible in mRouge. This observation is mainly related with changes in the cavity charge distribution, the hydrogen-bonding network involving the chromophore and a key ARG/THR mutation (which changes both charge and steric hindrance).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Beam-induced backgrounds measured in the ATLAS detector during local gas injection into the LHC beam vacuum

Inelastic beam-gas collisions at the Large Hadron Collider (LHC), within a few hundred metres of the ATLAS experiment, are known to give the dominant contribution to beam backgrounds. These are monitored by ATLAS with a dedicated Beam Conditions Monitor (BCM) and with the rate of fake jets in the calorimeters. These two methods are complementary since the BCM probes backgrounds just around the beam pipe while fake jets are observed at radii of up to several metres. In order to quantify the correlation between the residual gas density in the LHC beam vacuum and the experimental backgrounds recorded by ATLAS, several dedicated tests were performed during LHC Run 2. Local pressure bumps, with a gas density several orders of magnitude higher than during normal operation, were introduced at different locations. The changes of beam-related backgrounds, seen in ATLAS, are correlated with the local pressure variation. In addition the rates of beam-gas events are estimated from the pressure measurements and pressure bump profiles obtained from calculations. Using these rates, the efficiency of the ATLAS beam background monitors to detect beam-gas events is derived as a function of distance from the interaction point. These efficiencies and characteristic distributions of fake jets from the beam backgrounds are found to be in good agreement with results of beam-gas simulations performed with theFluka Monte Carlo programme.

43 PARTICLE ACCELERATORS↗

Massive red spiral galaxies in SDSS-IV MaNGA survey

ABSTRACT Massive red spiral galaxies (MRSGs) are supposed to be the possible progenitors of lenticular galaxies (S0s). We select a large sample of MRSGs ($M_*\gt 10^{10.5}\rm {\rm M}_{\odot }$) from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) DR17 using the g − r colour versus stellar mass diagram, along with control samples of blue spirals and S0s. Our main results are as follows: (1) After comparing the Sérsic index, concentration parameter, asymmetry parameter distribution, size–mass relation, and Σ1 (stellar mass surface density within the central 1 kpc)−mass relation, we find MRSGs are similar to S0s and have more compact and symmetric structures than blue spirals. MRSGs also resemble S0s in Dn4000, metallicity, Mgb/$\rm \left\langle Fe \right\rangle$, and V/σ radial profile. (2) By using MaNGA 2D spectra data, we separate the spatial regions into inner (R < 0.8Re) and outer (0.8 < R < 1.5Re) regions, and detect residual star formation in the outer regions of MRSGs. (3) When we select a sub-sample of MRSGs with NUV − r > 5, we find that they are completely star formation quenched in both inner and outer regions. Compared to optically selected MRSGs, NUV − r selected MRSGs appear to be more concentrated and have more massive dark matter haloes. The similarities between S0s and MRSGs suggest the possible evolutionary trend between MRSGs and S0s.

Astronomy & Astrophysics↗

Role of mechanical stress localizations on the radiation hardness of AlGaN/GaN high electron mobility transistors

Multi-material, multi-layered systems such as AlGaN/GaN high electron mobility transistors (HEMTs) contain residual mechanical stresses that arise from sharp contrasts in device geometry and materials parameters. These stresses, which can be either tensile or compressive, are difficult to detect and eliminate because of their highly localized nature. We propose that their high-stored internal energy makes potential sites for defect nucleation sites under radiation, particularly if their locations coincide with the electrically sensitive regions of a transistor. In this study, we validate this hypothesis with molecular dynamic simulation and experiments exposing both pristine and annealed HEMTS to 2.8 MeV Au +3 irradiation. Our unique annealing process uses mechanical momentum of electrons, also known as the electron wind force (EWF) to mitigate the residual stress at room temperature. High-resolution transmission electron microscopy and cathodoluminescence spectra reveal the reduction of point defects and dislocations near the two-dimensional electron gas region of EWF-treated devices compared to pristine devices. The EWF-treated HEMTs showed relatively higher resilience with approximately 10% less degradation of drain saturation current and ON-resistance and 5% less degradation of peak transconductance. Both mobility and carrier concentration of the EWF-treated devices were less impacted compared to the pristine devices. Our results suggest that the lower density of nanoscale stress localization contributed to the improved radiation tolerance of the EWF-treated devices. Intriguingly, the EWF is found to modulate the defect distribution by moving the defects to electrically less sensitive regions in the form of dislocation networks, which act as sinks for the radiation induced defects and this assisted faster dynamic annealing.

AlGaN/GaN HEMTs↗

Mechanism of mixed-linkage glucan biosynthesis by barley cellulose synthase–like CslF6 (1,3;1,4)-β-glucan synthase

Mixed-linkage (1,3;1,4)-β-glucans, which are widely distributed in cell walls of the grasses, are linear glucose polymers containing predominantly (1,4)-β-linked glucosyl units interspersed with single (1,3)-β-linked glucosyl units. Their distribution in cereal grains and unique structures are important determinants of dietary fibers that are beneficial to human health. We demonstrate that the barley cellulose synthase-like CslF6 enzyme is sufficient to synthesize a high–molecular weight (1,3;1,4)-β-glucan in vitro. Biochemical and cryo–electron microscopy analyses suggest that CslF6 functions as a monomer. A conserved “switch motif” at the entrance of the enzyme’s transmembrane channel is critical to generate (1,3)-linkages. There, a single-point mutation markedly reduces (1,3)-linkage formation, resulting in the synthesis of cellulosic polysaccharides. Our results suggest that CslF6 monitors the orientation of the nascent polysaccharide’s second or third glucosyl unit. Register-dependent interactions with these glucosyl residues reposition the polymer’s terminal glucosyl unit to form either a (1,3)- or (1,4)-β-linkage.

59 BASIC BIOLOGICAL SCIENCES↗

Incremental Fermi Large Area Telescope Fourth Source Catalog

We present an incremental version (4FGL-DR3, for Data Release 3) of the fourth Fermi Large Area Telescope (LAT) catalog of γ-ray sources. Based on the first 12 years of science data in the energy range from 50 MeV to 1 TeV, it contains 6658 sources. The analysis improves on that used for the 4FGL catalog over eight years of data: more sources are fit with curved spectra, we introduce a more robust spectral parameterization for pulsars, and we extend the spectral points to 1 TeV. The spectral parameters, spectral energy distributions, and associations are updated for all sources. Light curves are rebuilt for all sources with 1 yr intervals (not 2 month intervals). Among the 5064 original 4FGL sources, 16 were deleted, 112 are formally below the detection threshold over 12 yr (but are kept in the list), while 74 are newly associated, 10 have an improved association, and seven associations were withdrawn. Pulsars are split explicitly between young and millisecond pulsars. Pulsars and binaries newly detected in LAT sources, as well as more than 100 newly classified blazars, are reported. We add three extended sources and 1607 new point sources, mostly just above the detection threshold, among which eight are considered identified, and 699 have a plausible counterpart at other wavelengths. We discuss the degree-scale residuals to the global sky model and clusters of soft unassociated point sources close to the Galactic plane, which are possibly related to limitations of the interstellar emission model and missing extended sources.

79 ASTRONOMY AND ASTROPHYSICS↗

ResNet and CycleGAN for pulse shape discrimination of He-4 detector pulses: Recovering pulses conventional algorithms fail to label unanimously

Pulse shape discrimination (PSD) capable detectors, such as He-4, that respond to neutron and gamma-ray 7 interactions have a threshold deposited energy value below which n/γ discrimination vanishes when using 8 conventional PSD algorithms. Recent attempts in applying supervised learning based artificial neural 9 networks for PSD use the pulses in the separated regions to train the networks so they can be used to classify 10 another set of separated pulses. In doing so, pulses previously indistinguishable are not recovered for 11 classification, which would have increased the number of neutron and gamma-ray pulses that could be used 12 for further analysis. Assuming the reason why conventional PSD algorithms have unseparated regions is 13 because the parameter space of the algorithms fail to capture the intrinsic (but subtle) distinguishing 14 behavior of some of the neutron and gamma-ray pulses, a cycle-consistent generative adversarial network 15 (CycleGAN) was trained to amplify those differences and extract well separated neutron and gamma-ray 16 clusters. Results show that, once the network is trained with pulses from separated and unseparated regions, 17 it was able to transform the pulses in the unseparated region to improve the PSD. Subsequent n/γ 18 classification was performed using deep residual network (ResNet) that takes pulses with 512 data points 19 as an input. Two different ResNets were explored – simple ResNet and modified ResNet which takes 20 segmented pulse inputs in the first layer and the corresponding time axis values in the last hidden layer. 21 The later approach enables the network to extract time correlated pulse features to enhance its ability to 22 capture the pulse behaviors relevant for PSD. Although it achieves slightly lower accuracy, 99.41% versus 23 99.89%, based on simply counting the number of correct n/γ labels assigned, compared to the simple 24 ResNet, the modified ResNets architecture was able to decreases the cross-entropy loss function by half, 25 which implies that the correct n/γ labels assigned are less likely to be accidental. PSD parameter 26 distributions based on n/γ classification by ResNet before and after transforming unseparated pulses using 27 CycleGAN show that by enhancing the separation between neutrons and gamma-rays, the transformation 28 helps improve the performance of classifier networks that are trained using labeled dataset. The 29 enhancement of neutron and gamma-ray separation by the CycleGAN increased the PSD figure of merit 30 (FOM) by up to 70% in some regions. Here, the results show that, if a given detector achieves clear separation 31 between neutron and gamma-ray pulses in any energy region, such neural network approaches can help 32 lower the energy threshold for the separation and increasing the number of neutron and gamma-ray pulses 33 that can be used for further analysis.

4He↗

DAmodel: hierarchical Bayesian modelling of DA white dwarfs for spectrophotometric calibration

We use hierarchical Bayesian modelling to calibrate a network of 32 all-sky faint DA white dwarf (DA WD) spectrophotometric standards (⁠16.5 < V , 19.5⁠) alongside three CALSPEC standards, from 912 Å to 32 μm. The framework is the first of its kind to jointly infer photometric zero points and WD parameters (surface gravity log g⁠, effective temperature T eff ⁠, extinction A V ⁠, dust relation parameter R V ) by simultaneously modelling both photometric and spectroscopic data. We model panchromatic Hubble Space Telescope Wide Field Camera 3 (HST/WFC3) UVIS and IR photometry, HST/STIS UV spectroscopy, and ground-based optical spectroscopy to sub-per cent precision. Photometric residuals for the sample are the lowest yet yielding < 0.004 mag RMS on average from the UV to the NIR, achieved by jointly inferring time-dependent changes in system sensitivity and WFC3/IR count-rate nonlinearity. Our GPU-accelerated implementation enables efficient sampling via Hamiltonian Monte Carlo, critical for exploring the high-dimensional posterior space. The hierarchical nature of the model enables population analysis of intrinsic WD and dust parameters. Inferred spectral energy distributions from this model will be essential for calibrating the James Webb Space Telescope as well as next-generation surveys, including Vera Rubin Observatory’s Legacy Survey of Space and Time and the Nancy Grace Roman Space Telescope.

methods: statistical↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗