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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2026

Update on Radiochemical Assessment of High Burnup Commercially Irradiated Fuel

This work documents an effort to collect burnup measurements on a high burnup rod, designated 6XV, and first cycle accident tolerant fuel (ATF) rod, designated 47I, to enable benchmarking of fuel performance codes and neutronics codes. In addition to measurements, Virtual Environment for Reactor Applications (VERA) full-core-depletion analysis was also performed for the rods that were experimentally analyzed to provide an opportunity for code validation. This effort focuses on collecting data from rods irradiated at Byron Generating Station and shipped to the Oak Ridge National Laboratory (ORNL) hot-cells. This data will also anchor non-destructive examination evaluations of burnup of the various fuel rods undergoing postirradiation examination (PIE) at ORNL. Previous PIE of these fuel rods provides some guidance on the burnup trend across the fuel. Axial gamma spectroscopy scans provide a measure of relative changes in burnup across a fuel pin. Mass spectrometry based burnup measurements performed for this work at specific axial locations in the fuel are fully quantitative. By combining the mass spectrometry data with the gamma scans it is possible to more quantitatively evaluate axial variations in burnup across the entire fuel pin [1]. The combined set of burnup evaluations will be made available to other organizations that have an interest in high burnup radiochemistry data for validation of neutronic simulations and source term evaluation such as the Nuclear Regulatory Commission (NRC).

Harp, Jason [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2027

A multi-region approach for the analysis of porous materials and gas-solid reactions using USAXS-SAXS-WAXS: application to CaO carbonation

The reaction rate of gas-solid non-catalytic reactions is typically investigated using reactant conversion data over time and ex-situ measurements of the porous solid reactant textural properties; these data enable the experimental estimation of the initial intrinsic reaction rate, whereas the evolution of the textural properties and the reaction rate over time are evaluated theoretically using reaction models. In this work, a different methodology is presented, based on: a) in-situ time-resolved USAXS-SAXS-WAXS measurements of the solid sample, and b) a multi-region modeling approach; this methodology allows for the estimation of the textural properties and the intrinsic reaction rate at any time during the reaction. Referring to a reaction in which a solid product is obtained from a solid reactant and a gaseous reactant, the porous particle is described as consisting of several distinct regions with different microstructural properties, and both a gas-solid reaction model and a SAXS model are derived and applied to the carbonation of porous CaO. The proposed reaction model highlights the role of the inaccessible reactant and accurately predicts the solid reactant conversion versus time profile. The SAXS model accurately predicts the measured linear trends of the Porod invariant and of the pre-factor of the power law scattering profile versus CaO mass fraction; in the absence of chemical reactions, the proposed equations extend classical SAXS theory to porous materials containing macropores and nonporous solid phases in addition to standard nanoscale inhomogeneous regions.

CO2 solid sorbents↗
DOE OSTI2026

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗
DOE OSTI2026

Improving Marine Energy Production Through Commercialization of a Low Cost, Drag-Reducing Slippery Coating (CRADA 679 Abstract)

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and we have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing well over 50% cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the government-sponsored two-year program is complete. The main technical goal is to design, manufacture, and experimentally validate a new coating that can reduce hydrodynamic skin friction drag by 20%. The main commercialization goal is to develop a roadmap that identifies activities needed to complete SLIDE-Coat’s development after the conclusion of this project. Year 1 will focus on adaptation and modification of the existing SLIC coating system to optimize drag reduction and assessment and quantification of drag reduction on relevant materials in a laboratory setting. Year 2 will focus on optimizing and demonstrating drag reduction with preferred coatings. The manufacturability, ease of application, adhesion to relevant surfaces, and consistency will be assessed. Quantification of drag reduction on prototype materials in a relevant marine field setting will be executed.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine-learning interatomic potentials

Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (δ-phase) during electrochemical cycling. Here, in this computational study, we use charge-informed molecular dynamics with a fine-tuned CHGNet foundation potential to investigate the phase transformation in LixMn 0.8 Ti 0.1 O 1.9 F 0.1 . Our results indicate that transition metal migration occurs and reorders to form the spinel-like ordering in an FCC anion framework. The transformed structure contains a higher concentration of nontransition metal (0-TM) face-sharing channels, which are known to improve Li transport kinetics. Analysis of the Mn valence distribution suggests that the appearance of tetrahedral Mn 2+ is a consequence of spinel-like ordering, rather than the trigger for cation migration as previously suggested. Calculated equilibrium intercalation voltage profiles demonstrate that the δ-phase, unlike the ordered spinel, exhibits solid-solution signatures at low voltage. A higher Li capacity is obtained than in the DRX phase. This study provides atomic insights into solid-state phase transformation and its relation to experimental electrochemistry, highlighting the potential of machine-learning interatomic potentials for understanding complex oxide materials.

Zhong, Peichen [University of California, Berkeley↗
DOE OSTI2025

Chromium versus Aluminum: Impact of Nickel Alloy Composition and Interfacial Kinetics on High-Temperature Passivating Oxide Formation

High-temperature corrosion resistance depends critically on the formation of a passivating surface oxide, which is highly sensitive to alloy composition and structure. Such details often elude experimental investigation, and simplified analytical models fail to provide a truly chemical view of passivating oxide evolution. Here, we explicitly compare the fundamental chemistry of Cr and Al as prototypical passivating elements in Ni alloys by directly simulating competing reaction and diffusion processes within the oxide film using kinetic Monte Carlo and density functional theory. We find that the origin and expression of passivating behavior during early-stage thermal oxidation are qualitatively different between the two alloy systems. Ni–Cr alloys feature a sudden onset of passivation associated with a sharp phase transition upon Cr enrichment that directly couples oxidation kinetics to phase transformation behavior. In contrast, Ni–Al alloys display more continuous oxide phase variation with Al enrichment, ultimately resulting in a lower composition threshold for passivation and a thinner passivating layer. In addition, we elucidate the nonobvious role of metal exchange within the alloy near the oxide boundary, which fundamentally alters film composition and passivating behavior. Furthermore, our results have key implications for engineering improved corrosion-resistant alloys, both in terms of compositional variation and processing.

Alloys↗
DOE OSTI2026

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul [National Renewable Energy Lab. (NREL↗
DOE OSTI2023

Constraints on Nuclear Symmetry Energy Parameters

A review is made of constraints on the nuclear symmetry energy parameters arising from nuclear binding energy measurements, theoretical chiral effective field predictions of neutron matter properties, the unitary gas conjecture, and measurements of neutron skin thicknesses and dipole polarizabilities. While most studies have been confined to the parameters 𝑆 𝑉 and L, the important roles played by, and constraints on 𝐾 sym , or, equivalently, the neutron matter incompressibility 𝐾 𝑁 , are discussed. Strong correlations among 𝑆 𝑉 ,𝐿, and 𝐾 𝑁 are found from both nuclear binding energies and neutron matter theory. However, these correlations somewhat differ in the two cases, and those from neutron matter theory have smaller uncertainties. To 68% confidence, it is found from neutron matter theory that 𝑆 𝑉 = 32.0 ± 1.1 MeV, 𝐿 = 51.9 ± 7.9 MeV and 𝐾 𝑁 = 152.2 ± 38.1 MeV. Theoretical predictions for neutron skin thickness and dipole polarizability measurements of the neutron-rich nuclei 48 Ca, 120 Sn, and 208 Pb are compared to recent experimental measurements, most notably the CREX and PREX neutron skin experiments from Jefferson Laboratory. By themselves, PREX I+II measurements of 208 Pb and CREX measurement of 48 Ca suggest 𝐿 = 121 ± 47 MeV and 𝐿 = −5 ± 40 MeV, respectively, to 68% confidence. However, we show that nuclear interactions optimally satisfying both measurements imply 𝐿 = 53 ± 13 MeV, nearly the range suggested by either nuclear mass measurements or neutron matter theory, and is also consistent with nuclear dipole polarizability measurements. This small parameter range implies 𝑅 1.4 = 11.6 ± 1.0 km and Λ 1.4 = 228$^{+148}_{−90}$, which are consistent with NICER X-ray and LIGO/Virgo gravitational wave observations of neutron stars.

neutron skins↗
DOE OSTI2026

Self-Healing Lithium Dendrites through Spontaneous Passivating Layer Formation for Stable Solid-State Lithium–Metal Batteries

All-solid-state lithium–metal batteries have attracted significant attention, owing to their high energy density and superior safety. However, lithium–metal penetration through the solid electrolyte, leading to short-circuiting, remains a critical failure mode that demands comprehensive mitigation strategies. Most existing strategies are effective only prior to the initiation of lithium-dendrite formation and fail once dendrites begin to propagate through the electrolyte. In this study, we propose a self-healing mechanism in which the penetrated lithium reacts with a self-healing agent to form a passivating layer along the particle boundaries. Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) was incorporated into a Li 6 PS 5 Cl solid electrolyte as the self-healing agent to suppress lithium-dendrite propagation even after dendrite formation initiated under high current densities. The self-healing induced by LiTFSI was verified through comprehensive experimental analyses and was further demonstrated in a full-cell configuration. Moreover, LiTFSI incorporation plays an important role in increasing the critical current density by reducing the overall electronic conductivity of the solid electrolyte and facilitating the formation of a robust LiF-containing solid-electrolyte interphase.

25 ENERGY STORAGE↗
DOE OSTI2025

Field-tunable BKT and quantum phase transitions in spin-$\frac{1}{2}$ triangular lattice antiferromagnet

Quantum magnetism is one of the most active fields for exploring exotic phases and phase transitions. The recently synthesized Na 2 BaCo(PO 4 ) 2 (NBCP) is an ideal material incarnation of the spin-$\frac{1}{2}$ easy-axis triangular lattice antiferromagnet (TLAF). Experimental evidence shows that NBCP hosts the spin supersolid state with a giant magnetocaloric effect. Theory further predicts that magnetic fields can drive NBCP through Berezinskii-Kosterlitz-Thouless (BKT) and other richer quantum phase transitions. However, detecting these transitions is challenging, as they onset at ultralow temperatures near 60 mK and require high magnetization sensitivity. Using a newly developed gradient force magnetometer in a dilution refrigerator, we mapped the magnetic susceptibility phase diagram down to 30 mK. Our results provide a more comprehensive and accurate understanding of BKT melting of spin supersolidity and several field-tunable quantum phase transitions, which establish NBCP as a model platform for frustrated magnetism and highlight potential applications of its giant magnetocaloric effects.

BKT transition↗
DOE OSTI2025

Preliminary Evaluation of Joint Electricity-Hydrogen Concept of Operations

An initial thermal power dispatch (TPD) concept of operations was evaluated that couples a nuclear power plant to a nearby hydrogen production plant. GSE Systems’ generic pressurized water reactor full-scope simulator was modified with a TPD model comprised of a thermal power extraction and delivery system. A prototype human-system interface (HSI) was developed to interact with the TPD model and allow participants to execute the basic operating scenarios for normal operations. Four retired operators performed the evaluation, and due to COVID-19 travel restrictions, the original in-person experimental design was restructured to support a remote participator evaluation using a web meeting platform. Data from operator feedback, observations from the research team, and quantitative survey responses revealed that the initial TPD concept of operations is feasible. The operators were comfortable with the engineered system and HSI and could manage it without adverse impacts to reactor power, plant safety, or equipment. Findings are discussed in terms of both the TPD system design and HSI performance.

human factors↗
DOE OSTI2023

CFD Simulation of the Dosing Behavior within the Atomic Layer Deposition Feeding System

The effective operation of atomic layer deposition (ALD) feeding system is the premise of realizing specific ALD processes. In the present work, a detailed computational fluid dynamics (CFD) model of the feeding system has been developed and validated, which accounts for the roles of ALD valves and manifolds. A numerical simulation of the compressible fluid flow and heat/mass transfer within the feeding system was conducted. The dosing amounts and the spatiotemporal distributions of the precursors can be accurately predicted using the CFD model, as validated by experimental results. Different precursors, operating conditions, and structures of the feeding system were simulated and analyzed to examine the operating flexibility of the feeding system. The simulation results can be adopted as the upstream boundary conditions for simulations of the ALD process in the reaction chamber. The substrate-scale simulation indicates that the effect of the feeding system on the film deposition is highly related to the surface kinetics of ALD. The present work can serve as a guide for the development and optimization of different ALD-based processes via proper operation and even the design of the feeding system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Uncovering the linear boron environment in Na 3 BP 2 through solid-state 11 B NMR spectroscopy

Boron-based compounds exhibit a wide range of structural diversity, with potential applications spanning organic and inorganic chemistry. Herein, we focus on the characterization of the linear boron-phosphorus unit P═B═P in Na 3 BP 2 using solid-state nuclear magnetic resonance (ssNMR) spectroscopy and density functional theory (DFT) calculations. High-resolution 11 B ssNMR spectra were recorded at two fields, and key parameters such as chemical shift anisotropy (CSA), quadrupolar coupling constants (C Q ), and electric field gradient (EFG) tensors were extracted. The 11 B NMR results revealed a distinct chemical environment for the two-coordinate boron atom, with a CSA span (Ω) of 280 ppm and a C Q of 3.0 MHz. These values were further validated through periodic plane-wave DFT calculations, which showed good agreement with experimental results. The obtained spectral parameters are compared to other linear boron units, such as the BO 2 motif, providing a broader context for understanding boron coordination in inorganic compounds. This work expands the body of NMR knowledge on boron-containing materials, particularly for linear boron motifs. The findings contribute to the growing field of boron chemistry and its potential applications in advanced materials.

Porter, Andrew P. [Ames Laboratory (AMES), Ames, I↗
DOE OSTI2026

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen↗
DOE OSTI2025

Grain boundary segregation and chemical ordering in CoCrFeMnNi multi-principal element alloy

Owing to their far-from-dilute compositions, multi-principal element alloys (MPEAs) can exhibit unique combinations of engineering properties. As nearly all MPEAs are polycrystalline aggregates, it is necessary to understand the interactions of various elemental species with grain boundaries (GBs). This is of particular importance in extreme environments, such as radiation and elevated temperatures, where such interactions have implications on the properties of MPEAs. Herein, we employ atomistic simulations to generate a series of [001] asymmetric tilt GBs in a model CoCrFeMnNi MPEA and quantify solute interactions and segregation to these boundaries. We employ the Warren-Cowley order parameters to investigate the interplay between GB segregation and chemical short-range order (SRO). At temperatures above 800 K, simulation results reveal the segregation of Cr and Mn to CoCrFeMnNi GBs and show weak dependence of boundary solute excess on GB geometry, at least for the boundaries explored in this work. At temperatures in the range of 673–800 K, formation of domains rich in Cr is observed at GBs in agreement with experimental observations. Quantitative analysis shows that solute excess of various alloying elements decreases rapidly with the increase in temperature in the range of 1000–1200 K. Furthermore, we show that GB regions exhibit SRO characteristics that are distinct from the bulk crystals, leading to spatial variations in SRO. In broad terms, our study highlights the need to account for GB interactions with alloying elements when designing advanced MPEAs with novel chemistries.

Wang, Yitao [Lehigh University, Bethlehem, PA (Uni↗