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DOE OSTI2024

Revenue Analysis for Energy Storage Systems in the United States

In this work we evaluate the potential revenue from energy storage using historical electricity prices, forward-looking projections of hourly electricity prices, and actual reported revenue. This analysis examines the impact of storage characteristics, specifically duration and round-trip efficiency, as well as locational elements of storage revenue within the current and projected U.S. power system. Figure ES-1 illustrates the revenue for a 1 MW storage system in seven market regions with durations range from 1 hour to 12 hours using both historical and forward-looking price data. The historical analysis covers more than 500 price nodes for each market region, while the forward-looking analysis includes balancing areas under different 10 scenarios of the electricity generation mix. The results indicate that the revenues consistently increase with duration, though the marginal value declines as duration grows. Moreover, the range of revenue depends on the system's operational location, and the electricity generation mix changes for future years. This range also widens with increased durations. In addition, the sensitivity analysis of round-trip efficiency reveals that as efficiency improves, system revenue increases, though the value of better round-trip efficiency declines as at higher efficiency levels.

25 ENERGY STORAGE↗

DOE OSTI2022

Frictional properties of Opalinus Clay: influence of humidity, normal stress and grain size on frictional stability

SUMMARY The Opalinus Clay (OPA) is a clay-rich formation considered as a potential host rock for radioactive waste repositories and as a caprock for carbon storage in Switzerland. Its very low permeability (10−19 to 10−21 m2) makes it a potential sealing horizon, however the presence of faults that may be activated during the lifetime of a repository project can compromise the long-term hydrological confinement, and lead to mechanical instability. Here, we have performed laboratory experiments to test the effect of relative humidity (RH), grain size (g.s.) and normal stress on rate-and-state frictional properties and stability of fault laboratory analogues corresponding to powders of OPA shaly facies. The sifted host rock powders at different grain size fractions (<63 μm and 63 < g.s. < 125 μm), at room (∼25 per cent) and 100 per cent humidity, were slid in double-direct shear configuration, under different normal stresses (5–70 MPa). We observe that peak friction, μpeak and steady-state friction, μss, depend on water vapour content and applied normal stress. Increasing relative humidity from ∼25 per cent RH (room humidity) to 100 per cent RH causes a decrease of frictional coefficient from 0.41 to 0.35. The analysis of velocity-steps in the light of rate-and-state friction framework shows that the stability parameter (a–b) is always positive (velocity-strengthening), and it increases with increasing sliding velocity and humidity. The dependence of (a–b) on slip rate is lost as normal stress increases, for each humidity condition. By monitoring the variations of the layer thickness during the velocity steps, we observe that dilation (Δh) is directly proportional to the sliding velocity, decreases with normal stress and is unaffected by humidity. Microstructural analysis shows that most of the deformation is accommodated within B-shear zones, and the increase of normal stress (σn) promotes the transition from strain localization and grain size reduction to distributed deformation on a well-developed phyllosilicate network. These results suggest that: (1) the progressive loss of velocity dependence of frictional stability parameter (a–b) at σn > 35 MPa is dictated by a transition from localized to distributed deformation and (2) water vapour content does not affect the deformation mechanisms and dilation, whereas it decreases steady-state friction (μss), and enhances fault stability.

58 GEOSCIENCES↗

DOE OSTI2023

Weak trimerization in the frustrated two-dimensional triangular Heisenberg antiferromagnet Lu y Y 1-y MnO 3

To understand the 2D triangular Heisenberg antiferromagnetic system, we investigated the magnetic structures and the dynamics of Lu y Y 1-y MnO 3 in detail. The substitutions are adjusted to the Mn atomic position close to x Mn =$\frac{1}{3}$. The neutron powder diffraction data claims that the magnetic structure of Lu y Y 1-y MnO 3 is described as a mixture of Γ 3 (P6' 3 cm') and Γ 4 (P6' 3 c'm) at the x Mn position for y=0.15, 0.30, and 0.45. The ratio of Γ 3 and Γ 4 depends on temperature and composition and the fraction of Γ 3 increases upon cooling, while no clear trimerization was observed at the xMn position. We estimated exchange parameters from the analysis of the low-energy part of the spin waves. The results showed a weak trimerization effect on cooling because the nearest-neighbor exchange interaction is slightly enhanced. The temperature dependence of the spin-wave dispersion around the Γ point shows that the spin gap closes with increasing temperature because the exchange interactions in the nearest Mn-Mn neighbor become smaller. Gapless diffusive magnetic excitation from a Mn triangular lattice has been observed in a wide range in Q and E space of Lu y Y 1-y MnO 3 . We found that Lu 0.3 Y 0.7 MnO 3 could be an ideal case to investigate the trimerization, frustrated magnetism, and magnetoelastic coupling often observed in two-dimensional triangular lattice Heisenberg antiferromagnet systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

The energy saving potential of thermo-responsive desiccants for air dehumidification

The desiccant wheel is a promising technology for energy-efficient humidity control. However, its overall efficiency—hindered by the desiccant materials’ properties—remains low because traditional desiccants (e.g., silica gels) have a single isotherm regardless of their adsorption temperature. Thermo-responsive materials have been proposed to break this fixed affinity to water vapor, with drastically different adsorption isotherms depending on temperature. Its potential for improving dehumidification efficiency, however, has not been addressed. In this paper, we model the potential of a thermo-responsive interpenetrating polymer network (IPN) desiccant with temperature-dependent adsorption isotherms for energy-efficient dehumidification via a validated transient desiccant wheel model for humidity control of buildings. Thermo-responsive desiccants can improve the dehumidification performance due to their thermo-responsive switchable hydrophilicity below/above the lower critical solution temperature. Our analysis shows that thermo-responsive IPN desiccants can potentially reduce energy consumption by up to 30% compared to silica gels. Finally, the savings depend strongly on the critical temperature of the thermo-responsive desiccant and should be higher when the inlet temperatures are expected to be higher.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Climate-Relevant Gas Absorption Properties from AWARE and Other ARM Spectral Measurements (Final Report)

The objective of this project has been to use measurements from the Atmospheric Emitted Radiance Interferometer (AERI) deployed at ARM sites to improve our knowledge of uncertain infrared spectroscopic parameters of importance to climate, remote sensing, and data assimilation. A primary focus has been the water vapor continuum in the infrared atmospheric window. Radiation codes used to predict climate and weather base their representation of the water vapor continuum in this window on the MT_CKD model, but in this spectral region the MT_CKD water vapor continuum absorption coefficients were derived almost two decades ago by an analysis of AERI measurements for conditions with a limited range of precipitable water vapor (PWV) and temperature values, leading to uncertainty in the derived coefficients. This project has included a new, comprehensive analysis of all aspects of the water vapor continuum in the atmospheric window -- the self continuum, the foreign continuum, and the self continuum temperature dependence, all resolved spectrally. Having a wide range of PWV amounts and temperatures from deployments of the ARM Mobile Facility for GoAmazon as well as the more than a decade of AERI measurements at SGP has provided an appropriate foundation for such a comprehensive analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Computational assessment of smooth and rough parameter dependence of statistics in chaotic dynamical systems

An assumption of smooth response to small parameter changes, of statistics or long-time averages of a chaotic system, is generally made in the field of sensitivity analysis, and the parametric derivatives of statistical quantities are critically used in science and engineering. In this paper, we propose a numerical procedure to assess the differentiability of statistics with respect to parameters in chaotic systems. Here, we numerically show that the existence of the derivative depends on the Lebesgue integrability of a certain density gradient function, which we define as the derivative of logarithmic SRB density along the unstable manifold. We develop a recursive formula for the density gradient that can be efficiently computed along trajectories, and demonstrate its use in determining the differentiability of statistics. Our numerical procedure is illustrated on low-dimensional chaotic systems whose statistics exhibit both smooth and rough regions in parameter space.

42 ENGINEERING↗

DOE OSTI2026

Validating a Dynamic PWR Safety and Security Model?

Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2020

Current-driven transverse domain wall oscillations in perpendicular spin-valve structures

Spin-transfer-driven oscillations of a transverse domain wall confined to a perpendicular spin-valve structure are investigated using a one-dimensional model. The stack consists of a polarizer, nonmagnetic spacer, soft free layer, and pinned magnetic layer. It is found that the domain-wall oscillation frequency is a nonmonotonic, highly asymmetrical function of applied electric current, showing a strong dependence on the current direction and the relative strengths of the interfacial and bulk spin-transfer torques. Micromagnetic analysis reveals that the surprising and atypical oscillator response is due to an interplay between the interfacial spin-transfer torque, the bulk spin-transfer torque, the exchange torque, and the damping torque. The underlying physical and material responses are examined, including the important role of the domain-wall twist. The competitions between the involved torques under different operating conditions suggest that the oscillator could serve as a model system to investigate magnetic and spintronic phenomena at the nanoscale. Finally, the observed current-dependent twisting of the free-layer magnetization about the axis of precession may further be found interesting for investigations of the interaction between spin-polarized current and chiral spin structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Computationally inexpensive part-scale thermal history of additive friction-stir deposition

This study presents an analytical model for steady-state power generation and tool heat loss in additive friction-stir deposition (AFSD), developed to enable part-scale thermal simulation while remaining computationally inexpensive. The model predicts total generated power, yielding 3.7–4.7 kW across deposition temperature setpoints of 400–460 °C for the deposition of AA6061 with a Be-Cu tool. This corresponds to 90–95% of the reported spindle power. Tool heat loss is experimentally determined by calibrating a steady-state energy balance between the generated power, the substrate-deposition thermal gradient, and a temperature dependent tool heat loss term: q tool (T) = a + b (T - 400°C) with a = 2.7 x 10 6 Wm -2 and b = 9.5 x 10 3 Wm -2 K -1 . The calibration indicates that about 69% of the generated heat is conducted into the tool for this configuration, which is much higher than previously reported. The calibrated heat-source is implemented in finite element software (Adamantine) to simulate the transient thermal history of a 100 cm 3 representative build in 8 min on a standard desktop (at 0.635 mm build-height resolution). For the first three layers, the substrate temperatures between simulation and experiment are within 10% mean absolute percentage error. Sensitivity analysis indicates that uncertainties in average deposition temperature and deformation localization (stir-zone geometry, depth, and spatial dependance of strain-rate and flow stress) dominate model variance, motivating additional experimental verification.

Additive Friction-Stir Deposition↗

DOE OSTI2020

Techno-Economic Analysis and Global Warming Potential of a Novel Offshore Macroalgae Biorefinery

The success of a large scale macroalgae-based biorefinery is dependent on the demonstration of favorable system economics and environmental sustainability. This study uses detailed process modeling to quantify the mass and energy flows through the various unit operations required for a novel free-floating macroalgae biorefinery concept. The modular process model served as the foundation for the techno-economic and global warming potential analyses used to quantify the sustainability of the proposed concept. This work includes detailed techno-economic results for a complete macroalgae cultivation and conversion system with multiple hatchery configurations and several emerging technologies. System optimization was achieved through the evaluation of various technology options for each unit operation. Technologies considered include traditional twine and textile substrate hatchery configurations, drone assisted seeding and biomass transport, mechanized line seeding and harvesting, adhesive spore mixtures that simplify seeding operations and improve hatchery energetics, and hydrothermal liquefaction to produce upgradable biocrude. Outputs from the system include renewable diesel (R100), naphtha, biochar, nitrogen and phosphorus fertilizers, and aqueous/solid waste streams. Three different system pathways were explored, yielding a biomass production cost ranging from $210 to $565 per dry metric ton and a minimum fuel selling price from $1.35 to $2.91 per liter of gasoline equivalent. Stochastic manipulation of the process model and sensitivity analyses support these results. The global warming potential analysis shows net greenhouse gas emissions ranging from 14 to 29 gCO2-eq MJ-1, supported by stochastic and sensitivity analyses. The recommendations from this work highlight critical areas for research and development investment such that a sustainable macroalgae cultivation and conversion system can be realized.

NOMAD seaweed cultivation, techno-economic analysi↗

DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Neutronics Analysis of Heating and DPA of the Proton Beam Window and Core Vessel Nozzle Neutronics Heating Analysis for the Second Target Station

This reports details the analysis of the heating rates, dpa values and He production in the Proton Beam Window (PBW) assembly and the Core Vessel (CV) nozzle for the preliminary design for the Second Target Station (STS). This analysis focuses on the heating rates in the cooled beltline component of the CV. Neutronics calculations use a detailed unstructured mesh (UM) converted from a CAD model in SpaceClaim of the PBW and CV design of February 2024. The rest of the geometry is taken from the STS master model in constructive solid geometry (CSG). Heating is evaluated for four beam profiles, which are chosen as the most likely to produce the highest heating in the beltline component. The maximum energy deposition values in the beltline are 0.02-0.08 J/cc/pulse, depending on the beam profile. Detailed point cloud data of the full UM geometry is made available for mechanical analysis. The maximum dpa rate in the beltline steel is approximately 0.02 dpa/year, which corresponds to a lifetime of 3,000 years. These results are in good agreement with previous results for the CV. For the PBW itself, maximal heating, dpa, and He production rates are very similar to the previous analysis.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

On the trapped magnetic moment in type-II superconductors

In this article, measurements of the trapped (remanent) magnetic moment, M trap (H) , when a small magnetic field H is turned off after cooling below the superconducting transition temperature, T c , or ramping a magnetic field up and down after cooling in a zero magnetic field, offer substantial advantages in difficult cases of small samples and large field-dependent backgrounds, which is relevant for hydrogen-based ultra-high-T c superconductors (UHTS). Until recently, there was no need for a separate paper on the trapped magnetic flux for well-known critical-state models due to the simplicity of the physics involved. However, recent publications showed the need for such an analysis. This note summarizes the expectations for the Bean model with constant critical current density and the Kim model with field-dependent critical currents. It is shown that if the trapped moment is fitted to the power law, M trap $\propto$ H a , the fixed exponent α = 2 is exact for the Bean model, while Kim models show a wide interval of possible values, 2$\leqslant$a$\leqslant$4. Furthermore, accounting for reversible magnetization expands the range of possible exponents to 1$\leqslant$a$\leqslant$4. In addition, demagnetizing factors are essential and make the trapped moment orientation dependent even in isotropic materials. As a concrete application, it is shown that flux trapping experiments performed on H 3 S UHTS compounds can be well described using this generalized approach, lending further support to the type-II superconducting nature of H 3 S under ultra-high pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗

DOE OSTI2024

Modeling delayed thermal runaway in nitric acid-soaked cat litter mixed with radioactive waste

Thermal ignition of radioactive waste within a 55-gallon drum was simulated by using a pressure-dependent waste decomposition model (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) calibrated with data from full-scale drum experiments (Parker et al. in The thermolytic response of a surrogate RNS waste mixture at the drum scale. Los Alamos National Laboratory Report LA-UR-16-21760, 2016) and validated with experiments from multiple laboratories (Hobbs et al. in Thermal analysis of aged nitric acid-soaked kitty litter in TRU waste drums-23370.WM2023 Conference, Phoenix, AZ, 2023). The acceleration of nitric acid chemistry reacting with an organic cat litter leading to thermal ignition was likely triggered by a restricted vent in the drum. Here, we address whether the form of the rate equation in (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) is sufficient to extrapolate thermal ignition within aged drums of similar content that have been stored in Texas for over nine years by investigating four different reaction rate forms for waste decomposition. A critical reaction rate reduction analysis is performed on each of these models to determine if delayed thermal runaway within vented aged waste is possible after nine years. We found that a pressure-dependent first-order rate expression not only predicted the accidental ignition of the waste drum, but the form also matches multiple experiments from different laboratories. Even though the waste composition decreases over time, the model predicts that acceleration leading to thermal runaway is possible if the waste is confined, even after 9 years. In conclusion, waste containing oxidizers such as nitric acid should not be mixed with organic adsorbents, especially if the waste is confined.

cookoff↗

DOE OSTI2026

Cross-family and phage-specific gene requirements for Klebsiella infection revealed by scalable RB-TnSeq genetic screens.

Bacteriophages are being cataloged at an accelerating pace and are recognized as key players in nutrient and energy cycling across ecosystems. Yet the bacterial genetic determinants that govern phage-host specificity and infection success remain poorly understood, particularly in clinically and ecologically important genera such as Klebsiella where prior receptor characterization has been almost entirely limited to capsulated strains. Here we used a randomly barcoded, genome-wide, loss-of-function transposon mutant library (RB-TnSeq) of Klebsiella sp. M5al, a naturally acapsular, nitrogen-fixing rhizobacterium, to generate the first systematic, cross-family map of phage receptor gene dependencies in Klebsiella. Challenging the library against 25 double-stranded DNA phages spanning five families in 213 parallel assays, we identified 42 bacterial genes associated with phage infection, of which 15 had no prior association with phage infection in any bacterial system. Disruption of surface receptor biosynthesis genes conferred cross-resistance across multiple phage families, while intracellular gene disruptions had predominantly phage-specific effects. Clonal validation of eight genes confirmed LPS outer core biosynthesis genes as primary receptor determinants alongside additional host factors spanning outer membrane transport, cofactor biosynthesis, and two-component signaling. Comparative analysis across all 25 phages revealed that phage genus rather than family is the stronger predictor of host gene dependency profiles, a finding with direct implications for the functional annotation of uncharacterized phage isolates and rational phage cocktail design. Together, these findings provide a community resource for linking phage genomic diversity to functional host interaction space in this ecologically and clinically important genus.

Gittrich, Marissa R↗