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Hilary Egan

Publications and source records attributed to Hilary Egan.

12 recordsLinked to original sources

Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials

Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising systems never reach deployment. This "valley of death" stems from optimization that prioritizes laboratory metrics over industrial viability. We propose a new strategy: "born-qualified" autonomous development, which embeds manufacturability, cost, and durability constraints from the outset. This approach is enabled by four pillars, including the development of multi-objective metrics, causal models, a modular infrastructure, and embedding manufacturing in the discovery loop. Realizing this vision will require sustained, community-wide commitment, but the potential return on that investment is commensurate with the scale of the challenge.

cond-mat.mtrl-sci

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti$_3$C$_2$T$_X$ MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures--from isolated vacancies to nanopores--revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

cond-mat.mtrl-sci

Understanding Computational Science and Engineering (CSE) and Domain Science Skills Development in National Laboratory Postgraduate Internships

Background: Harnessing advanced computing for scientific discovery and technological innovation demands scientists and engineers well-versed in both domain science and computational science and engineering (CSE). However, few universities provide access to both integrated domain science/CSE cross-training and Top-500 High-Performance Computing (HPC) facilities. National laboratories offer internship opportunities capable of developing these skills. Purpose: This student presents an evaluation of federally-funded postgraduate internship outcomes at a national laboratory. This study seeks to answer three questions: 1) What computational skills, research skills, and professional skills do students improve through internships at the selected national laboratory. 2) Do students gain knowledge in domain science topics through their internships. 3) Do students' career interests change after these internships? Design/Method: We developed a survey and collected responses from past participants of five federally-funded internship programs and compare participant ratings of their prior experience to their internship experience. Findings: Our results indicate that participants improve CSE skills and domain science knowledge, and are more interested in working at national labs. Participants go on to degree programs and positions in relevant domain science topics after their internships. Conclusions: We show that national laboratory internships are an opportunity for students to build CSE skills that may not be available at all institutions. We also show a growth in domain science skills during their internships through direct exposure to research topics. The survey instrument and approach used may be adapted to other studies to measure the impact of postgraduate internships in multiple disciplines and internship settings.

cs.CY

Adaptive Computing for Scale-up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

math.OC

Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization

What does materials science look like in the "Age of Artificial Intelligence?" Each materials domain-synthesis, characterization, and modeling-has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

cond-mat.mtrl-sci

A Beginner's Guide to Power and Energy Measurement and Estimation for Computing and Machine Learning

Concerns about the environmental footprint of machine learning are increasing. While studies of energy use and emissions of ML models are a growing subfield, most ML researchers and developers still do not incorporate energy measurement as part of their work practices. While measuring energy is a crucial step towards reducing carbon footprint, it is also not straightforward. This paper introduces the main considerations necessary for making sound use of energy measurement tools and interpreting energy estimates, including the use of at-the-wall versus on-device measurements, sampling strategies and best practices, common sources of error, and proxy measures. It also contains practical tips and real-world scenarios that illustrate how these considerations come into play. It concludes with a call to action for improving the state of the art of measurement methods and standards for facilitating robust comparisons between diverse hardware and software environments.

eess.SP

Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.

cs.DC

The High-Energy Radiation Environment Around a 10 Gyr M Dwarf: Habitable at Last?

High levels of X-ray and UV activity on young M dwarfs may drive rapid atmospheric escape on temperate, terrestrial planets orbiting within the liquid water habitable zone. However, secondary atmospheres on planets orbiting older, less active M dwarfs may be stable and present more promising candidates for biomarker searches. We present new HST and Chandra observations of Barnard's Star (GJ 699), a 10 Gyr old M3.5 dwarf, acquired as part of the Mega-MUSCLES program. Despite the old age and long rotation period of Barnard's star, we observe two FUV ($δ_{130}$ $\approx$ 5000s; $E_{130}$ $\approx$ 10$^{29.5}$ erg each) and one X-ray ($E_{X}$ $\approx$ 10$^{29.2}$ erg) flares, and estimate a high-energy flare duty cycle (defined here as the fraction of the time the star is in a flare state) of $\sim$ 25\%. A 5 A - 10 $μ$m SED of GJ 699 is created and used to evaluate the atmospheric stability of a hypothetical, unmagnetized terrestrial planet in the habitable zone ($r_{HZ}$ $\sim$ 0.1 AU). Both thermal and non-thermal escape modeling indicate (1) the $quiescent$ stellar XUV flux does not lead to strong atmospheric escape: atmospheric heating rates are comparable to periods of high solar activity on modern Earth, and (2) the $flare$ environment could drive the atmosphere into a hydrodynamic loss regime at the observed flare duty cycle: sustained exposure to the flare environment of GJ 699 results in the loss of $\approx$ 87 Earth atmospheres Gyr$^{-1}$ through thermal processes and $\approx$ 3 Earth atmospheres Gyr$^{-1}$ through ion loss processes, respectively. These results suggest that if rocky planet atmospheres can survive the initial $\sim$ 5 Gyr of high stellar activity, or if a second generation atmosphere can be formed or acquired, the flare duty cycle may be the controlling stellar parameter for the stability of Earth-like atmospheres around old M stars.

astro-ph.EP

Planetary Magnetic Field Control of Ion Escape from Weakly Magnetized Planets

Intrinsic magnetic fields have long been thought to shield planets from atmospheric erosion via stellar winds; however, the influence of the plasma environment on atmospheric escape is complex. Here we study the influence of a weak intrinsic dipolar planetary magnetic field on the plasma environment and subsequent ion escape from a Mars sized planet in a global three-dimensional hybrid simulation. We find that increasing the strength of a planet's magnetic field enhances ion escape until the magnetic dipole's standoff distance reaches the induced magnetosphere boundary. After this point increasing the planetary magnetic field begins to inhibit ion escape. This reflects a balance between shielding of the southern hemisphere from ``misaligned" ion pickup forces and trapping of escaping ions by an equatorial plasmasphere. Thus, the planetary magnetic field associated with the peak ion escape rate is critically dependent on the stellar wind pressure. Where possible we have fit power laws for the variation of fundamental parameters (escape rate, escape power, polar cap opening angle and effective interaction area) with magnetic field, and assessed upper and lower limits for the relationships.

astro-ph.EP

Stellar Influence on Heavy Ion Escape from Unmagnetized Exoplanets

Planetary habitability is in part determined by the atmospheric evolution of a planet; one key component of such evolution is escape of heavy ions to space. Ion loss processes are sensitive to the plasma environment of the planet, dictated by the stellar wind and stellar radiation. These conditions are likely to vary from what we observe in our own solar system when considering a planet in the habitable zone around an M-dwarf. Here we use a hybrid global plasma model to perform a systematic study of the changing plasma environment and ion escape as a function of stellar input conditions, which are designed to mimic those of potentially habitable planets orbiting M-dwarfs. We begin with a nominal case of a solar wind experienced at Mars today, and incrementally modify the interplanetary magnetic field orientation and strength, dynamic pressure, and Extreme Ultraviolet input. We find that both ion loss morphology and overall rates vary significantly, and in cases where the stellar wind pressure was increased, the ion loss began to be diffusion or production limited with roughly half of all produced ions being lost. This limit implies that extreme care must be taken when extrapolating loss processes observed in the solar system to extreme environments.

astro-ph.EP

Length Scales and Turbulent Properties of Magnetic Fields in Simulated Galaxy Clusters

Additional physics beyond standard hydrodynamics is needed to fully model the intracluster medium (ICM); however, as we move to more sophisticated models, it is important to consider the role of magnetic fields and the way the fluid approximation breaks down. This paper represents a first step towards developing a self-consistent model of the ICM by characterizing the statistical properties of magnetic fields in cosmological simulations of galaxy clusters. We find that plasma conditions are largely homogeneous across a range of cluster masses and relaxation states. We also find that the magnetic field length scales are resolution dependent and not based on any particular physical process. Energy transfer mechanisms and scales are also identified, and imply the existence of small scale dynamo action. The scales of the small scale dynamo are resolution limited and driven by numerical resistivity and viscosity.

astro-ph.CO

Bringing Simulation and Observation Together to Better Understand the Intergalactic Medium

The methods by which one characterizes the distribution of matter in cosmological simulations is intrinsically different from how one performs the same task observationally. In this paper, we make substantial steps towards comparing simulations and observations of the intergalactic medium (IGM) in a more sensible way. We present a pipeline that generates and fits synthetic QSO absorption spectra using sight lines cast through a cosmological simulation, and simultaneously identifies structure by directly analyzing the variations in HI and OVI number density. We compare synthetic absorption spectra with a less observationally motivated, but more straightforward density threshold-based method for finding absorbers. Our efforts focus on HI and OVI to better characterize the warm/hot intergalactic medium, a subset of the IGM that is challenging to conclusively identify observationally. We find that the two methods trace roughly the same quantities of HI and OVI above observable column density limits, but the synthetic spectra typically identify more substructure in absorbers. We use both methods to characterize HI and OVI absorber properties. We find that both integrated and differential column density distributions from both methods generally agree with observations. The distribution of Doppler parameters between the two methods are similar for Lya and compare reasonably with observational results, but while the two methods agree with each other with OVI systems, they both are systematically different from observations. We find a strong correlation between OVI baryon fraction and OVI column density. We also discuss a possible bimodality in the temperature distribution of the gas traced by OVI.

astro-ph.CO