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At least 649 records · Page 36

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗

Nanoscale Magnetic Domains in Polycrystalline Mn 3 Sn Films Imaged by a Scanning Single-Spin Magnetometer

Noncollinear antiferromagnets with novel magnetic orders, vanishingly small net magnetization, and exotic spin related properties hold enormous promise for developing next-generation, transformative spintronic applications. A major ongoing research focus of this community is to explore, control, and harness unconventional magnetic phases of this emergent material system to deliver state-of-the-art functionalities for modern microelectronics. Here we report direct imaging of magnetic domains of polycrystalline Mn 3 Sn films, a prototypical noncollinear antiferromagnet, using nitrogen-vacancy-based single-spin scanning microscopy. Nanoscale evolution of local stray field patterns of Mn 3 Sn samples are systematically investigated in response to external driving forces, revealing the characteristic “heterogeneous” magnetic switching behaviors in polycrystalline textured Mn 3 Sn films. Furthermore, our results contribute to a comprehensive understanding of inhomogeneous magnetic orders of noncollinear antiferromagnets, highlighting the potential of nitrogen-vacancy centers to study microscopic spin properties of a broad range of emergent condensed matter systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective

Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.

collisions↗

Universality of Dicke superradiance in arrays of quantum emitters

Abstract Dicke superradiance is an example of emergence of macroscopic quantum coherence via correlated dissipation. Starting from an initially incoherent state, a collection of excited atoms synchronizes as they decay, generating a macroscopic dipole moment and emitting a short and intense pulse of light. While well understood in cavities, superradiance remains an open problem in extended systems due to the exponential growth of complexity with atom number. Here we show that Dicke superradiance is a universal phenomenon in ordered arrays. We present a theoretical framework – which circumvents the exponential complexity of the problem – that allows us to predict the critical distance beyond which Dicke superradiance disappears. This critical distance is highly dependent on the dimensionality and atom number. Our predictions can be tested in state of the art experiments with arrays of neutral atoms, molecules, and solid-state emitters and pave the way towards understanding the role of many-body decay in quantum simulation, metrology, and lasing.

74 ATOMIC AND MOLECULAR PHYSICS↗

Enhancing Coherence Limits in Superconducting Quantum Systems for Computing and Sensing

This talk will highlight recent efforts at the SQMS Center to develop qudit-based quantum computing architectures using superconducting three-dimensional (3D) cavities, as well as the use of these ultra-coherent cavities for quantum sensing. I will present systematic studies of materials and devices aimed at identifying and mitigating the dominant sources of decoherence—including two-level systems (TLS), quasiparticles, and other noise mechanisms—in both transmons and 3D cavities. These investigations include microwave loss characterization of niobium, tantalum, aluminum, their native oxides, and substrate materials such as silicon and sapphire. By combining measurements on qubits and cavities, we disentangle subsystem-specific loss mechanisms and establish a hierarchy of mitigation strategies, leading to transmon coherence times exceeding one millisecond. I will also discuss studies of quasiparticle dynamics, including quasiparticle bursts observed in qubits operated both above ground and at the Gran Sasso underground laboratory, and the observation that applied magnetic fields can suppress temporal T₁ fluctuations. Building on these advances, we demonstrate a record-coherence two-cell cavity-qudit system with coherence times exceeding 20 milliseconds. Leveraging tunable sideband interactions together with error-resilient protocols, including measurement-based error correction and post-selection, we achieve high-fidelity quantum state control, including the preparation of Fock states up to N=20 with fidelities above 95% and the generation of high-fidelity two-mode entangled states. Finally, I will discuss how these ultra-coherent quantum systems are enabling emerging quantum sensing applications, including searches for dark matter and gravitational waves.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

Preparation of Smart Materials by Additive Manufacturing Technologies: A Review

Over the last few decades, advanced manufacturing and additive printing technologies have made incredible inroads into the fields of engineering, transportation, and healthcare. Among additive manufacturing technologies, 3D printing is gradually emerging as a powerful technique owing to a combination of attractive features, such as fast prototyping, fabrication of complex designs/structures, minimization of waste generation, and easy mass customization. Of late, 4D printing has also been initiated, which is the sophisticated version of the 3D printing. It has an extra advantageous feature: retaining shape memory and being able to provide instructions to the printed parts on how to move or adapt under some environmental conditions, such as, water, wind, light, temperature, or other environmental stimuli. This advanced printing utilizes the response of smart manufactured materials, which offer the capability of changing shapes postproduction over application of any forms of energy. The potential application of 4D printing in the biomedical field is huge. Here, the technology could be applied to tissue engineering, medicine, and configuration of smart biomedical devices. Various characteristics of next generation additive printings, namely 3D and 4D printings, and their use in enhancing the manufacturing domain, their development, and some of the applications have been discussed. Special materials with piezoelectric properties and shape-changing characteristics have also been discussed in comparison with conventional material options for additive printing.

36 MATERIALS SCIENCE↗

Hybrid Entanglement between Optical Discrete Polarizations and Continuous Quadrature Variables

By coherently combining advantages while largely avoiding limitations of two mainstream platforms, optical hybrid entanglement involving both discrete and continuous variables has recently garnered widespread attention and emerged as a promising idea for building heterogenous quantum networks. In contrast to previous results, here we propose a new scheme to remotely generate hybrid entanglement between discrete polarization and continuous quadrature optical qubits heralded by two-photon Bell-state measurement. As a novel nonclassical light resource, we further use it to discuss two examples of ways—entanglement swapping and quantum teleportation—in which quantum information processing and communications could make use of this hybrid technique.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Elucidating the Morphological Instability Mechanisms During Electrodeposition of Active Metals

The primary aim of this investigation is to elucidate the mechanisms by which a group of metals pertinent to battery technology exhibit unstable growth morphology during electrodeposition, which are crucial for the operational efficacy of batteries. The metals under consideration include alkali metals alongside zinc, all of which are characterized by high atomic mobility and reactivity with the electrolytes employed in battery systems. These materials represent promising electrode candidates for next-generation rechargeable batteries that are anticipated to deliver significantly enhanced energy density at a reduced cost. Nevertheless, the widespread occurrence of distinctly non-uniform morphologies, exemplified by the emergence of filamentous and moss-like structures, constitutes a significant impediment to their effective utilization, as it leads to accelerated capacity degradation and potential internal short circuits. This study addresses a critical question that has thus far garnered limited attention: Does the residual stress induced by the plating process play an instrumental role in inducing the morphological instability? Utilizing zinc as the primary model system, this project will be executed through three interconnected tasks: (1) the quantification of the relationship between plating stress and electroplating morphologies, (2) the three-dimensional imaging of the microstructure of the mossy structure at the nanoscale, and (3) the development of a mesoscale electroplating model to interpret empirical findings and generate additional predictive insights.

25 ENERGY STORAGE↗

Programmable interactions and emergent geometry in an array of atom clouds

Interactions govern the flow of information and the formation of correlations between constituents of many-body quantum systems, dictating phases of matter found in nature and forms of entanglement generated in the laboratory. Typical interactions decay with distance and thus produce a network of connectivity governed by geometry—such as the crystalline structure of a material or the trapping sites of atoms in a quantum simulator. However, many envisioned applications in quantum simulation and computation require more complex coupling graphs including non-local interactions, which feature in models of information scrambling in black hole, and mappings of hard optimization problems onto frustrated classical magnets. Here we describe the realization of programmable non-local interactions in an array of atomic ensembles within an optical cavity, in which photons carry information between atomic spins. By programming the distance dependence of the interactions, we access effective geometries for which the dimensionality, topology and metric are entirely distinct from the physical geometry of the array. As examples, we engineer an antiferromagnetic triangular ladder, a Möbius strip with sign-changing interactions and a treelike geometry inspired by concepts of quantum gravity. The tree graph constitutes a toy model of holographic duality, in which the quantum system lies on the boundary of a higher-dimensional geometry that emerges from measured correlations. Overall, our work provides broader prospects for simulating frustrated magnets and topological phases, investigating quantum optimization paradigms and engineering entangled resource states for sensing and computation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Modeling Distributed Generation in California

In support of analysis for the biennial Integrated Energy Policy Report, the California Energy Commission and the National Renewable Energy Laboratory have partnered to study the growth of distributed energy resources in California. This study involves the use of National Renewable Energy Laboratory's Distributed Generation Market Demand model, available at https://www.nrel.gov/analysis/dgen/, to project statewide adoption of distributed photovoltaics and paired storage. Key outcomes of the collaboration include: • Improved representation of California building stock, load profiles, historical adoption, and tariffs, including the net billing tariff, in the dGen model; • Trained CEC staff members to use and adapt the dGen model for their specific needs; • Developed a methodology for representing emerging consumer segments to potentially adopt distributed energy resources, including low-income, multifamily, and renter-occupied buildings; • Forecasted solar photovoltaic and paired storage growth in California using a common set of modeling parameters. This report describes the multiyear effort, which includes a discussion of: • Methodology and data employed in adapting the Distributed Generation Market Demand model for California to forecast solar photovoltaic and storage statewide through 2040; • Steps taken to modify the base model to forecast solar photovoltaic adoption in emerging market segments such as multifamily or renter-occupied homes or both; • Future enhancements of the model.

14 SOLAR ENERGY↗

Microbial spies and bloggers: programming cells to convert environmental information into discernible signals

Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.

analyte↗

Transforming the Process Industries through Electrification: Challenges and Opportunities

For the more than 70 years, the process industries have provided essential fuels and materials for global growth. Increased manufacturing production comes with substantial environmental impact. Reducing environmental impact through process electrification, carbon capture, and other emerging technologies would require large changes throughout the process industries. We review opportunities and challenges related to electrification, focusing on technical, operational, and economic considerations. Here, we conclude that electrification could completely eliminate scope 1 CO 2 emissions, increase product quality, and reduce the equipment size and cost. On the other hand, it calls for a significant expansion of power generation capacity, as well as new paradigms for process design and operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The emergence of valency in colloidal crystals through electron equivalents

Colloidal crystal engineering of complex, low-symmetry architectures is challenging when isotropic building blocks are assembled. In this study we describe an approach to generating such structures based upon programmable atom equivalents (nanoparticles functionalized with many DNA strands) and mobile electron equivalents (small particles functionalized with a low number of DNA strands complementary to the programmable atom equivalents). Under appropriate conditions, the spatial distribution of the electron equivalents breaks the symmetry of isotropic programmable atom equivalents, akin to the anisotropic distribution of valence electrons or coordination sites around a metal atom, leading to a set of well-defined coordination geometries and access to three new low-symmetry crystalline phases. All three phases represent the first examples of colloidal crystals, with two of them having elemental analogues (body-centred tetragonal and high-pressure gallium), while the third (triple double-gyroid structure) has no known natural equivalent. This approach enables the creation of complex, low-symmetry colloidal crystals that might find use in various technologies.

36 MATERIALS SCIENCE↗

IGR J18249−3243: a new GeV-emitting FR II and the emerging population of high-energy radio galaxies

ABSTRACT The advent of new all-sky radio surveys such as the VLA Sky Survey and the Rapid ASKAP Continuum Survey, performed with the latest generation radio telescopes, is opening new possibilities on the classification and study of extragalactic γ-ray sources, specially the underrepresented ones like radio galaxies. In particular, the enhanced sensitivity (sub-mJy level) and resolution (a few arcsec) provides a better morphological and spectral classification. In this work, we present the reclassification of a Fermi/Large Area Telescope (LAT) source as a new Fanaroff–Riley II radio galaxy from the International Gamma-Ray Astrophysics Laboratory sample found to emit at GeV energies. Through a broad-band spectral fitting from radio to γ-ray, we find that the commonly invoked jet contribution is not sufficient to account for the observed γ-ray flux. Our modelling suggests that the observed emission could mainly originate in the lobes (rather than in the radio core) by inverse Compton scattering of radio-emitting electrons off the ambient photon fields. In addition, we cross-correlated the latest generation radio surveys with a list of Fermi/LAT candidate misaligned AGN from the literature, finding four new radio galaxies with a double-lobed morphology. Additional four objects could be classified as such thanks to previous studies in the literature, for a total of nine new radio galaxies with GeV emission presented in this work. We foresee that further objects of this class might be found in the near future with the advent of the Square Kilometer Array, populating the GeV sky.

Bruni, G. (ORCID:0000000251826289)↗

Transmission of Human Influenza A Virus in Pigs Selects for Adaptive Mutations on the HA Gene

Influenza A viruses (FLUAV) cause respiratory diseases in many host species, including humans and pigs. The spillover of FLUAV between swine and humans has been a concern for both public health and the swine industry. With the emergence of the triple reassortant internal gene (TRIG) constellation, establishment of human-origin FLUAVs in pigs has become more common, leading to increased viral diversity. However, little is known about the adaptation processes that are needed for a human-origin FLUAV to transmit and become established in pigs. Here, we generated a reassortant FLUAV (VIC11pTRIG) containing surface gene segments from a human FLUAV strain and internal gene segments from the 2009 pandemic and TRIG FLUAV lineages and demonstrated that it can replicate and transmit in pigs. Sequencing and variant analysis identified three mutants that emerged during replication in pigs, which were mapped near the receptor binding site of the hemagglutinin (HA). The variants replicated more efficiently in differentiated swine tracheal cells compared to the virus containing the wildtype human-origin HA, and one of them was present in all contact pigs. These results show that variants are selected quickly after replication of human-origin HA in pigs, leading to improved fitness in the swine host, likely contributing to transmission.

60 APPLIED LIFE SCIENCES↗

Hybrid Power Purchase Agreements for Flexible 24/7 Energy Delivery – A Comprehensive Review of Current Practices and Research Pathways

Power Purchase Agreements (PPAs) are becoming increasingly preferred among large energy consumers, such as data centers, to secure cost-effective energy and meet accelerating demand growth. Traditionally, variable renewable energy (VRE)-based PPAs operate on a pay-as-produced basis, balancing supply and demand for a relatively longer duration (e.g., annually). However, the focus is shifting toward matching supply and demand on an hourly basis to fully meet energy needs. This shift requires the integration of flexible energy resources, such as hydropower, thermal generation, and energy storage, to complement VRE sources like wind and solar, forming the foundation for 24/7 PPA. This work contributes by: (i) reviewing emerging market trends and current practices in PPA procurement, supported by data on PPA prices and technology portfolios; (ii) synthesizing the existing literature on modeling approaches for contract pricing, quantities, hybrid resource procurement, and risk management in 24/7 PPA design, while identifying key research gaps; and (iii) proposing an integrated 24/7 PPA design framework along with two contracting mechanisms from the perspectives of both PPA providers and consumers. The proposed framework highlights critical modeling challenges, risk-allocation issues, and future research opportunities for 24/7 PPA design.

24/7↗

Optimization-based modeling and analysis of brine reflux osmotically assisted reverse osmosis for application toward zero liquid discharge systems

Significant amounts of high-salinity wastewater generated by water-intensive industrial activities such as shale oil and gas production have raised serious environmental concerns in recent years. Existing and emerging desalination technologies offer promise to manage these high salinity wastewater streams while simultaneously producing fresh water that could be diverted for beneficial uses. Osmotically assisted reverse osmosis (OARO) is one such emerging desalination technology capable of handling hypersaline brines and achieving high recoveries. However, rigorous modeling and analysis is needed to evaluate the process performance, energy consumption, and treatment cost of various OARO configurations. Here, this work presents detailed modeling and analysis of brine-reflux OARO (BR-OARO) system and compares it with other commonly discussed configurations, including cascading osmotically mediated reverse osmosis (COMRO), consecutive loop OARO, and split feed counterflow RO, through a cost optimization-based framework. We analyze and compare the treatment costs, membrane area, specific energy consumption, and design parameters of the aforementioned configurations with the ultimate goal of achieving zero liquid discharge (ZLD). The results indicate that the BR-OARO system with treatment cost of 5.1 US $/m 3 of produced water with 10% salinity outperforms other configurations in terms of number of stages needed, treatment cost, membrane area, and energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

Dynamic graph embedding has emerged as a very effective technique for addressing diverse temporal graph analytic tasks (i.e., link prediction, node classification, recommender systems, anomaly detection, and graph generation) in various applications. Such temporal graphs exhibit heterogeneous transient dynamics, varying time intervals, and highly evolving node features throughout their evolution. Hence, incorporating long-range dependencies from the historical graph context plays a crucial role in accurately learning their temporal dynamics. In this paper, we develop a graph embedding model with uncertainty quantification, TransformerG2G, by exploiting the advanced transformer encoder to first learn intermediate node representations from its current state (t) and previous context (over timestamps [t–1,t–l], l is the length of context). Moreover, we employ two projection layers to generate lower-dimensional multivariate Gaussian distributions as each node's latent embedding at timestamp t. We consider diverse benchmarks with varying levels of "novelty" as measured by the TEA (Temporal Edge Appearance) plots. Here, our experiments demonstrate that the proposed TransformerG2G model outperforms conventional multi-step methods and our prior work (DynG2G) in terms of both link prediction accuracy and computational efficiency, especially for high degree of novelty. Furthermore, the learned time-dependent attention weights across multiple graph snapshots reveal the development of an automatic adaptive time stepping enabled by the transformer. Importantly, by examining the attention weights, we can uncover temporal dependencies, identify influential elements, and gain insights into the complex interactions within the graph structure. For example, we identified a strong correlation between attention weights and node degree at the various stages of the graph topology evolution.

97 MATHEMATICS AND COMPUTING↗