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At least 1,351 records · Page 75

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗

Challenges with vitrification of Hanford High-Level Waste (HLW) to borosilicate glass – An overview

The Hanford site in Washington State houses ~56 million gallons of radioactive wastes stored in 177 underground tanks. The waste must be immobilized and permanently stored, and the plan is to separate the tank wastes into low activity waste (LAW) and high-level waste (HLW) streams. The U.S. Department of Energy is building a Waste Treatment and Immobilization Plant at Hanford site to separately vitrify these two waste streams in borosilicate glass using Joule-heated ceramic melters (JHCM). Although the process of nuclear waste vitrification seems to be well established, in practicality, it is faced with complex problems starting from the design of glass compositions, to processing in melters and long-term performance of the final vitrified waste forms. The article presents an overview of our current understanding of critical challenges related to the development and performance of HLW glasses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Deep glassy state dynamic data challenge glass models: Elastic models

The idea of an “ideal” glass transition temperature has persisted at least since the work from Kauzmann when it was observed that the entropy of glass-forming liquids extrapolated to below that of the crystal, thus suggesting the need for a phase transition at a finite or non-zero absolute temperature. This thermodynamic paradox was also found to be related to the observations of a diverging of the extrapolated viscosity or relaxation times at a temperature near to this ideal glass transition. Recently, however, we have carried out experiments using both an ancient amber material and an ultra-stable amorphous fluoropolymer that challenge the ideas of the divergence of the viscosity or relaxation times at this ideal glass transition. In the present manuscript we have evaluated two theories of the glass transition that are based on ideas related to elasticity of the amorphous glass-forming material. We find that the models from both J. Dyre and his group and of K.S. Schweizer and his group not only show non-diverging behavior but are also in some agreement with the new data, though still showing somewhat slower dynamics than those observed in the experiments. The work shows that the data are good enough to distinguish between theories and it is suggested that other mechanisms may be needed to fully describe the non-diverging responses of the ultra-stable glasses.

36 MATERIALS SCIENCE↗

Transformational Challenge Reactor preconceptual core design studies

In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Engineering challenges for detectors at the ILC

Over the last years two proposals for experiments at the ILC have been developed, ILD and SID. Extensive R&D has been carried out around the world to develop the needed technologies. Furthermore a first round of engineering studies was made as part of the ILC TDR to understand the integration of these different sub-systems into coherent and integrated detector concepts. Among the key challenges for the sub detectors are the extreme low mass/low power requirements or the extreme channel densities needed in particle flow based detectors. Throughout these studies special care was taken to ensure that the engineering models and the simulation models, used in studies of the physics capabilities of the detectors, stay synchronized. In the near future, the models will need to be evolved to take the special requirements of the potential ILC site in Japan into account. Furthermore, the state of the integration of the detectors, and the future directions, will be discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Language models for materials discovery and sustainability: Progress, challenges, and opportunities

Significant advancements have been made in one of the most critical branches of artificial intelligence: natural language processing (NLP). These advancements are exemplified by the remarkable success of OpenAI’s GPT-3.5/4 and the recent release of GPT-4.5, which have sparked a global surge of interest akin to an NLP gold rush. Here, in this article, we offer our perspective on the development and application of NLP and large language models (LLMs) in materials science. We begin by presenting an overview of recent advancements in NLP within the broader scientific landscape, with a particular focus on their relevance to materials science. Next, we examine how NLP can facilitate the understanding and design of novel materials and its potential integration with other methodologies. To highlight key challenges and opportunities, we delve into three specific topics: (i) the limitations of LLMs and their implications for materials science applications, (ii) the creation of a fully automated materials discovery pipeline, and (iii) the potential of GPT-like tools to synthesize existing knowledge and aid in the design of sustainable materials.

36 MATERIALS SCIENCE↗

The research challenges in security and safeguards for nuclear fission batteries

This paper discusses the nuclear security and safeguards research challenges presented by the development and deployment of nuclear fission batteries. These are defined as easily transportable and deployable nuclear systems which are designed to operate either unattended or autonomously. We start by defining the current landscape of domestic and international safeguards and security and discuss how it can be affected by the introduction these new nuclear systems. We then specifically discuss the technology gaps and technologies to be developed to facilitate their practical deployment. We find that, as expected, we can leverage conclusions from existing security and safeguards studies for small modular rectors and develop bespoke target set analyses to inform security postures based on probabilistic risk assessment. We find also that specific fission battery security economic analysis tools are needed and security by design must be applied early. However, the most important finding is that these new systems will require a new comprehensive set of cyber tools covering transportation, installation, operation, maintenance security of the fission battery systems. Altogether, we find that the development of the necessary security and safeguards requirements at the design phase of such a technology will be of great benefit in the smooth deployment of this modern nuclear energy system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Elucidating the challenges in extracting ultra-slow flame speeds in a closed vessel - A CH 2 F 2 microgravity case study using optical and pressure-rise data

Refrigerants with a low global warming potential (GWP) possess mild flammability. Hence, a fundamental understanding of their combustion characteristics is required to assess their fire-hazardous potential. The laminar burning velocity is one fundamental property to describe these under safety evaluation aspects. However, measuring laminar burning velocities for slow-burning components, such as low-GWP alternatives, is challenging. This is due to influencing effects such as buoyant flame deformation, stretch, radiation, and confinement, especially at the flammability limits. Here, in the present study, we investigated near-limit flames of the representative refrigerant difluoromethane (CH 2 F 2 ) with nitrogen-enriched oxidizer mixtures to elucidate the potentials and limitations at ultra-slow flame speeds of two widely used flame speed measurement methods in the closed vessel configuration: the optical flame speed measurement in the early quasi-isobaric regime and the flame speed determination from the pressure-rise during the later phase of the isochoric combustion process. Experiments were performed under terrestrial- and microgravity, conducted in a specially designed setup suitable for drop tower applications, using both methods in parallel. Recommendations for the extraction of flame speed data are derived from the non-buoyant reference investigations under microgravity and transferred to ultra-slow flames at terrestrial gravity. Near-limit flames under microgravity were found to be significantly affected by stretch effects for the optical method so that flame speed extrapolations to unstretched conditions are prone to errors. Stretch also affects the pressure method’s lower evaluation limit, and errors can be estimated by combining flame speed data from the pressure method and Markstein lengths from optical experiments.

42 ENGINEERING↗

Oil spill detection by imaging radars: Challenges and pitfalls

In this paper, criteria for discriminating between radar signatures of oil films and biogenic slicks visible on synthetic aperture radar (SAR) images of the sea surface as dark patches are critically reviewed. We question the often claimed high success rate of oil spill detection algorithms using single-polarization SARs because the SAR images used to train these algorithms are based usually on subjective interpretation and are not validated by on-site inspections or multi-sensor measurements carried out from oil pollution surveillance planes. Furthermore, we doubt that polarimetric parameters derived from fully-polarimetric SAR data, like entropy, anisotropy, and mean scattering angle, are beneficial for discriminating between mineral oil films and biogenic slicks. We challenge the often-made claim that another scattering mechanism than Bragg scattering applies for radar backscattering from mineral oil films than from biogenic slicks. This view is supported by data acquired by the Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) of NASA/JPL, which operates at L-band and has an extremely low noise floor. We suspect that opposing results obtained from previous analyses of spaceborne polarimetric SAR data are caused by the high noise floors of the spaceborne SARs. However, most of the analyzed spaceborne polarimetric data were not acquired at L-band, but at C-and X-band. On the other hand, differences in the statistical behavior of the radar backscattering could be real due to the fact that, other than biogenic surface films, mineral oil films, can form multi-layers, whose thickness can vary within an oil patch. Radar backscattering from emulsion layers can also fluctuate due to variations of the oil/water mixture ratio. These effects could cause an increase of the standard deviation (STD) of the co-polarized phase difference (CPD) for scattering at mineral oil films and emulsions. In the special case of thick oil layers or oil/water emulsion layers, where the radar is sensitive to the dielectric constant of the oil, discrimination becomes possible due the fact that Bragg scattering depends on the dielectric constant of the scattering medium.

47 OTHER INSTRUMENTATION↗

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Price formation in zero-carbon electricity markets - fundamentals, challenges, and research needs

Future power systems dominated by zero-carbon generation resources may require significant revisions to electricity market designs to ensure capacity adequacy and market efficiency. Here, in this paper, we first conceptually outline key fundamentals underlying electricity market design and price formation in U.S. electricity markets. We then discuss a set of potential market design challenges related to price formation in a grid dominated by zero-carbon resources with marginal cost profiles that differ compared to traditional thermal resources. Next, we review electricity market design solutions that have been proposed in the literature to ensure market efficiency in zero-carbon systems, and the associated implications for price formation. We conclude by summarizing key observations and establishing a set of research questions that should be addressed to improve our understanding of market design, price formation, and market efficiency in zero-carbon power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hydrogen technology for maritime applications: A review of challenges, opportunities, and lessons from the port authority of New York and New Jersey

The maritime industry faces increasing demand for energy security, operational efficiency, and environmental performance improvements. Hydrogen technology, considered a potential energy carrier, is being explored for port operations, including cargo-handling equipment, heavy-duty vehicles, and stationary power systems. This review evaluates the feasibility, challenges, and potential benefits of hydrogen integration within port infrastructure, using the Port Authority of New York and New Jersey as a representative case study. Drawing on case studies, technical reports, and policy analyses, this study examines the infrastructural, regulatory, and operational factors influencing large-scale deployment, emphasizing supply chain development, storage requirements, and refueling infrastructure. By situating hydrogen within broader maritime energy transition efforts, this review provides an evidence-based assessment of its role in port operations and energy diversification strategies. In conclusion, the findings outline key barriers to adoption and emphasize the need for coordinated efforts among stakeholders to determine hydrogen's role alongside other emerging energy technologies.

08 HYDROGEN↗

Artificial intelligence methods for protein structure and interaction prediction: Recent advances and challenges

Recent advances in artificial intelligence have introduced novel methods for high-accuracy prediction of protein tertiary structures, protein complex structures, and interactions between proteins and other biomolecules, such as small molecules and nucleic acids. Such advancements are accelerating biomedical research and the development of new protein design and bioengineering methods among many other important biotechnology applications. Here, in this review, we outline the recent advances in protein-centric biomolecular structure and interaction prediction, highlight some major challenges in the field, and discuss potential directions to address them.

Morehead, Alex [Lawrence Berkeley National Laborat↗

Additive manufacturing of near-net-shape bonded magnets: Prospects and challenges

Additive manufacturing (AM) or 3D printing is well known for producing arbitrary shaped parts without any tooling required, offering a promising alternative to the conventional injection molding method to fabricate near-net-shaped magnets. In order to determine their applicability in the fabrication of Nd-Fe-B bondedmagnets, we compare two 3D printing technologies, namely binder jetting and material extrusion. Some prospects and challenges of these state-of-the-art technologies for large-scale industrial applications will be discussed.

36 MATERIALS SCIENCE↗

Challenges in spatial metabolomics and proteomics for functional tissue unit and single-cell resolution

While transcriptomics is the most broadly applied technology for global spatial and single cell measurements in healthy and diseased tissues. Transcripts are often used as a proxy for protein and even metabolite measurements, but it has become commonly accepted that extrapolating this kind of information is a poor proxy and not a substitute for direct measurement. Within the last decade advanced developments of mass spectrometry-based assays have made these direct measurements not only possible, but routine. Where mass spectrometry has become an enabling technology, and various methods can now detect hundreds of metabolites and thousands of proteins from samples. Not only can this be performed within bulk measurements, but much effort has been directed into translating these measurements to single cells and tissues at cellular resolution. The information obtained from mass spectrometry is now able to trace metabolic events and decipher feedback loops across anatomical regions, connecting genetic and metabolic networks that define phenotypes. Herein, we will broadly overview developments in the field over the past decade, leading into several case studies which highlight the direct measurement of metabolites, proteins, and proteoforms from thinly sliced tissues. Much of this work is feasible due to multidisciplinary team science, and we offer brief perspective on paths forward and the challenges that persist with adoption and application of spatial omics.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges in integrating dissolved organic matter chemodiversity into kinetic models of soil respiration

The chemodiversity of dissolved organic matter (DOM) in soil has been proposed to influence the microbial metabolism and fate of belowground organic carbon (C). However, integrating DOM chemistry into soil C cycle models to improve predictions of C stocks and fluxes—beyond simply considering DOM pool size—remains a challenge. While recent research suggests that incorporating DOM chemodiversity into models can improve predictions of microbial respiration, there is still a lack of mechanistic understanding describing how DOM chemodiversity affects microbial metabolism and soil respiration. Here, we evaluated whether DOM chemodiversity was a determinant of soil respiration using paired measurements of high-resolution DOM chemistry, obtained from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), and potential soil respiration rates from across the United States (U.S.), all data provided by the Molecular Observation Network. Our objectives were to (1) assess statistical relationships between DOM chemodiversity and microbial respiration, and (2) evaluate the ability of kinetic models to leverage DOM chemistry to explain empirical relationships found in statistical models. Statistical regressions revealed that DOM chemodiversity (alpha diversity) was nonlinearly related to potential soil respiration rates, both independently and through its interactions with DOM and total C concentrations. In soils with relatively high DOM but low total C concentrations, potential soil respiration rates were negatively correlated with DOM alpha diversity, whereas in soils with relatively low DOM and high total C concentrations showed the opposite trend. However, when metabolic transition theory kinetic models were modified to include chemodiversity, their performance was comparable to traditional Monod kinetics approaches, which simulate respiration rates as a function of DOM concentration. The inability to account for nonlinearities in DOM chemodiversity–respiration relationships highlight an opportunity to advance substrate uptake kinetics by establishing causal links between DOM chemodiversity, microbial metabolism trade-offs, and potential interactions under varied environmental conditions.

Bioenergetic model↗

Structural design challenges and implications for high temperature concentrating solar power receivers

High operating temperatures along with diurnal cycling and high operating stresses bring many material and engineering challenges for concentrated solar power (CSP) receivers. Current design rules in ASME Boiler and Pressure Vessel (B&PV) Code for high temperature structural components were not intended for CSP components. The paper reviews the design rules in several sections of ASME B&PV Code in terms of their applicability in designing high temperature CSP receivers. With some restrictions and modifications, the conditions assumed in the design rules in Section III, Division 5 of ASME B&PV Code are found to closely resemble the loading conditions of CSP receiver, including accounting for the interaction between creep and fatigue damage. Further, the paper applies the proposed design rules to an external tubular receiver design and discusses several lessons learned from the design study. The creep damage accumulation due to high thermal stresses resulting from circumferentially non-uniform flux distribution is found to control the design of CSP receivers. Several mitigation actions to improve the design life of receivers are also discussed.

14 SOLAR ENERGY↗

Overcoming significant challenges in extracting off-stoichiometric thermodynamics using the compound energy formalism through complementary use of experimental and first principles data: A case study of Ba 1-x Sr x FeO 3-δ

The compound energy formalism (CEF) is a powerful framework to describe the thermodynamics of metal oxides as a function of off-stoichiometry, temperature, and composition. The thermodynamic properties are crucial materials design attributes in metal oxide-based oxygen-exchange chemical processes. Despite the richness of information an accurate CEF model provides, a method to determine a unique and accurate fit for oxygen exchange materials remains elusive. This contribution details a method for fitting the CEF model that overcomes the current fitting challenges through three innovations: 1) the combination of density functional theory calculations with experimental data decorrelates excess terms and delineates the enthalpic/entropic contributions to the Gibbs free energy; 2) a systematic determination of the important CEF model terms, removing thermodynamic predetermining human intervention; 3) a self-consistent solution of the starting oxygen offstoichiometry (δ 0 ) of thermogravimetric measurements. Thus, our method enables the reliable extraction of off-stoichiometric metal oxide thermodynamic properties and facilitates rapid materials compositional screening, and reliable process design of systems dependent on off-stoichiometric redox-active metal oxides. We apply this method to a Ba x Sr 1-x FeO 3-δ test case. We find by systematically examining the performance of the CEF model fit with and without each innovation that all three innovations are necessary for an accurate fit. We determined that reduction enthalpy is higher and more sensitive to off-stoichiometry when the Sr fraction is large (139.5 and 185.3 kJ/mol O 2 for SrFeO 3 at δ = 0 and δ = 0.5, respectively vs. nearly constant 83 kJ/mol O 2 for BaFeO 3 ). However, the reduction entropy is mostly insensitive to Sr fraction, but highly dependent on δ suggesting larger contributions in the non-configurational entropy parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗