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Using state-of-the-art technology trends to assess space system cost risk
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Noise in state of the art clocks and their impact for fundamental physics
In this paper a review of the use of advanced atomic clocks in testing the fundamental physical laws will be presented. Noise sources of clocks will be discussed, together with an outline their characterization based on current models. The paper will conclude with a discussion of recent attempts to reduce the fundamental, as well as technical noise in atomic clocks.
Unfolding the Universe With the James Webb Space Telescope: Combining Art, Science, and Technology for Public Outreach
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ART Advanced Materials Program- Grain Coarsening Behavior of Alloy 709 Heats
Powerpoint slides for ATR Advanced Materials Program Grain Coarse
Chemical Profiles of the Oxides on Tantalum in State of the Art Superconducting Circuits
Abstract Over the past decades, superconducting qubits have emerged as one of the leading hardware platforms for realizing a quantum processor. Consequently, researchers have made significant effort to understand the loss channels that limit the coherence times of superconducting qubits. A major source of loss has been attributed to two level systems that are present at the material interfaces. It is recently shown that replacing the metal in the capacitor of a transmon with tantalum yields record relaxation and coherence times for superconducting qubits, motivating a detailed study of the tantalum surface. In this work, the chemical profile of the surface of tantalum films grown on c‐plane sapphire using variable energy X‐ray photoelectron spectroscopy (VEXPS) is studied. The different oxidation states of tantalum that are present in the native oxide resulting from exposure to air are identified, and their distribution through the depth of the film is measured. Furthermore, it is shown how the volume and depth distribution of these tantalum oxidation states can be altered by various chemical treatments. Correlating these measurements with detailed measurements of quantum devices may elucidate the underlying microscopic sources of loss.
Material selection and manufacturing for high‐temperature heat exchangers: Review of state‐of‐the‐art development, opportunities, and challenges
Abstract Many energy systems demand heat transfer at high temperatures to keep up with high demand for power, so high‐temperature material that can perform and last under these harsh conditions is needed for heat exchangers. The engineering requirements for these high‐temperature heat exchanger material call for high thermal conductivity, high resistance to fracture, high resistance to creep deformation, environmental stability in environments associated with the application, and high modulus of elasticity while maintaining low cost to make and maintain. Naturally, ceramics are a good solution for this endeavor. In the past, high‐temperature heat exchangers made from ceramics have been used. We provide examples of ceramics in relevant heat exchange applications and provide motivation where additive manufacturing (AM) can improve efficiency. AM for the relevant material is under development, and we provide insight on the AM of ceramic materials and examples of AM heat exchangers keeping cost in mind. The motivation of the review paper is to provide a framework for material and manufacturing selection for high‐temperature heat exchangers for AM to keep up with the demand for better efficiency, better material, better manufacturing, and cost moving forward with AM technology in high‐temperature ceramic heat exchangers.
Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies
Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.
Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles
Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.
Simulating dispatchable grid services provided by flexible building loads: State of the art and needed building energy modeling improvements
End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability, reduce costs, and support increased hosting of distributed renewable generation. This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling. We consider services delivered to (1) the high-voltage bulk power system through the coordinated action of many, distributed building loads working together, and (2) targeted support provided to the operation of low-voltage electric distribution grids. Although an exhaustive exploration is not possible, we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling (BEM) tools, suggesting pathways for future research and development.
Cost-Benefit Analysis of Electricity Resilience Projects: State of the Art and Gap Analysis
Utilities and regulators must weigh the benefits of electricity resilience projects against their costs, which would be passed on to customers. Cost-benefit analysis (CBA) is an appropriate method for assessing this tradeoff. Here, in this paper we review the literature on CBA of electricity resilience projects and analyze gaps in the available methods and tools. The costs of resilience projects are typically straightforward to estimate but their benefits — particularly the avoided costs of power interruptions — are complex to quantify and monetize. A common perception among practitioners is that current CBA tools are not sufficiently mature to be adopted into real-world practice. We propose an electricity resilience CBA framework consisting of several elements: risks, physical impacts, power interruptions, economic impacts, and resilience projects. While methods for some elements are well-developed, there is a need for novel approaches to value avoided power interruptions, integrate multiple risks and benefit streams, and incorporate uncertainty.
A new algae technical standards focus group: Summarizing and guiding the algae state of the art
The value proposition of algae technical metrics was the subject of a recent, industry-led, Focus Group interactive discussion. The interactive platform allowed for real time capturing and priority ranking of the topics that are deemed critical challenges for a future successful algae-based bioeconomy. This work ultimately sets the stage for providing guidance, methods, and standard reference materials tailored to respective algae industry segments for the cultivation, processing and marketing of high-quality and safe algae-based products. The group solicits input from the broader algae community on the value proposition and presents a case here to build a consensus around algae-specific metrics. The value proposition of technical standards to the industry is that guidance obtained through these collaborations builds producers' and consumers' trust that algae and algae-derived products are safe, reliable, and may allow for expanded market access, and increased competitiveness and international trade.
Power market models for the clean energy transition: State of the art and future research needs
As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.
Unlocking the secret of lignin-enzyme interactions: Recent advances in developing state-of-the-art analytical techniques
Bioconversion of renewable lignocellulosics to produce liquid fuels and chemicals is one of the most effective ways to solve the problem of fossil resource shortage, energy security, and environmental challenges. Among the many biorefinery pathways, hydrolysis of lignocellulosics to fermentable monosaccharides by cellulase is arguably the most critical step of lignocellulose bioconversion. In the process of enzymatic hydrolysis, the direct physical contact between enzymes and cellulose is an essential prerequisite for the hydrolysis to occur. However, lignin is considered one of the most recalcitrant factors hindering the accessibility of cellulose by binding to cellulase unproductively, which reduces the saccharification rate and yield of sugars. This results in high costs for the saccharification of carbohydrates. The various interactions between enzymes and lignin have been explored from different perspectives in literature, and a basic lignin inhibition mechanism has been proposed. However, the exact interaction between lignin and enzyme as well as the recently reported promotion of some types of lignin on enzymatic hydrolysis is still unclear at the molecular level. Multiple analytical techniques have been developed, and fully unlocking the secret of lignin-enzyme interactions would require a continuous improvement of the currently available analytical techniques. This review summarizes the current commonly used advanced research analytical techniques for investigating the interaction between lignin and enzyme, including quartz crystal microbalance with dissipation (QCM-D), surface plasmon resonance (SPR), attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, atomic force microscopy (AFM), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy (FLS), and molecular dynamics (MD) simulations. Interdisciplinary integration of these analytical methods is pursued to provide new insight into the interactions between lignin and enzymes. Finally, this review will serve as a resource for future research seeking to develop new methodologies for a better understanding of the basic mechanism of lignin-enzyme binding during the critical hydrolysis process.
Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.
Novel application of the modal strain energy technique for state-of-the-art damping predictions
Structural damping, which measures the energy dissipation of a vibrating structure, is a key modeling input for lightweight structures but is notoriously hard to predict. This work utilizes vibration-based measurements of centimeter-scale coupons and the modal strain energy approach to predict structural damping of a lightly damped structure. The approach was originally validated with panels shorter than a meter in length. This work extends the validation to a 2.75 m beam made of unidirectional and biaxial glass fiber laminates bonded by adhesive. The comparison between three-dimensional finite element model predictions and full-scale experimental measurements of damping show an average error of 5.2% for the first five modes. Additionally, the modal strain energy approach is newly applied with a one-dimensional geometrically exact beam theory model and a two-dimensional sectional analysis solver. This beam approach accurately predicts the damping behavior of the first bending modes but loses accuracy for higher order modes that are dominated by three-dimensional effects. This novel approach provides faster simulations while allowing arbitrary beam cross sections. The paper also investigates traditional and high-force dynamic mechanical analysis to measure structural damping of coupons. Both alternatives show significant errors in attempted validation against the theoretical thermoelastic damping of aluminum coupons.