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At least 451 records · Page 25

Resolving the mystery of electron perpendicular temperature spike in the plasma sheath

A large family of plasmas has collisional mean-free-path much longer than the non-neutral sheath width, which scales with the plasma Debye length. The plasmas, particularly the electrons, assume strong temperature anisotropy in the sheath. The temperature in the sheath flow direction (Te∥) is lower and drops toward the wall as a result of the decompressional cooling by the accelerating sheath flow. The electron temperature in the transverse direction of the flow field (Te⊥) not only is higher but also spikes up in the sheath. This abnormal behavior of Te⊥ spike is found to be the result of a negative gradient of the parallel heat flux of transverse degrees of freedom (qes) in the sheath. The non-zero heat flux qes is induced by pitch-angle scattering of electrons via either their interaction with self-excited electromagnetic waves in a nearly collisionless plasma or Coulomb collision in a collisional plasma, or both in the intermediate regime of plasma collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ∼12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

97 MATHEMATICS AND COMPUTING↗

Utilisation of spatial derivative measurements in circular diffuse optical tomographic imaging to improve image resolution and contrast

The resolution of images recovered using diffuse optical tomography without spatial prior information is inherently limited due to the diffusive nature of light transport in scattering dominated biological tissue. Several studies have previously reported an improvement in depth sensitivity in near infrared spectroscopy by considering the subtraction of two neighbouring measurements. A nearest neighbour, spatial derivative based algorithm is presented, in which the difference between neighbouring source-sharing source – detector pairs is considered for tomographic reconstruction. Using a circular, inward-facing optode geometry, it is shown that deeper abnormalities in oxyhaemoglobin, deoxyhaemoglobin and water can be recovered with better localisation and contrast as compared to reconstructing using absolute values of multi-wavelength data. Relative improvements of up to 25 % in quantitative accuracy of recovered physiological values are demonstrated at better resolution for cancerous tissue in a heterogeneous breast model, when using this proposed spatial derivative based parameter reconstruction. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hedgehog–FGF signaling axis patterns anterior mesoderm during gastrulation

Significance Anterior–posterior axis patterning is a fascinating but poorly understood developmental process. Single-cell sequencing was utilized to interrogate patterning abnormalities in a mesoderm-specific Hedgehog (Hh) pathway mutant, which revealed selective anterior mesoderm defects. We found that Hh signaling was required for fibroblast growth factor (FGF) pathway activity in nascent mesoderm during gastrulation. Mouse genetics, cell biology, and genomic experiments indicate that FGF signaling acts downstream of Hh signaling in nascent mesoderm for anterior mesoderm morphogenesis. This work demonstrates the utility of applying single-cell technologies to resolve complex developmental phenotypes. Here, it revealed a role for Hh signaling from the node in organizing anterior mesoderm morphogenesis, independent of its role in left–right determination, by promoting FGF signaling in gastrulating mesoderm.

Guzzetta, Alexander↗

A partially disordered region connects gene repression and activation functions of EZH2

Enhancer of Zeste Homolog 2 (EZH2) is the catalytic subunit of Polycomb Repressive Complex 2 (PRC2), which minimally requires two other subunits, EED and SUZ12, for enzymatic activity. EZH2 has been traditionally known to mediate histone H3K27 trimethylation, a hallmark of silent chromatin. Emerging evidence indicates that EZH2 also activates gene expression in cancer cells in a context distinct from canonical PRC2. The molecular mechanism underlying the functional conversion of EZH2 from a gene repressor to an activator is unclear. In this work, we show that EZH2 harbors a hidden, partially disordered transactivation domain (TAD) capable of interacting with components of active transcription machinery, mimicking archetypal acidic activators. The EZH2 TAD comprises the SRM (Stimulation-Responsive Motif) and SANT1 (SWI3, ADA2, N-CoR, and TFIIIB 1) regions that are normally involved in H3K27 methylation. The crystal structure of an EZH2–EED binary complex indicates that the EZH2 TAD mediates protein oligomerization in a noncanonical PRC2 context and is entirely sequestered. The EZH2 TAD can be unlocked by cancer-specific EZH2 phosphorylation events to undergo structural transitions that may enable subsequent transcriptional coactivator binding. The EZH2 TAD directly interacts with the transcriptional coactivator and histone acetyltransferase p300 and activates gene expression in a p300-dependent manner in cells. The corresponding TAD may also account for the gene activation function of EZH1, the paralog of EZH2. Distinct kinase signaling pathways that are known to abnormally convert EZH2 into a gene activator in cancer cells can now be understood in a common structural context of the EZH2 TAD.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for Zika envelope domain III recognition by a germline version of a recurrent neutralizing antibody

Recent epidemics demonstrate the global threat of Zika virus (ZIKV), a flavivirus transmitted by mosquitoes. Although infection is usually asymptomatic or mild, newborns of infected mothers can display severe symptoms, including neurodevelopmental abnormalities and microcephaly. Given the large-scale spread, symptom severity, and lack of treatment or prophylaxis, a safe and effective ZIKV vaccine is urgently needed. However, vaccine design is complicated by concern that elicited antibodies (Abs) may cross-react with other flaviviruses that share a similar envelope protein, such as dengue virus, West Nile virus, and yellow fever virus. This cross-reactivity may worsen symptoms of a subsequent infection through Ab-dependent enhancement. To better understand the neutralizing Ab response and risk of Ab-dependent enhancement, further information on germline Ab binding to ZIKV and the maturation process that gives rise to potently neutralizing Abs is needed. In this work, we use binding and structural studies to compare mature and inferred-germline Ab binding to envelope protein domain III of ZIKV and other flaviviruses. We show that affinity maturation of the light-chain variable domain is important for strong binding of the recurrent VH3-23/VK1-5 neutralizing Abs to ZIKV envelope protein domain III, and identify interacting residues that contribute to weak, cross-reactive binding to West Nile virus. These findings provide insight into the affinity maturation process and potential cross-reactivity of VH3-23/VK1-5 neutralizing Abs, informing precautions for protein-based vaccines designed to elicit germline versions of neutralizing Abs.

59 BASIC BIOLOGICAL SCIENCES↗

Designing electrolytes with polymerlike glass-forming properties and fast ion transport at low temperatures

Significance Liquid electrolytes with thermophysical properties analogous to solid polymers, but with exceptional liquidlike ionic conductivities, are formed spontaneously when moderate amounts (≤1 M) of inorganic salts coordinate strongly with small molecules in a conventional aprotic solvent. Specifically, we report that electrolytes composed of the cyclic liquid ether, dioxolane (DOL), and containing the simple salt LiNO 3 are able to completely bypass the liquid → crystalline solid thermal transition, and to exhibit abnormally high bulk and interfacial ionic conductivities down to temperatures as low as −50 °C. Through physical, spectroscopic, and ion-transport measurements it is shown that strong interactions between LiNO 3 and DOL distort bonds in DOL, couple motions of individual solvent molecules, and lower the thermodynamic activity of the electrolyte.

36 MATERIALS SCIENCE↗

HP1-driven phase separation recapitulates the thermodynamics and kinetics of heterochromatin condensate formation

The spatial segregation of pericentromeric heterochromatin (PCH) into distinct, membrane-less nuclear compartments involves the binding of Heterochromatin Protein 1 (HP1) to H3K9me2/3-rich genomic regions. While HP1 exhibits liquid–liquid phase separation properties in vitro, its mechanistic impact on the structure and dynamics of PCH condensate formation in vivo remains largely unresolved. Here, using a minimal theoretical framework, we systematically investigate the mutual coupling between self-interacting HP1-like molecules and the chromatin polymer. We reveal that the specific affinity of HP1 for H3K9me2/3 loci facilitates coacervation in nucleo and promotes the formation of stable PCH condensates at HP1 levels far below the concentration required to observe phase separation in purified protein assays in vitro. These heterotypic HP1–chromatin interactions give rise to a strong dependence of the nucleoplasmic HP1 density on HP1-H3K9me2/3 stoichiometry, consistent with the thermodynamics of multicomponent phase separation. The dynamical cross talk between HP1 and the viscoelastic chromatin scaffold also leads to anomalously slow equilibration kinetics, which strongly depend on the genomic distribution of H3K9me2/3 domains and result in the coexistence of multiple long-lived, microphase-separated PCH compartments. The morphology of these complex coacervates is further found to be governed by the dynamic establishment of the underlying H3K9me2/3 landscape, which may drive their increasingly abnormal, aspherical shapes during cell development. These findings compare favorably to 4D microscopy measurements of HP1 condensate formation in live Drosophila embryos and suggest a general quantitative model of PCH formation based on the interplay between HP1-based phase separation and chromatin polymer mechanics.

3D genomics↗

A biophysical framework for double-drugging kinases

Selective orthosteric inhibition of kinases has been challenging due to the conserved active site architecture of kinases and emergence of resistance mutants. Simultaneous inhibition of distant orthosteric and allosteric sites, which we refer to as “double-drugging”, has recently been shown to be effective in overcoming drug resistance. However, detailed biophysical characterization of the cooperative nature between orthosteric and allosteric modulators has not been undertaken. Here, we provide a quantitative framework for double-drugging of kinases employing isothermal titration calorimetry, Förster resonance energy transfer, coupled-enzyme assays, and X-ray crystallography. We discern positive and negative cooperativity for Aurora A kinase (AurA) and Abelson kinase (Abl) with different combinations of orthosteric and allosteric modulators. We find that a conformational equilibrium shift is the main principle governing cooperativity. Notably, for both kinases, we find a synergistic decrease of the required orthosteric and allosteric drug dosages when used in combination to inhibit kinase activities to clinically relevant inhibition levels. X-ray crystal structures of the double-drugged kinase complexes reveal the molecular principles underlying the cooperative nature of double-drugging AurA and Abl with orthosteric and allosteric inhibitors. Finally, we observe a fully closed conformation of Abl when bound to a pair of positively cooperative orthosteric and allosteric modulators, shedding light on the puzzling abnormality of previously solved closed Abl structures. Collectively, our data provide mechanistic and structural insights into rational design and evaluation of double-drugging strategies.

59 BASIC BIOLOGICAL SCIENCES↗

High-Fidelity Modeling and Experiments to Inform Safety Analysis Codes for Heat Pipe Microreactors

Heat pipe microreactors are reactor designs that primarily use liquid-metal heat pipes to cool the core. The main interest in heat pipes is the fact that they can remove heat passively. This, along with the use of liquid metal, allows the reactor to operate at higher temperatures. Although the use of heat pipes in nuclear reactors is new, liquid-metal heat pipe technology is mature. Nevertheless, experimental data on heat pipes are scarce, and very little is known about their behavior during abnormal operations and close to their thermal limits. Therefore, new experiments and accurate heat pipe simulations are needed to develop reliable closure models. This work describes a joint experimental and numerical investigation into heat pipes that attempts an initial closure of this gap. Further, the numerical and experimental efforts are currently proceeding in parallel, aimed at different aspects of heat pipes. The numerical part is focused on gaps in local closures, and the experiments capture the overall heat pipe behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Opportunities, Challenges, and Research Needs for Remote Microreactor Operations

As the nuclear industry develops new advanced reactor technologies, many companies are embracing this advancement by pursuing the development of microreactors. The term microreactor generally refers to a nuclear reactor with an operating power of 20 MW(thermal) or less. The power range of microreactors makes them appealing for many use cases, such as powering remote communities, mining sites, and military bases. Most of the microreactor designs being pursued are expected to incorporate remote facility operations into the final product. However, no framework has yet been developed to determine what remote operations systems require for reliable, resilient, and secure operation of a microreactor. Here, this work identifies the research needs for challenges that are unique to remote operations and monitoring for microreactors, specifically regarding instrumentation and control, communication methods, regulatory requirements, and operational policies. The types of commands and sensor measurements that must be transmitted between the facilities, as well as methods for verifying the trustworthiness of these signals, are assessed. This work evaluates the security, reliability, and performance requirements that must be met when considering the selection of communication hardware and protocols for use in remote operations. Also, an assessment was performed to study how remote operations fit within current regulatory requirements and what may need to be updated in regulatory policy to allow for remote operation. Finally, the operational contingencies unique to remote operations that must be in place for responses to abnormal events are identified. This paper identifies the challenges and research opportunities within the areas of importance for the design of remote operation systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗

Statistical Modeling and Analysis of k -Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes

Two-dimensional layered materials/flakes, also known as crystalline atom-thick layer nanosheets, have recently been receiving great attention in electronics fabrication due to their unique and intriguing properties. The k-layer coverage area (i.e., the area covered by k number of overlapping layers) of the printed flake pattern significantly impacts on the properties of the printed electronics. In this work, we constructed a statistical model to describe the k-layer coverage of randomly distributed two-dimensional materials. A series of results are obtained to provide not only the expectation but also the variance of the coverage area. The boundary effects on the random flakes coverage are also studied. In addition, an approximated statistical testing approach is also developed in this work to detect abnormal coverage patterns. Furthermore, the case studies based on simulated data and real flakes images obtained from the inkjet printing process demonstrate the accuracy and effectiveness of the proposed model and analysis methods.

36 MATERIALS SCIENCE↗

Structure-Spin-Transport Anomaly in Quasi-One-Dimensional Ba9Fe3Te15 under High Pressure

Recently, a series of novel compounds Ba3MX5 (M= Fe, Ti, V; X=Se, Te) with hexagonal crystal structures composed of quasi-1-dimensional (1D) magnetic chains has been synthesized by our research team using high-pressure and high-temperature methods. The initial hexagonal phases persist to the maximum achievable pressure, while spin configurations and magnetic interactions may change dramatically as a result of considerable reductions in interchain separations upon pressurization. These compounds therefore offer unique possibilities for studying the evolution of intrinsic electronic structures in quasi-1D magnetic systems. Here we present a systematic investigation of Ba9Fe3Te15, in which the interchain separations between trimerized 1D chains (~10.2 Å) can be effectively modulated by external high pressure. The crystal structure especially along the 1D chains exhibits an abnormal expansion at ~5GPa, which accompanies trimerization entangled anomalous mixed-high-low spin transition. An insulator-metal transition has been observed under high pressure as a result of charge-transfer gap closing. Pressure-induced superconductivity emerges at 26GPa, where the charge-transfer gap fully closes, 3D electronic configuration forms and local spin fully collapses.

Zhang, Jun↗

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗

Runaway electron-induced plasma facing component damagein tokamaks

This Roadmap article addresses the critical and multifaceted challenge of plasma facing component (PFC) damage caused by runaway electrons (REs) in tokamaks, a phenomenon that poses a significant threat to the viability and longevity of future fusion reactors such as ITER and DEMO. The dramatically increased RE production expected in future high-current tokamaks makes it very difficult to avoid or mitigate REs in such devices when a plasma discharge terminates abnormally. Preventing damage from the intense localised heat loads they can cause requires a holistic approach that considers plasma, REs and PFC damage. Despite decades of progress in understanding the physics of REs and the thermomechanical response of PFCs separately, their complex interplay remains poorly understood. This document aims to initiate a coordinated, interdisciplinary approach to bridge this gap by reviewing experimental evidence, advancing diagnostic capabilities, and improving modelling tools across different scales, dimensionalities, and fidelities. Key topics include RE beam formation and transport, damage mechanisms in both brittle and metallic PFCs, and observed effects in major facilities such as JET, DIII-D, WEST and EAST. The Roadmap emphasises the urgency of predictive, high-fidelity modelling validated against well-diagnosed controlled experiments, particularly in the light of recent changes in ITER’s wall material strategy and the growing importance of private sector fusion initiatives. Each section of the Roadmap article is written to provide a concise overview of one area of this multidisciplinary subject, with an assessment of the status, a look at current and future challenges, and a brief summary. The ultimate goal of this initiative is to guide future mitigation strategies and design resilient components that can withstand the intense localised loads imposed by REs, thus ensuring the safe and sustainable operation of the next generation of fusion power plants.

Ratynskaia, Svetlana [KTH Royal Inst. of Technolog↗

Review of the gas breakdown physics and nanomaterial-based ionization gas sensors and their applications

Ionization gas sensors are ubiquitous tools that can monitor desired gases or detect abnormalities in real time to protect the environment of living organisms or to maintain clean and/or safe environment in industries. The sensors’ working principle is based on the fingerprinting of the breakdown voltage of one or more target gases using nanostructured materials. Fundamentally, nanomaterial-based ionization-gas sensors operate within a large framework of gas breakdown physics; signifying that an overall understanding of the gas breakdown mechanism is a crucial factor in the technological development of ionization gas sensors. Moreover, many studies have revealed that physical properties of nanomaterials play decisive roles in the gas breakdown physics and the performance of plasma-based gas sensors. Based on this insight, this review provides a comprehensive description of the foundation of both the gas breakdown physics and the nanomaterial-based ionization-gas-sensor technology, as well as introduces research trends on nanomaterial-based ionization gas sensors. The gas breakdown is reviewed, including the classical Townsend discharge theory and modified Paschen curves; and nanomaterial-based-electrodes proposed to improve the performance of ionization gas sensors are introduced. The secondary electron emission at the electrode surface is the key plasma–surface process that affects the performance of ionization gas sensors. Finally, we present our perspectives on possible future directions.

nanomaterial-based gas breakdown characteristics↗