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At least 271 records · Page 15

Reshaping the Quantum Arrow of Time

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum control tools that can yield dynamics more consistent with time flowing backward than forward. The control tools are based on the explicit construction of a Hamiltonian that can replicate the stochastic trajectories of a monitored quantum system. Such a Hamiltonian can reverse the effect of monitoring and, via a feedback process, generate trajectories consistent with a reversed arrow of time. It can also be used to simulate the backward-in-time dynamics of an open quantum system. Finally, we design a feedback-driven continuous measurement engine powered by the energy pumped into the system by the monitoring process. We show that the engine can operate under experimentally realizable conditions with feedback delay and finite-efficiency measurements.

Entropy production↗

ASSESSING THE EFFECTIVENESS OF ULTRASONIC IMPACT TREATMENT ON RESIDUAL STRESS PROFILES IN DISSIMILAR WELDED JOINTS

Residual stresses (RS) induced during welding processes are a critical concern in materials engineering, as they can significantly impair the mechanical performance of components by reducing fatigue strength and tensile load capacity. This challenge is especially pronounced in dissimilar metal welds (DMWs), where variations in thermal expansion properties between the joined alloys exacerbate the formation of tensile RS. Conventional post-weld heat treatments, though effective for homogeneous materials, often require substantial energy, specialized equipment, and extensive processing time, making them less practical for DMW applications. Thus, there is a clear need for innovative, energy-efficient techniques to mitigate these detrimental stresses. This study investigates ultrasonic impact treatment (UIT) as a possible alternative for mitigating tensile RS in both similar and dissimilar metal welds. To evaluate UIT’s effectiveness, neutron diffraction (ND) was employed as a nondestructive technique to quantify RS in three orthogonal directions—longitudinal, transverse, and normal. The results showed that UIT significantly reduced peak tensile RS, particularly in the longitudinal direction, by up to 180 MPa in similar welds and up to 150 MPa in dissimilar welds. Given the limited literature on UIT application in DMWs, this work contributes valuable data on stress redistribution mechanisms and highlights UIT’s potential as a practical stress-relief method. The findings lay the groundwork for further investigations aimed at optimizing process parameters and understanding long-term performance in welded joints.

EisaZadeh, Hamid [Western Carolina University, Cul↗

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

Phase transition in two-dimensional monolayer (1L)-molybdenum disulfide induced by atomic S-basal plane gliding via synchrotron X-ray monochromatic beam radiation for superior electronic performance

Here, in this work, we report a novel approach to reduce the channel resistance by inducing a phase transition behavior from 2H to 1T in a monolayer MoS 2 (1L-MoS 2 ) by a synchrotron X-ray monochromatic beam (mono-beam) radiation. The effects of the biphase structure by the mono-beam on the 1L-MoS2 film were investigated using Raman spectra, photoluminescence (PL) spectra, scanning tunneling microscopy, and scanning tunneling spectroscopy, respectively. Through material characterization, we identified that the lateral sliding of S-vacancies along the S-plane in the 1L-MoS 2 is the key reason for the origin of unidirectional phase transition. The precise phase engineering triggered by the mono-beam radiation process allows the realization of field-effect transistors (FET) with 2X improvement in mobility toward a high on/off ratio (~10 8 ) and a near-ideal subthreshold swing of ~88 mV per decade. The validity of the phase engineering could be further extended for its application as a memory device, exhibiting a gate tunable conduction modulation behavior and a high resistance ratio of ~10 2 at a gate bias of 5 V with endurance of ~100 cycles. Furthermore, an artificial neural network using the synaptic weight update with accuracy of ~93 % was achieved.

36 MATERIALS SCIENCE↗

Engineered reduction of S-adenosylmethionine alters lignin in sorghum

Abstract Background Lignin is an aromatic polymer deposited in secondary cell walls of higher plants to provide strength, rigidity, and hydrophobicity to vascular tissues. Due to its interconnections with cell wall polysaccharides, lignin plays important roles during plant growth and defense, but also has a negative impact on industrial processes aimed at obtaining monosaccharides from plant biomass. Engineering lignin offers a solution to this issue. For example, previous work showed that heterologous expression of a coliphage S -adenosylmethionine hydrolase (AdoMetase) was an effective approach to reduce lignin in the model plant Arabidopsis. The efficacy of this engineering strategy remains to be evaluated in bioenergy crops. Results We studied the impact of expressing AdoMetase on lignin synthesis in sorghum ( Sorghum bicolor L. Moench). Lignin content, monomer composition, and size, as well as biomass saccharification efficiency were determined in transgenic sorghum lines. The transcriptome and metabolome were analyzed in stems at three developmental stages. Plant growth and biomass composition was further evaluated under field conditions. Results evidenced that lignin was reduced by 18% in the best transgenic line, presumably due to reduced activity of the S -adenosylmethionine-dependent O -methyltransferases involved in lignin synthesis. The modified sorghum features altered lignin monomer composition and increased lignin molecular weights. The degree of methylation of glucuronic acid on xylan was reduced. These changes enabled a ~20% increase in glucose yield after biomass pretreatment and saccharification compared to wild type. RNA-seq and untargeted metabolomic analyses evidenced some pleiotropic effects associated with AdoMetase expression. The transgenic sorghum showed developmental delay and reduced biomass yields at harvest, especially under field growing conditions. Conclusions The expression of AdoMetase represents an effective lignin engineering approach in sorghum. However, considering that this strategy potentially impacts multiple S -adenosylmethionine-dependent methyltransferases, adequate promoters for fine-tuning AdoMetase expression will be needed to mitigate yield penalty.

Tian, Yang↗

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into “Beyond CMOS” and “More than Moore” paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. Finally, the outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

36 MATERIALS SCIENCE↗

Accelerating Discovery to Deployment: Argonne's Materials Engineering Research Facility (MERF) and Its Role in Scaling Materials Technologies for Water and Resource Solutions

The U.S. Department of Energy (DOE) national laboratories represent a unique class of government‐owned, contractor‐operated research institutions dedicated to conducting research and development (R&D) related activities that address national priorities, supporting and advancing the DOE mission. They play a vital role in sustaining U.S. innovation capacity, stewarding the nation's technical base, and nurturing science and technologies. In this perspective, we highlight the processing science and scaleup capabilities of the Materials Engineering Research Facility (MERF) at DOE's Argonne National Laboratory to demonstrate how DOE National Laboratories bridge fundamental science and applied technology development to accelerate deployment. Case studies are presented on selective membranes for critical mineral recovery, sensors for per‐ and polyfluoroalkyl substances (PFAS) detection, surface functionalization via atomic layer deposition (ALD) and sequential infiltration synthesis (SIS), and lithium recovery from battery recycling waste streams using a novel electrodialysis process. These examples underscore MERF's role in translating innovative technologies into practical solutions for renewable water and critical resource recovery, which also leverage Argonne's analytical and computational capabilities. This perspective also outlines mechanisms for collaborating with the DOE national laboratories to strengthen partnerships across government, the national laboratories, academia, and industry.

36 MATERIALS SCIENCE↗

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗

Microbial valorization of lignin to malic acid by Aspergillus niger

Lignin is the largest renewable source of aromatic carbon, yet its heterogeneity and recalcitrance limit its use in higher-value bioconversion processes. In this study, Aspergillus niger was engineered to enable the bioconversion of lignin-derived aromatics and base-catalyzed depolymerized (BCD) lignin streams into malic acid, a value-added C4 dicarboxylic acid with broad industrial relevance. Overexpression of the C4 dicarboxylate transporter C4T318 from Aspergillus oryzae enhanced malic acid secretion, while medium optimization under buffered conditions further improved the production. The engineered strain efficiently assimilated representative lignin-derived aromatics, including 4-hydroxybenzoic acid and p-coumaric acid, producing up to 3.9 g/L malic acid. Conversion of BCD lignin liquors from poplar and sorghum demonstrated effective utilization of heterogeneous aromatic mixtures, generating up to 0.82 g/L malic acid. This work demonstrates direct fungal conversion of real lignin streams into malic acid and establishes A. niger as a promising platform for sustainable lignin valorization.

Aromatic bioconversion↗

Bound Exciton Complexes in Near-Infrared Emitting Quantum Shells

Near-infrared (NIR) light sources based on colloidal semiconductor nanocrystals (NCs) represent a scalable, low-cost alternative to epitaxial semiconductor platforms. However, their performance remains hindered by rapid Auger recombination, a problem that is particularly pronounced in narrow-bandgap materials. Here, we report on CdS/HgS/CdS and CdS/HgCdSe/ ZnS quantum shells (QSs), a class of spherical quantum wells specifically engineered for a suppression of nonradiative Auger processes. Fabricated QSs exhibit tunable NIR emission with photoluminescence quantum yields reaching ∼60% below 1000 nm and up to 30% near 1300 nm. Optical gain and stimulated emission were observed in CdS/HgS/CdS QSs. In contrast, CdS/HgCdSe/ZnS QSs displayed a photoinduced absorption in lieu of optical gain despite demonstrating a comparatively stronger Auger suppression. Transient absorption spectroscopy revealed that this phenomenon arises from the formation of bound multiexciton complexes that induce long-lived sub-bandgap multiexciton states. The observation of such bound excitonic clusters at room temperature offers a pathway toward nonlinear NIR photonic phenomena, including biexciton−exciton cascade emission, optical modulation, and singleexciton gain.

Auger recombination↗

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

Lotus japonicus↗

Electromagnetic Modeling of Lattice Structures in Additively Manufactured Electric Machines

Recent advancements in metal additive manufacturing (AM) show great potential to revolutionize the design and manufacturing of electromagnetic components used in the field of electrical engineering. Lattice structures directly printed by AM processes typically offer better structural performance with reduced weight, such as high stiffness, surface area, elongation, energy absorption, and porosity, than the solid counterpart. This paper aims to study the electromagnetic modeling of lattice structures used in additively manufactured magnetic cores or windings for electric machines. Three dimensional (3D) electromagnetic finite element (FE) analysis with high performance computing (HPC) shows the highest fidelity in predicting the electromagnetic performance of designs with lattice structures by preserving complex geometry details. FE-based homogenization methods have also been explored to potentially speed up concept design. A case study based on an additively manufactured axial-flux permanent magnet machine with a Hilbert pattern stator validates the discussed electromagnetic modeling approaches.

Chung, Shi-Uk [ANSYS, Inc.]↗

Guest Editorial for Nondestructive Testing and Evaluation (NDT&E) Special Section

Nondestructive testing and evaluation (NDT&E) are interdisciplinary fields that require a significant amount of interconnection between fundamental physics, measurement techniques, data processing, decision making, and reporting to have a significant impact on industry. NDT&E practitioners are challenged to keep up with the fast-paced evolution of materials, structures, processing, and manufacturing technologies. The development of engineered materials, complex structures and composites, and novel forming techniques require NDT&E to rapidly evolve to meet the needs of industry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Broadband 920-nm mirror thin film damage competition

The 2023 Laser Damage conference thin-film damage competition was devoted to a survey on the state-of-the-art broadband near-IR multilayer dielectric (MLD) mirrors designed for ultra-short pulsed laser applications. The requirements for the coatings were a minimum reflection of 99.5% at 45-deg incidence angle for S-polarization from 830 nm to 1010 nm and group delay dispersion (GDD) < ± 50fs 2 . The participants were allowed to select the coating materials, coating design, and coating deposition method. Samples were damage tested at a single testing facility to enable direct comparison among the participants using a 25 ± 5 fs optical parametric chirped-pulse amplification (OPCPA) laser system operating at 5 Hz. The testing results from this set of 37 samples showed that dense coatings by ion-beam sputtering (IBS), magnetron sputtering (MS), and electron-beam ion assisted deposition (e-beam IAD) exhibited highest damage initiation onset (laser-induced damage threshold or LIDT) while e-beam coatings were low performers. In addition, multilayer coatings using tantala and/or hafnia as high index materials were top performers. Furthermore, this competition included for the first time the measurement of the damage growth onset (laser-induced damage growth threshold or LDGT). This latter performance metric plays an important role in establishing the safe operational conditions for larger aperture ultrashort pulsed lasers. Information pertaining to the morphology of the damage sites and their evolution under subsequent exposure to different laser fluences leading to damage growth is presented. Finally, not all coating samples in the survey met the GDD requirements stated above and associated measurements are discussed in the context of the present and past thin-film damage competitions focused on similar broadband near-IR MLD coatings.

23 broadband high reflectors↗

The Oak Ridge National Laboratory Glenn T. Seaborg Institute: 2025 highlights

The Glenn T. Seaborg Institute (GTSI) at Oak Ridge National Laboratory (ORNL) serves as a dedicated hub for advancing actinide R&D, aimed at strengthening the United States’ capabilities in actinide science. With a focus on medical, industrial, and national security applications, the ORNL GTSI seeks to foster the next generation of scientists and engineers. Collaborating closely with corresponding Seaborg Institutes at Lawrence Livermore National Laboratory (LLNL), Lawrence Berkeley National Laboratory (LBNL), Los Alamos National Laboratory (LANL), and Idaho National Laboratory, the ORNL GTSI leverages its unique strengths. These include unparalleled expertise in isotope production, handling of rare isotopes, and leadership in neutron and computational sciences. Notably, the ORNL GTSI is positioned as the nation’s cornerstone for actinide R&D, capitalizing on the exceptional capabilities of the High Flux Isotope Reactor—the premier reactor for isotope production—and the Hazard Category 2 Radiochemical Engineering Development Center, which supports advanced production, processing, and applications research. Furthermore, the GTSI is committed to serving as a national center of excellence for training across all levels of actinide science education. This report provides an overview of the activities, milestones, and accomplishments of the ORNL GTSI over the past year.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

An automated integrated web-based smart tool for open stope design

The Stability Graph is a widely used tool for the design of open stopes in underground mining. Many users of the Stability Graph still apply this design method manually. Although the manual approach has benefits, using multiple graphs and stability number computation charts for each stope surface is time-consuming, even for the experienced mining engineer. Current practice in the use of the method also limits data sharing. This paper presents a StopeSoft web-based tool for open stope stability prediction that is developed on the basis of the Stability Graph method and is available at openstope.com. StopeSoft incorporates flexibility in terms of Stability Graph options and incorporates additional critical factors often overlooked. As a web-based tool, StopeSoft encourages and makes data sharing possible globally, focused on expanding the database and improving the current limitations of the Stability Graph to provide practical, reliable solutions for mining engineers, consultants, and academics. The StopeSoft automated process facilitates the process of open stope stability prediction, saving time and minimizing potential human errors. Statistical treatment of the data accounts for the variability of input parameters to emphasize the probabilistic nature of the Stability Graph method. The probabilistic interpretation of the stability states of stope surfaces eliminates the false feeling of absolute stope performance based on its location on the Stability Graph , as implied by the deterministic approach.

58 GEOSCIENCES↗