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Abstract Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.
Solid additives are crucial in layer-by-layer (LBL) polymer solar cells (PSCs). Despite its importance, the simultaneous application of solid additives into both donor and acceptor layers has been largely overlooked. In this work, two multifunctional solid additives are actively designed, and investigated the synergistic effect on both donor and acceptor layers. Incorporating the multifunctional solid additives into the donor layer could effectively enhance the aggregation and molecular stacking of the donor polymer, leading to reduced energy disorder and minimizing ΔE 2 . When the multifunctional solid additives are introduced into the acceptor layer, they just play a role in optimizing the morphology, thereby reducing the ΔE 3 . Excitedly, the simultaneous addition of the multifunctional solid additives into both donor and acceptor layers produced a synergistic effect for decreasing ΔE 2 and ΔE 3 simultaneously, especially adding SA2, thus enabling an excellent power conversion efficiency (PCE) of 19.95% (certified as 19.68%) with an open-circuit voltage (V oc ) of 0.921 V, a short circuit current density (J sc ) of 27.08 mA cm -2 and a fill factor (FF) of 79.98%. The work highlights the potential of multifunctional solid additives in independently regulating the properties of donor and acceptor layers, which is expected as a promising approach for further developing higher performance PSCs.
Nickel-based alloys are leading contenders for use as structural materials in molten salt reactors. While there have been extensive studies on the impact of fluoride/chloride-based molten salt corrosion on the microstructural evolution of various nickel-based alloys, the effects of simultaneous molten salt corrosion and radiation on the mechanical integrity of grain boundaries (GBs) remain underexplored. In this study, we use a Ni-20Cr model alloy to investigate this issue, subjecting it to simultaneous molten fluoride salt corrosion and proton irradiation. We performed cross-sectional and chemically-sensitive electron microscopy characterization of the microstructures of these materials, identifying the characteristic corrosion-induced microstructure and local chemical heterogeneity near GBs. After developing a sample preparation method for reliable characterization of GB strength, we assess the mechanical degradation of GBs using in situ push-to-pull micro tensile tests. Our findings reveal that voids induced by corrosion are the primary influence on the failure mode of GBs, regardless of whether proton irradiation is present. For materials that exhibit ductile fracture, those subjected to simultaneous corrosion and radiation exhibit lower yield strengths than those exposed to corrosion alone, which may be linked to the previously observed phenomenon of proton irradiation-decelerated intergranular corrosion in molten salt.
Nuclear energy is a promising low-carbon energy candidate to meet the increased demand for green energy, where the integration of fuel recycling can have significant benefits for material usage and waste reduction. Utilizing in situ monitoring tools can provide ample opportunities to better control and safeguard nuclear material recycle processes while also offering knowledge and insight into real-time solution properties. The simultaneous measurement of analytical targets in multiple process locations can enable real-time mass balance and material accountancy calculations. This is demonstrated here with a mass balance study of Nd 3+ on countercurrent aqueous/organic metal extraction within a single centrifugal contactor. The Nd 3+ concentration was simultaneously monitored at the inlets and outlets of both aqueous and organic phases using a visible absorbance detector that allowed for the simultaneous measurement of up to six locations. The Nd 3+ concentration was calculated by using chemical data science algorithms, where model training sets were collected on a single track of the detector. The discussion includes addressing the challenges of using a model collected on a single track and applying it as a model across the other tracks on the detector. Each track of the detector corresponds to one measurement location on the contactor. The difference in the integrated moles of Nd 3+ between the inlet and outlet at the end of the experiment was near zero, indicating that the mass balance of this experiment was maintained. Overall, the online spectroscopic monitoring was able to follow changing solution conditions and accurately measure the concentration of Nd 3+ in different locations within the contactor system.
The position of mobile active and inactive ions, specifically ion insertion sites, within organic crystals, significantly affects the properties of organic materials used for energy storage and ionic transport. Identifying the positions of these atomic (and ionic) sites in an organic crystal is challenging, especially when the element has low X-ray scattering power, such as lithium (Li) and hydrogen, which are difficult to detect by powder X-ray diffraction. First-principles calculations, exemplified by density functional theory (DFT), are very practical for confirming the relative stability of ion positions in materials. However, the lack of effective strategies to identify ion sites in these organic crystalline frameworks renders this task extremely challenging. This work presents two algorithms: the (i) efficient location of ion insertion sites from extrema in electrostatic local potential and charge density (ELIISE), and the (ii) ElectRostatic InsertioN (ERIN), which leverage charge density and electrostatic potential fields accessed from first-principles calculations, combined with the Simultaneous Ion Insertion and Evaluation (SIIE) workflow. SIIE inserts all ions simultaneously—to determine ion positions in organic crystals. We demonstrate that these methods accurately reproduce known ion positions in 16 organic materials and identify previously overlooked low-energy sites in tetralithium 2,6-naphthalenedicarboxylate (Li4NDC), an organic electrode material, highlighting the importance of inserting all ions simultaneously, as in the SIIE workflow. These algorithms are also integrated with off-the-shelf machine learning potentials, yielding promising results comparable to first-principles findings.
We present a control co-design software framework that can be used to optimize floating wind turbines and their controllers. Because this framework has many options for design variables, constraints, and merit figures, along with modeling fidelity levels, we seek to demonstrate best practices for using the tool while designing a floating platform for the new 22 MW offshore reference wind turbine developed within the International Energy Agency Wind Technology Commercialization Programme 55 on Reference Wind Turbines and Farms. During these studies, we evaluate the use of different simulation fidelity levels, the effect of using different load cases for controller tuning, and the difference between sequential and simultaneous control co-design solutions. Based on these efforts, we suggest using an algorithm that performs an initial search of the design space before optimization. We find that solving smaller optimization problems, in a sequential manner, leads to more reliable outcomes in fewer iterations than larger, simultaneous control co-design solutions. However a simultaneous CCD solution produces a platform with a 2% lower mass than the sequential CCD outcome.
Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over k simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach. We develop new efficient methods to solve each level of the bilevel optimization by employing knowledge of the physics of the underlying system. This yields significant improvements in speed and convergence that enable us to address the N-k SCOPF problem at scale. We demonstrate the effectiveness of our method by conducting a comprehensive analysis of an N-3 SCOPF for a 500-bus network. Furthermore, we emphasize the ability of our physics-driven techniques to handle larger systems by successfully scaling up to 12,000 buses.
Abstract In concentrated solar power (CSP) applications, fluidized bed is a promising approach for high heat transfer coefficient (HTC) solar receivers and heat exchangers. However, the complexity of multiphase mixing has made it difficult to characterize and analyze the heat transfer mechanism. This paper presents an experimental study on simultaneously characterizing heat transfer in both the near-wall and the bulk regions of a fluidized bed using modulated photothermal radiometry (MPR). The MPR is a non-contact frequency-domain technique using an intensity-modulated laser as the heat source and surface infrared emission as thermometry. The thermal penetration depth of the laser heating is varied by controlling its modulation frequency, and thus the measurement can resolve the near-wall and the bulk thermal resistances. With the MPR technique, we measured fluidized silica sands with a mean size of 164 μm in a vertical channel of 6 mm depth. Our results show that the near-wall thermal resistance is substantially increased with increasing gas velocity, which partially offsets the benefit of higher HTC brought by stronger particle mixing during the fluidization. We also used the MPR to quantify the improvement in particle-wall heat transfer in an inclined channel. We found that an 8° inclination towards the heat exchanging side led to a lower near-wall thermal resistance and a higher HTC at high gas velocities. This work demonstrates that the MPR technique is a useful tool to quantify the important near-wall thermal resistance from a bulk particle bed, which not only advances our understanding of heat transfer in fluidized beds, but may also contribute to the design of fluidized bed heat exchangers with higher HTC.
The development and innovation of floating offshore wind energy in the U.S. requires detailed high-fidelity observations and measurements of turbine and platform loading due to wind, waves, and currents. However, full-scale and quasi-full-scale experiments require significant financial and temporal investments for construction, experimental testing, and long-term field campaigns. To support the commercial advancement of the offshore wind energy industry, specialized wind tunnel and wave basin experimental facilities are critical to be able to test FOWT designs at small scale under controlled conditions prior to full-scale deployment. Oregon State University (OSU) is internationally known as a leader in water and energy research, development, and testing. The O.H. Hinsdale Wave Research Laboratory (HWRL) and the Wallace Energy Systems and Renewables Facility (WESRF) at OSU have extensive experience building, modeling, monitoring, controlling, and actuating scaled systems. Experiments on wave-structure interaction have been performed at the HWRL since its establishment in 1972. Studies have included the interaction of waves with coastal structures (breakwaters, seawalls, buildings, cylinders, bridges, fixed foundations of offshore wind turbines, etc.) and with floating structures (e.g., wave energy converters, maneuvering of vessels, etc.). Hinsdale is actively used by marine energy technology developers, both for private testing and OSU-collaborative research projects. However, despite the availability of several large-scale facilities for hydrodynamic testing (at OSU and elsewhere in the U.S.), existing experimental laboratories are generally limited in their ability to accurately generate combined wind and wave conditions. The simulation of both wind and waves in experimental testing is complicated due to a number of constraints, including: [i] incompatible similitude laws governing the wind and waves for scaled experiments, [ii] producing accurate wind over a large enough control volume via fans, and [iii] generating wind that reasonably represents the atmospheric boundary layer in existing wave basins/flumes. Hence, physical test data providing insight into the simultaneous wave- and wind-structure response of floating offshore wind components can be difficult to generate. Given the aforementioned challenges in classic hydrodynamic experiments, the motivation of this project is to establish a real-time hybrid simulation (RTHS) approach that can apply aero- and hydro-dynamic loading by augmenting wave-only experimental facilities with virtual aerodynamic forces through numerical models representing the remaining dynamic forces. RTHS is a physical-numerical approach that partitions a prototype system into physical and numerical sub-assemblies that interact with each other through actuators and sensors in real time. In coupling physical and numerical models, the hybrid simulation approach applied herein is ideal for problems with: (1) structures subjected to different scaling laws, such as floating offshore wind turbines subjected to combined aero/hydro-dynamic loading, (2) structures that are too large or complex to be tested entirely in a laboratory setting, such as deep-water mooring applications, and (3) component testing, where the behavior of a portion of the assembly is uncertain but still interacts with other portions of the structure, such as testing the fatigue life of turbine blades. Few U.S. experimental facilities are able to test simultaneous aero- and hydro-dynamic loading and none can accurately produce aero/hydro-dynamic response on scaled FOWT models due to conflicting similitude laws between the wind (commonly Reynolds) and the waves (commonly Froude). To aid in accelerating the development of the U.S. floating offshore industry, there is a significant need to develop a flexible, modular framework that can expand the capacities of existing wave-only laboratories. The project goal is to demonstrate a hydrodynamic real-time hybrid simulation (hydro-RTHS) framework that couples numerical wind and physical waves acting on a FOWT, thus representing simultaneous aero/hydro-dynamic loading. The FOWT is partitioned into a full-scale numerical sub-assembly associated with the aerodynamics and a model-scale physical sub-assembly associated with the hydrodynamics. The numerical-physical partition associated with hydro-RTHS mitigates scaling constraints by supplying different scaling laws to the physical and numerical sub-assemblies. Herein, length, force, and time are scaled and exchanged between the sub-assemblies using Froude scaling to represent the open-channel flow in the physical sub-assembly. Other similitude laws could also be utilized depending on the problem definition. It is envisioned that the ability to model FOWTs under waves and wind, with mitigation of similitude distortions, would result in reduced development costs (currently, FOWT concept development is performed with full-size pro- totypes at enormous expense and risk) and increase the reliability of the FOWT industry (since extreme wave and wind conditions and contingency events can be tested safely in a controlled environment).
Agrivoltaics, the synergistic integration of agriculture and solar energy production on the same piece of land, has emerged as a compelling dual-use solution that maximizes land productivity while simultaneously addressing the need for sustainable agricultural practices and renewable energy generation. Despite the growing global interest in this dual-use system, the microclimatic shifts created beneath solar panels and their consequences for crop performance remain insufficiently synthesized. This review highlights the intricate interactions between agrivoltaics systems and plant microclimates, discussing their impacts on various physiological processes, metabolic pathways, and overall yield responses in different crop species. Evidence indicates that moderated light intensity and altered microclimates can enhance water-use efficiency, stabilize photosynthetic function, and trigger beneficial metabolic adjustments; however, responses remain highly species-specific and strongly dependent on regional climate conditions and panel configuration. Yield outcomes vary widely among vegetables, cereals, pulses, and fruit crops, highlighting the necessity for tailored agronomic strategies and crop selection within agrivoltaic designs. A critical knowledge gap identified in this review concerns the limited understanding of molecular and omics-level responses underlying plant adaptation to agrivoltaic environments. We further provide a detailed and interdisciplinary overview of adaptive agronomic strategies, and optimal crop selection, tailored to agrivoltaic systems. Despite the benefits of land use efficiency and simultaneous food and energy production, challenges remain concerning initial investment, technological adaptation, social and legal barriers, and shade-induced yield penalties. Further research in this area will be critical to enhancing the agricultural, environmental, and economic sustainability of agrivoltaics while simultaneously augmenting their practical utility and appeal to farmers in the future.
Raman fingerprint spectroscopy and fluorescence lifetime imaging are emerging tools for studying metabolic profiles of biological specimens. While Raman fingerprint spectroscopy detects intrinsic molecular vibrations that reflect the molecular composition and chemical environment of a sample, fluorescence lifetime imaging measures changes in the excited-state lifetime of fluorophores that are sensitive to their microenvironments. Here, we present a multimodal imaging platform combining broadband coherent anti-Stokes Raman scattering (BCARS) and two-photon fluorescence lifetime imaging (2p-FLIM) microscopy that can acquire biologically relevant Raman fingerprint spectra and fluorescence lifetime signals in vivo and simultaneously. The tremendous chemical information obtained from spatially co-registered BCARS and 2p-FLIM images allows us to characterize the subtle differences between sub-cellular compartments and verify the potential false-positive results generated by fluorescence imaging alone. This is demonstrated by directly comparing the BCARS, 2p-FLIM, and two-photon excitation fluorescence(TPEF) signals simultaneously obtained from the same dye-stained organelle in the live, intact C. elegans expressing a green fluorescent protein (GFP) marker. In this work, we introduce the BCARS/2p-FLIM/TPEF setup scheme, the image acquisition steps, data processing, and representative results showing that the cross-modality imaging method enables rigorous characterization and in vivo detection at sub-cellular resolution. Furthermore, this protocol provides a framework for simultaneous chemical and fluorescence lifetime imaging to improve the accuracy of biological interpretation in complex living systems.
The Solid-state Prealkylation of Electrode ARchitectures (SPEAR) is different than traditional electrochemical prealkylation processes. Through SPEAR, alkylation is driven by solid-state diffusion without the simultaneous SEI formation concomitant with polarization. Here, we investigate the prelithiation of 80 wt. % Si-based anodes to varying amounts (up to Li 1.38 Si) to understand the trade-off between improved Li capacity and expansion-induced stress. Through dilatometry, we found that solid-state lithiation led to filling of the electrode pores through silicon expansion. This swelling changed the SEI formation process and accessibility of the silicon compared to an electrochemically lithiated electrode. Indeed, optimal prelithiation to Li 0.82 Si increases the initial C/3 cycling capacity post-SEI formation up to 43%, consistent with deeper Si activation through the electrode bulk. Prelithiation and cycling cells prelithiated beyond Li 0.82 Si results in a state of charge (SOC) close to 100% which facilitates parasitic degradation mechanisms and volume expansion of the Si electrode. The results demonstrate a pathway to modify silicon activation/SEI formation to enable high-energy electrodes.
All‐solid‐state batteries suffer from high interface resistance and lithium dendrite growth leading to low Li plating/stripping Coulombic efficiency (CE) of <90% and low critical current density at high capacity. Here, in this work, both challenges are simultaneously addressed and the Li plating/stripping CE is significantly increased to 99.6% at 0.2 mA cm −2 /0.2 mAh cm −2 , and critical current density (CCD) of > 3.0 mA cm −2 /3.0 mAh cm −2 by inserting a mixed ionic‐electronic conductive (MIEC) and lithiophobic LiF‐C‐Li 3 N‐Bi nanocomposite interlayer between Li 6 PS 5 Cl electrolyte and Li anode. The highly lithiophobic LiF‐C‐Li 3 N‐Bi interlayer with high ionic conductivity (10 −5 S cm −1 ) and low electronic conductivity (3.4×10 −7 S cm −1 ) enables Li to plate on the current collector (CC) surface rather than on Li 6 PS 5 Cl surface avoiding Li 6 PS 5 Cl electrolyte reduction. During initial Li plating on CC, Li penetrates into porous LiF‐C‐Li 3 N‐Bi interlayer and lithiates Bi nanoparticles into Li 3 Bi. The lithiophilic Li 3 Bi and Li 3 N nanoparticles in LiF‐C‐Li 3 N‐Li 3 Bi sub‐interlayer will move to CC along with plated Li, forming LiF‐C/Li 3 N‐Li 3 Bi lithiophobic/lithiophilic sublayer during the following Li stripping. This interlayer enables Co 0.1 Fe 0.9 S 2 /Li 6 PS 5 Cl/Li cell with an areal capacity of 1.4 mAh cm −2 to achieve a cycle life of >850 cycles at 150 mA g −1 . The lithiophobic/lithiophilic interlayer enables solid‐state metal batteries to simultaneously achieve high energy and long cycle life.
INTRODUCTION: In the aging brain, cognitive abilities emerge from the coordination of complex pathways arising from a balance between protective lifestyle and environmental factors and accumulation of neuropathologies. METHODS: As part of the Rush Memory and Aging Project (n = 440), we measured accelerometer-based actigraphy, cognitive performance, and after brain autopsy, selected reaction monitoring mass spectrometry. Multilevel network analysis was used to examine the relationships among the molecular machinery of vesicular neurotransmission, Alzheimer's disease (AD) neuropathology, cognition, and late-life physical activity. RESULTS: Synaptic peptides involved in neuronal secretory function were the most influential contributors to the multilayer network, reflecting the complex interdependencies among AD pathology, synaptic processes, and late-life cognition. Older adults with lower physical activity evidenced stronger adverse relationships among phosphorylated tau peptides, markers of synaptic integrity, and tangle pathology. DISCUSSION: Network-based approaches simultaneously model interdependent biological processes and advance understanding of the role of physical activity in age-associated cognitive impairment. Highlights: Network-based approaches simultaneously model interdependent biological processes. Secretory synaptic peptides were influential contributors to the multilayer network. Older adults with lower physical activity had adverse relationships among pathology. There was interdependence among phosphorylated tau, synaptic integrity, and tangles. Network methods elucidate the role of physical activity in cognitive impairment.
Abstract We investigate the effect on neutrino oscillations generated by beyond-the-standard-model interactions between neutrinos and matter. Specifically, we focus on scalar-mediated non-standard interactions (NSI) whose impact fundamentally differs from that of vector-mediated NSI. Scalar NSI contribute as corrections to the neutrino mass matrix rather than the matter potential and thereby predict distinct phenomenology from the vector-mediated ones. Similar to vector-type NSI, the presence of scalar-mediated neutrino NSI can influence measurements of oscillation parameters in long-baseline neutrino oscillation experiments, with a notable impact on CP measurement in the case of DUNE. Our study focuses on the effect of scalar NSI on neutrino oscillations, using DUNE as an example. We introduce a model-independent parameterization procedure that enables the examination of the impact of all non-zero scalar NSI parameters simultaneously. Subsequently, we convert DUNE’s sensitivity to the NSI parameters into projected sensitivity concerning the parameters of a light scalar model. We compare these results with existing non-oscillation probes. Our findings reveal that the region of the light scalar parameter space sensitive to DUNE is predominantly excluded by non-oscillation probes, especially when considering all nonzero parameters simultaneously for DUNE.
The production of multiple Higgs bosons at the CERN LHC provides a direct way to measure the trilinear and quartic Higgs self-interaction strengths as well as potential access to beyond the standard model effects that can enhance production at large transverse momentum p T . The largest event fraction arises from the fully hadronic final state in which every Higgs boson decays to a bottom quark-antiquark pair ($b\bar{b}$). This introduces a combinatorial challenge known as the jet assignment problem: assigning jets to sets representing Higgs boson candidates. Symmetry-preserving attention networks (SPA-Nets) have been developed to address this challenge. However, the complexity of jet assignment increases when simultaneously considering both H → $b\bar{b}$ reconstruction possibilities, i.e., two “resolved” small-radius jets each containing a shower initiated by a b quark or one “boosted” large-radius jet containing a merged shower initiated by a $b\bar{b}$ pair. The latter improves the reconstruction efficiency at high p T . In this work, we introduce a generalization to the SPA-Net approach to simultaneously consider both boosted and resolved reconstruction possibilities and unambiguously interpret an event as “fully resolved”, “fully boosted”, or in between. We report the performance of baseline methods, the original SPA-Net approach, and our generalized version on nonresonant HH and HHH production at the LHC. Considering both boosted and resolved topologies, our SPA-Net approach increases the Higgs boson reconstruction purity by 56–80% and the efficiency by 37–38% compared to the baseline method depending on the final state.