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At least 235 records · Page 13

An NV − center in magnesium oxide as a spin qubit for hybrid quantum technologies

Recent predictions suggest that oxides, such as MgO and CaO, could serve as hosts of spin defects with long coherence times and thus be promising materials for quantum applications. However, in most cases, specific defects have not yet been identified. Here, by using a high-throughput first-principles framework and advanced electronic structure methods, we identify a negatively charged complex between a nitrogen interstitial and a magnesium vacancy in MgO with favorable electronic and optical properties for hybrid quantum technologies. We show that this NV − center has stable triplet ground and excited states, with singlet shelving states enabling optical initialization and spin-dependent readout. We predict several properties, including absorption, emission, and zero-phonon line energies, as well as zero-field splitting tensor, and hyperfine interaction parameters, which can aid in the experimental identification of this defect. Our calculations show that due to a strong pseudo-Jahn Teller effect and low-frequency phonon modes, the NV − center in MgO is subject to a substantial vibronic coupling. We discuss design strategies to reduce such coupling and increase the Debye-Waller factor, including the effect of strain and the localization of the defect states. We propose that the favorable properties of the NV − defect, along with the technological maturity of MgO, could enable hybrid classical-quantum applications, such as spintronic quantum sensors and single qubit gates.

36 MATERIALS SCIENCE↗

Distributed Acoustic Sensing for Whale Vocalization Monitoring: A Vertical Deployment Field Test

Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments.

Saw, Jaewon↗

Developing a heterogeneous ensemble learning framework to evaluate Alkali-silica reaction damage in concrete using acoustic emission signals

The monitoring and evaluation of Alkali-silica reaction (ASR) damage in concrete structures are required to ensure the serviceability and integrity of concrete infrastructures such as bridges and dams. The innovation of this paper lies in the development of an automatic ASR monitoring and evaluation approach by leveraging acoustic emission (AE) and a heterogeneous ensemble learning framework. Here, in this paper, ASR was monitored by AE sensors attached to a concrete specimen, which was placed in a chamber with high humidity and temperature. The recorded AE signals were filtered and divided by four ASR phases according to signal strength, crack width and expansion strain. A heterogeneous ensemble network including convolutional neural networks (CNN) and random forest models was employed to learn different features from AE signals and classify the AE signals into their corresponding phases. The results suggest that the proposed model has a high performance and classifies the signals into the assigned phases with high accuracy.

42 ENGINEERING↗

Eu speciation in apatite at 1 bar: An experimental study of valence-state partitioning by XANES, lattice strain, and Eu/Eu* in basaltic systems

Abstract Partition coefficients for rare earth elements (REEs) between apatite and basaltic melt were determined as a function of oxygen fugacity (fO2; iron-wüstite to hematite-magnetite buffers) at 1 bar and between 1110 and 1175 °C. Apatite-melt partitioning data for REE3+ (La, Sm, Gd, Lu) show near constant values at all experimental conditions, while bulk Eu becomes more incompatible (with an increasing negative anomaly) with decreasing fO2. Experiments define three apatite calibrations that can theoretically be used as redox sensors. The first, a XANES calibration that directly measures Eu valence in apatite, requires saturation at similar temperature-composition conditions to experiments and is defined by: ( E u 3 + ∑ E u ) Apatite = 1 1 + 10 - 0.10 ± 0.01 × l o g ⁡ ( f o 2 ) - 1.63 ± 0.16 . The second technique involves analysis of Sm, Eu, and Gd in both apatite and coexisting basaltic melt (glass), and is defined by: ( Eu E u * ) D Sm × Gd = 1 1 + 10 - 0.15 ± 0.03 × l o g ⁡ ( f o 2 ) - 2.46 ± 0.41 . The third technique is based on the lattice strain model and also requires analysis of REE in both apatite and basalt. This calibration is defined by ( Eu E u * ) D lattice strain = 1 1 + 10 - 0.20 ± 0.03 × l o g ⁡ ( f o 2 ) - 3.03 ± 0.42 . The Eu valence-state partitioning techniques based on (Sm×Gd) and lattice strain are virtually indistinguishable, such that either methodology is valid. Application of any of these calibrations is best carried out in systems where both apatite and coexisting glass are present and in direct contact with one another. In holocrystalline rocks, whole rock analyses can be used as a guide to melt composition, but considerations and corrections must be made to either the lattice strain or Sm×Gd techniques to ensure that the effect of plagioclase crystallization either prior to or during apatite growth can be removed. Similarly, if the melt source has an inherited either a positive or negative Eu anomaly, appropriate corrections must also be made to lattice strain or Sm×Gd techniques that are based on whole rock analyses. This being the case, if apatite is primary and saturates from the parent melt early during the crystallization sequence, these corrections may be minimal. The partition coefficients for the REE between apatite and melt range from a maximum DEu3+ = 1.67 ± 0.25 (as determined by lattice strain) to DLu3+ = 0.69 ± 0.10. The REE partition coefficient pattern, as observed in the Onuma diagram, is in a fortuitous situation where the most compatible REE (Eu3+) is also the polyvalent element used to monitor fO2. These experiments provide a quantitative means of assessing Eu anomalies in apatite and how they be used to constrain the oxygen fugacity of silicate melts.

Geochemistry & Geophysics↗

Embedding of Fiber Optic Sensors in Stainless Steel for Sensing in Harsh Environments

Structural health monitoring is critical for components working in harsh environments to assess their safety and integrity. This can be realized with advanced sensors, such as fiber optic sensors, embedded in these components. Recent studies have used ultrasonic consolidation (UC) and laser-based additive manufacturing (AM) techniques to embed fiber optic sensors in metals. However, sensor embedding using these techniques has been challenging, with gaps and voids around the embedded fiber. Successful embedding of fiber optic sensors requires good contact between the fiber and the matrix to eliminate potential gas/liquid leaks in critical systems such as in nuclear and aerospace services. Defect-free fiber/matrix bond is also essential for accurate measurement of parameters of interest, such as temperature and strain. This study developed a novel fiber embedding technique based on electric field-assisted sintering (EFAS). Sapphire optical fibers with diameters of 125 µm and 250 µm were embedded in stainless steel (SS) 316L using EFAS. The embedding was completed by sintering SS 316L powders at a pressure of 50MPa, hold time of 5 min, and temperatures of 1000°C, 1100°C, and 1200°C. Joule heating mechanism during EFAS enabled rapid sintering of the SS 316L powder with resulting sample densities over 99%. Microscopy analysis performed on the cross-sections revealed a defect-free bond between the embedded fiber and SS 316L. The good integrity of the embedded fiber was evidenced by optical transmittance measurement. Optical attenuation of the fiber before and after embedment was examined in the near-infrared region. Scanning electron microscopy was employed to investigate the grain morphology of SS 316L near the embedded fiber. Hardness distribution in the sintered part was also investigated to study the effect of the embedded fiber on the mechanical properties of the as-fabricated component. The results indicated that EFAS was able to embed fiber in SS with good fiber functionality and part quality.

36 - MATERIALS SCIENCE↗

Pathogenic and Apathogenic Strains of Lymphocytic Choriomeningitis Virus Have Distinct Entry and Innate Immune Activation Pathways

Lymphocytic choriomeningitis virus (LCMV) and Lassa virus (LASV) share many genetic and biological features including subtle differences between pathogenic and apathogenic strains. Despite remarkable genetic similarity, the viscerotropic WE strain of LCMV causes a fatal LASV fever-like hepatitis in non-human primates (NHPs) while the mouse-adapted Armstrong (ARM) strain of LCMV is deeply attenuated in NHPs and can vaccinate against LCMV-WE challenge. Here, we demonstrate that internalization of WE is more sensitive to the depletion of membrane cholesterol than ARM infection while ARM infection is more reliant on endosomal acidification. LCMV-ARM induces robust NF-κB and interferon response factor (IRF) activation while LCMV-WE seems to avoid early innate sensing and failed to induce strong NF-κB and IRF responses in dual-reporter monocyte and epithelial cells. Toll-like receptor 2 (TLR-2) signaling appears to play a critical role in NF-κB activation and the silencing of TLR-2 shuts down IL-6 production in ARM but not in WE-infected cells. Pathogenic LCMV-WE infection is poorly recognized in early endosomes and failed to induce TLR-2/Mal-dependent pro-inflammatory cytokines. Following infection, Interleukin-1 receptor-associated kinase 1 (IRAK-1) expression is diminished in LCMV-ARM- but not LCMV-WE-infected cells, which indicates it is likely involved in the LCMV-ARM NF-κB activation. By confocal microscopy, ARM and WE strains have similar intracellular trafficking although LCMV-ARM infection appears to coincide with greater co-localization of early endosome marker EEA1 with TLR-2. Both strains co-localize with Rab-7, a late endosome marker, but the interaction with LCMV-WE seems to be more prolonged. These findings suggest that LCMV-ARM’s intracellular trafficking pathway may facilitate interaction with innate immune sensors, which promotes the induction of effective innate and adaptive immune responses.

59 BASIC BIOLOGICAL SCIENCES↗

Stabilizing the heavily-doped and metallic phase of MoS 2 monolayers with surface functionalization

Monolayer molybdenum disulfide (MoS 2 ) is one of the most studied two-dimensional (2D) transition metal dichalcogenides that is being investigated for various optoelectronic properties, such as catalysis, sensors, photovoltaics, and batteries. One such property that makes this material attractive is the ease in which 2D MoS 2 can be converted between the semiconducting (2H) and metallic/semi-metallic (1T/1T') phases or heavily n-type doped 2H phase with ion intercalation, strain, or excess negative charge. Using n-butyl lithium (BuLi) immersion treatments, we achieve 2H MoS 2 monolayers that are heavily n-type doped with shorter immersion times (10–120 mins) or conversion to the 1T/1T' phase with longer immersion times (6–24 h); however, these doped/converted monolayers are not stable and promptly revert back to the initial 2H phase upon exposure to air. To overcome this issue and maintain the modification of the monolayer MoS 2 upon air exposure, we use BuLi treatments plus surface functionalization p-(CH 3 CH 2 ) 2 NPh-MoS 2 (Et 2 N-MoS 2 )—to maintain heavily n-type doped 2H phase or the 1T/1T' phase, which is preserved for over two weeks when on indium tin oxide or sapphire substrates. We also determine that the low sheet resistance and metallic-like properties correlate with the BuLi immersion times. These modified MoS 2 materials are characterized with confocal Raman/photoluminescence, absorption, x-ray photoelectron spectroscopy as well as scanning Kelvin probe microscopy, scanning electrochemical microscopy, and four-point probe sheet resistance measurements to quantify the differences in the monolayer optoelectronic properties. We will demonstrate chemical methodologies to control the modified monolayer MoS 2 that likely extend to other 2D transition metal dichalcogenides, which will greatly expand the uses for these nanomaterials.

2D TMDC↗

Monolayer Sc 2 CF 2 as a Potential Selective and Sensitive NO 2 Sensor: Insight from First-Principles Calculations

Two-dimensional materials with excellent surface–volume ratios and massive reaction sites recently have been receiving attention for gas sensing. With first-principles calculations, we explored the performance of monolayer Sc 2 CF 2 as a gas sensor. We investigated how molecule adsorption affects its electronic structure and optical properties. It is found that a large charge transfer quantity happens between Sc 2 CF 2 and NO 2 , which results from the fact that the lowest unoccupied molecular orbital (LUMO) of NO 2 is below the valence band maximum (VBM) of Sc 2 CF 2 . Moreover, the MD simulation shows that NO 2 can adsorb on the Sc 2 CF 2 surface stably at room temperature. We explored the effect of biaxial strain on the adsorption energy and charge transfer quantity of each system, and the results show that the biaxial strain can enhance both the adsorption energy and charge transfer quantity of the NO 2 system and thus can improve the sensitivity of Sc 2 CF 2 in detecting the NO 2 molecule. Furthermore, we investigated the adsorption behavior and charge transfer of polar polyatomic molecules at the Sc 2 CF 2 surface with h-BN as a substrate, and the results demonstrate that the h-BN substrate can hardly modify the main results. Our result predicts that Sc 2 CF 2 can be a promising selective and sensitive sensor to detect the NO 2 molecule, and could also give a theoretical guide for other terminated MXenes used for gas sensors or detectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aerosol jet printing of piezoelectric surface acoustic wave thermometer

Abstract Surface acoustic wave (SAW) devices are a subclass of micro-electromechanical systems (MEMS) that generate an acoustic emission when electrically stimulated. These transducers also work as detectors, converting surface strain into readable electrical signals. Physical properties of the generated SAW are material dependent and influenced by external factors like temperature. By monitoring temperature-dependent scattering parameters a SAW device can function as a thermometer to elucidate substrate temperature. Traditional fabrication of SAW sensors requires labor- and cost- intensive subtractive processes that produce large volumes of hazardous waste. This study utilizes an innovative aerosol jet printer to directly write consistent, high-resolution, silver comb electrodes onto a Y-cut LiNbO 3 substrate. The printed, two-port, 20 MHz SAW sensor exhibited excellent linearity and repeatability while being verified as a thermometer from 25 to 200 ∘ C. Sensitivities of the printed SAW thermometer are $$-96.9\times 1{0{}^{-6}}^{\circ }$$ − 96.9 × 1 0 − 6 ∘ C −1 and $$-92.0\times 1{0{}^{-6}}^{\circ }$$ − 92.0 × 1 0 − 6 ∘ C −1 when operating in pulse-echo mode and pulse-receiver mode, respectively. These results highlight a repeatable path to the additive fabrication of compact high-frequency SAW thermometers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Seismic DAS observations of a large underground chemical explosion in dry tuff

On 18 October 2023 a 16.3-ton TNT equivalent chemical explosion was detonated underground at the Nevada National Security Site, generating a seismic event with a magnitude of 1.7 (Meyers et al., 2024). The associated seismic wavefield was measured on a Distributed Acoustic Sensing (DAS) array with slant range distances from 27 m – 1123 m. The first arriving phase traveled at an apparent velocity of about 2640 m s -1 from 27 m to 420 m slant range and about 2470 m s -1 from 505 m to 1123 m slant range according to the first arrival moveouts on the DAS data. The first arrival from the explosion temporarily saturated the cable from a slant range of 27 m – 186 m and 0.009 s to 0.084 s post detonation. From 186 m slant range to 420 m slant range, peak strain rates of 5.6 x 10 6 nm m -1 s -1 were observed for the first arrival phase. For the first arrival from 505 m slant range to 1123 m slant range, peak strain rates reduced to 8.0 x 104 nm m -1 s -1 . A comparison of the scaled accelerations computed from DAS, the geophone pairs, and the measurements of co-located accelerometer pairs show common agreement at the scaled ranges of the single point sensors. This study adds to the body of work reporting near-source DAS observations of the seismic wavefields generated by underground chemical explosions. These results indicate that near-source DAS observations can refine interpretations of phase identification from single-point sensor observations. Phase identification could be one mechanism that contributes scatter to single point seismic measurements which would confound the performance of empirical relationships for small explosions. Removing that mechanism may therefore reduce interstation variability and increase empirical relationship performance for small explosions.

58 GEOSCIENCES↗

Seismic DAS Observations of a large underground chemical explosion in dry tuff

On 18 October 2023 a 16.3-ton TNT equivalent chemical explosion was detonated underground at the Nevada National Security Site, generating a seismic event (Meyers et al., 2024). The associated seismic wavefield was measured on a Distributed Acoustic Sensing (DAS) array with slant range distances from 27 m – 1123 m. The first arriving phase traveled at an apparent velocity of about 2640 m s -1 from 27 m to 420 m slant range and about 2470 m s -1 from 505 m to 1123 m slant range according to the first arrival moveouts on the DAS data. The first arrival from the explosion temporarily saturated the cable from a slant range of 27 m – 186 m and 0.009 s to 0.084 s post detonation. From 186 m slant range to 420 m slant range, peak strain rates of 5.6 x 10 6 nm m -1 s -1 were observed for the first arrival phase. For the first arrival from 505 m slant range to 1123 m slant range, peak strain rates reduced to 8.0 x 10 4 nm m -1 s -1 . A comparison of the scaled accelerations computed from DAS, the geophone pairs, and the measurements of co-located accelerometer pairs show common agreement at the scaled ranges of the single point sensors. This study adds to the body of work reporting near-source DAS observations of the seismic wavefields generated by underground chemical explosions. These results indicate that near-source DAS observations can refine interpretations of phase identification from single-point sensor observations. Phase identification could be one mechanism that contributes scatter to single point seismic measurements which would confound the performance of empirical relationships for small explosions. Removing that mechanism may therefore reduce interstation variability and increase empirical relationship performance for small explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Surface Energy Modulated Self‐Assembly of Percolative Gallium Nanodroplet Films for Stretchable Electronics

Advancements in soft robotics and wearable technologies have led to an increased need for flexible and stretchable electronic systems. Liquid metals like Gallium (Ga) and its alloys offer high potential in the field of stretchable electronics and photonics due to their inherent high conductivity and malleability. However, their high surface tension and native oxide formation hinder uniform wetting and continuous film formation to get conducting films. Here, we report a fabrication strategy to realize electrically conductive Ga thin films with effective thicknesses around 100 nm on polymeric and elastomeric substrates. By enhancing the surface energy of the elastomer, we create uniform Ga nanodroplets capable of sustaining stretchability up to 200% strain. Our devices exhibit electronic conduction primarily through tunneling and display strain tunable piezoresistive characteristics, which are explained using Kirchhoff's resistive network and Simmon's analytical tunneling current model. To showcase the device's capability in fields of stretchable electronics, we demonstrate several functional prototypes, including flexible devices integrated with Light Emitting Diodes (LEDs), curvature and pressure sensors, and soft robotic grippers capable of sensing object curvature. The demonstrated devices highlight the potential of this approach for scalable integration of stretchable electronics in soft robotic and wearable platforms.

42 ENGINEERING↗

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗

Toll-like Receptor Ligands Enhance Vaccine Efficacy against a Virulent Newcastle Disease Virus Challenge in Chickens

To enhance the efficacy of the current Newcastle disease vaccine, we have selected potential adjuvants that target well-characterized pattern recognition receptors: the toll-like receptors (TLRs). Imiquimod is a small-molecule activator of TLR7, which is a sensor of dsDNA. ODN-1826 is a mimetic of CpG DNA and ligates TLR21 (a chicken homologue of TLR9 in mammals). The activation of TLRs leads to antiviral responses, including the induction of type I interferons (IFNs). In this study, birds were vaccinated intranasally with a live LaSota strain with or without imiquimod or ODN-1826 (50 µg/bird). Two weeks after vaccination, the birds were challenged with a virulent Newcastle disease virus (chicken/CA/212676/2002). Both adjuvants (imiquimod or ODN-1826) induced higher and more uniform antibody titers among vaccinated birds compared with the live vaccine-alone group. In addition, adjuvanted vaccines demonstrated greater protective efficacy in terms of the reduction in virus-shedding titer and the number of birds shedding the challenge virus at 2 and 4 days post-challenge. A differential expression of antiviral and immune-related genes was observed among groups from tissues (Harderian gland, trachea, cecal tonsil, and spleen) collected 1 and 3 days after treatment. These results demonstrate the potential of TLR-targeted adjuvants as mucosal vaccine enhancers and warrant a further characterization of immune correlates and optimization for efficacy.

59 BASIC BIOLOGICAL SCIENCES↗

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗

Optimized Illuminance Operation-A Light-Driven Dilution Strategy to Improve Microalgae Biomass Productivity

Periodic dilution is a necessary operation to avoid light limitation due to self-shading as the culture grows dense. However, environmental conditions are constantly changing in outdoor cultivation systems, making it difficult to determine the optimal dilution rate. To address this challenge, this study evaluated a dilution approach based on light penetration to optimize illuminance (OptiLum) in the culture. Biomass concentration was controlled via sensor-feedback directed dilution to ensure that light reaching the bottom of the culture was maintained above the compensation intensity. Under replicated outdoor pond conditions, by keeping the entire culture within a net-positive photosynthetic zone, the OptiLum operation improved the biomass productivities of two top-performing strains, Picochlorum celeri and Tetraselmis striata, by 95 % and 86 %, respectively, compared to conventional semi-continuous batch cultivation. The dilution rate varied daily and was dynamically adjusted based on the light status within the culture, which is concurrently influenced by weather, culture density, and growth rate. The techno-economic analysis showed that the OptiLum operation could reduce biomass production cost by as much as 24 % and 33 % for P. celeri and T. striata, respectively, assuming a low-cost dewatering approach with initial gravity settling of biomass can be realized for both strains. However, a more costly two-stage dewatering strategy, comprising only membranes and centrifuges, may be necessary for non-settling strains, such as P. celeri, which would alternatively increase production costs by 23 % for the OptiLum case. The results demonstrated that the proposed OptiLum operation is a promising approach to improve biomass productivity and lower production cost via weather-responsive and self-adjusting dilution.

09 BIOMASS FUELS↗

Geophysical Signatures of Crack Network Coalescence in Rocks at Multiple Length Scales

The main goal of the research project was to identify the geophysical signatures of fracture growth in natural rocks by utilizing novel geophysical techniques. The research objectives were to (a) investigate the potential for geophysical methods to determine when cracks initiate, the types and locations of propagated cracks, and the coalescence of networks of cracks in natural rocks at multiple scales, (b) determine how damage at the microscale evolved into damage at the macroscale and then link the microscopic and macroscopic observations, (c) quantify crack coalescence in rocks under realistic stress conditions using coupled mechanical-geophysical-optical visualization, and (d) identify the precursors in geophysical signals to crack coalescence. The following research thrusts were explored to achieve the research objectives: (1) uniaxial compression testing of rock specimens with and without a set of pre‐existing flaws and (2) triaxial compression testing of natural rock specimens. These thrusts allowed for exploring fracturing in rocks under realistic in situ environments and at multiple scales. This project provided educational opportunities for nine graduate and undergraduate students and resulted in 27 peer-reviewed publications. This first research thrust focused on investigating the micromechanics of fractures in rocks through uniaxial compression testing combined with advanced geophysical and imaging techniques, specifically acoustic emission (AE) monitoring, ultrasonic imaging, and 2-dimensional Digital Image Correlation (2D-DIC). By examining damage processes under time-independent and time-dependent loading conditions, insights into damage localization, crack initiation, and fracturing mechanisms were gained. It was observed that the AE signals and the strain-based measurements directly reflect the state of damage in the rock specimen and could be used to identify the cracking levels, such as the crack initiation (CI) and crack damage (CD), and the mode of deformation. A novel calibration apparatus was developed to enhance the accuracy of AE sensors, allowing for the estimation of key parameters such as magnitude, source dimension, stress drop, and radiated seismic energy associated with the fractures. The findings highlighted significant variations in the temporal evolution of AE source parameters during the primary, secondary, and tertiary stages of creep, identifying tensile cracking as the primary deformation mode. The second research thrust focused on enhancing the understanding of fracturing processes in natural rocks through triaxial compression testing, real-time AE monitoring, and ultrasonic monitoring. We investigated the impact of various factors such as fracture propagation regimes, injection parameters, rock types, and pre-existing conditions on the hydraulic fracture (HF) behavior using scaled true-triaxially loaded specimens of Barre granite and Lyons sandstone. Custom sensor housing facilitated concurrent active and passive monitoring to analyze hydro-mechanical responses and microseismicity associated with different HF scenarios. A coupled investigation of passive microseismicity and active signal attributes permitted a detailed comprehension of the various HF processes (aseismic deformation, fracture initiation and propagation, fluid permeation, and leak-off) and their dependence on the specific rock type. The findings of this research demonstrated the effectiveness of AE monitoring techniques in providing valuable insights into the impact of various factors on the behavior and dynamics of HF processes. The advancements in monitoring techniques, offering a more thorough and precise approach, represent a significant step towards optimizing HF practices and ensuring sustainable resource extraction.

58 GEOSCIENCES↗

Achieving High-Yield Conversion of Janus Transition Metal Dichalcogenides on Diverse Substrates

Janus transition metal dichalcogenides (TMDCs) with intrinsic broken mirror symmetry and vertical dipole moment provide an additional degree of freedom to manipulate material symmetry down to atomic-layer thickness. However, despite advances in synthesis strategies, fundamental understanding of this atomic substitution process remains limited, which has impeded their implementation in advanced devices. Here, by using a room-temperature atomic-layer substitution (RT-ALS) strategy, we systematically investigate the critical factors facilitating the high-yield conversion of Janus TMDCs on diverse substrates. Combining Raman spectroscopy probes, X-ray photoelectron spectroscopy (XPS) measurements, and density functional theory (DFT) calculations, we demonstrate that substrates with enhanced electron doping or larger surface polarity substantially benefit the conversion of Janus TMDCs reaching a near-unity yield. Intriguingly, the strong affinity between Janus TMDCs and substrates (e.g., Au) brings about abnormal Raman spectroscopic phenomena. These findings highlight the significance of substrates in achieving the reliable synthesis of Janus two-dimensional materials with improved homogeneity on various substrates. In addition, this takes us one step closer to utilizing Janus TMDCs as a versatile platform in next-generation optoelectronic devices, sensors, and quantum technologies.

Doping↗