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At least 505 records · Page 28

Stress Dependency of Brittle Creep in Granite: Insights into Source Mechanisms and Parameters

Creep in rocks refers to the gradual deformation of rock material over time under the influence of constant stress. Characterizing these deformations is of great importance for engineering design, geotechnical assessment, mining operations, geological studies, and understanding natural hazards. While laboratory experiments and a variety of numerical approaches have offered explanations for microcrack interaction and damage accumulation under the three stages of creep (primary, secondary and tertiary) in conventional creep experiments, the micromechanisms of the fractures produced in brittle creep and its dependency on the applied stress have not been explored in detail. The present study focused on investigating the fracturing mechanisms that occur during creep-induced fracturing at different stress levels and estimation of the source parameters and energy budget components. A series of uniaxial compression creep experiments have been conducted at different stress level ratios (70%, 75%, 80% and 85%), to the unconfined compressive strength (UCS) of double-flawed Barre granite specimen. Creep measurements were complemented with the Acoustic Emission (AE) measurements. The creep-induced fractures were classified into double-couple (DC), compensated linear vector dipole (CLVD) and isotropic (ISO) components using the AE moment tensor decomposition technique. The results show that non-double-couple sources dominated during creep at all the specified stress levels; however, their proportions decreased as the stress level was increased. The source parameters estimation indicated a significant increase in the magnitude of the events and the radiated seismic energy with increasing levels of stress and a slight increase in the evaluated source radius and stress drop with increasing stress levels. Furthermore, this study contributes to the existing knowledge of creep-induced fracturing by providing insights into the fracturing mechanisms and the radiated seismic energy produced, which can be helpful for the development of improved models and strategies for rock engineering and geoscience applications.

58 GEOSCIENCES↗

Considerations for testing full-scale wind turbine nacelles with hardware-in-the-loop

In this paper, pole placement control techniques are utilized to compensate for variations in the torsional dynamics resulting from the different boundary conditions experienced by a wind turbine nacelle when mounted on a test bench. Simulation case studies are used to understand the baseline torsional characteristics of the nacelle coupled to the test bench versus that coupled to the rotor. It was found that the frequency shifts by up to 200% and 400% for the first and second torsional modes, respectively. The feasibility of utilizing pole placement technique to match the torsional characteristics of the turbine on the test bench is investigated using PI and PID controllers. Here, the performance of the tuned controller is then verified under two test scenarios: Low Voltage Ride Through (LVRT), and a highly dynamic turbulent wind input. It is demonstrated that tuning the test bench speed controller can effectively shift the poles of the closed-loop system to match the desired first and second modes of the full turbine and replicate transient field events on the test bench.

17 WIND ENERGY↗

Peri-Net-Pro: the neural processes with quantified uncertainty for crack patterns

Abstract This paper develops a deep learning tool based on neural processes (NPs) called the Peri-Net-Pro, to predict the crack patterns in a moving disk and classifies them according to the classification modes with quantified uncertainties. In particular, image classification and regression studies are conducted by means of convolutional neural networks (CNNs) and NPs. First, the amount and quality of the data are enhanced by using peridynamics to theoretically compensate for the problems of the finite element method (FEM) in generating crack pattern images. Second, case studies are conducted with the prototype microelastic brittle (PMB), linear peridynamic solid (LPS), and viscoelastic solid (VES) models obtained by using the peridynamic theory. The case studies are performed to classify the images by using CNNs and determine the suitability of the PMB, LBS, and VES models. Finally, a regression analysis is performed on the crack pattern images with NPs to predict the crack patterns. The regression analysis results confirm that the variance decreases when the number of epochs increases by using the NPs. The training results gradually improve, and the variance ranges decrease to less than 0.035. The main finding of this study is that the NPs enable accurate predictions, even with missing or insufficient training data. The results demonstrate that if the context points are set to the 10th, 100th, 300th, and 784th, the training information is deliberately omitted for the context points of the 10th, 100th, and 300th, and the predictions are different when the context points are significantly lower. However, the comparison of the results of the 100th and 784th context points shows that the predicted results are similar because of the Gaussian processes in the NPs. Therefore, if the NPs are employed for training, the missing information of the training data can be supplemented to predict the results.

Mathematics↗

Synthesis of CdZnTeSe single crystals for room temperature radiation detector fabrication: mitigation of hole trapping effects using a convolutional neural network

In this article, we report the growth of Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 (CZTS) wide bandgap semiconductor single crystals for room temperature gamma-ray detection using a modified vertical Bridgman method. Charge transport properties measured in the radiation detectors, fabricated from the grown CZTS crystals, indicated signs of hole trapping. Hole traps inhibit high-resolution radiation detection especially for energetic gamma rays. Machine learning (ML) applications are gaining tremendous mpetus in improving device and sensor performance by compensating for limi tations arising from such intrinsic material properties. In this article, we describe a deep convolutional neural network (CNN) that has demonstrated remarkable efficiency in identifying the energy of a gamma photon detected by a CZTS detector. The CNN has been trained using simulated data that resemble output pulses from actual CZTS detectors when exposed to 662-keV gamma photons. The device properties required for the simulation have been derived from radiation detection measurements on a real Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 detector fabricated in our laboratory. The CNN has been trained with detector pulses arising through photoelectric (PE) and Compton scattering (CS) separately. The percentage error in predicting the detected energies, within an extremely small duration of 0.28 ms, was found to be lower than 0.1% for gamma energies above 50 keV and for training datasets con taining PE and CS events separately. The CNN was also validated for a mixed PE and CS dataset to obtain a prediction error of 1%. Additionally, the effect of detector resolution on the efficiency of the CNN was also explored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The carbon-concentrating mechanism of the extremophilic red microalga Cyanidioschyzon merolae

Abstract Cyanidioschyzon merolae is an extremophilic red microalga which grows in low-pH, high-temperature environments. The basis of C. merolae ’s environmental resilience is not fully characterized, including whether this alga uses a carbon-concentrating mechanism (CCM). To determine if C. merolae uses a CCM, we measured CO 2 uptake parameters using an open-path infra-red gas analyzer and compared them to values expected in the absence of a CCM. These measurements and analysis indicated that C. merolae had the gas-exchange characteristics of a CCM-operating organism: low CO 2 compensation point, high affinity for external CO 2 , and minimized rubisco oxygenation. The biomass δ 13 C of C. merolae was also consistent with a CCM. The apparent presence of a CCM in C. merolae suggests the use of an unusual mechanism for carbon concentration, as C. merolae is thought to lack a pyrenoid and gas-exchange measurements indicated that C. merolae primarily takes up inorganic carbon as carbon dioxide, rather than bicarbonate. We use homology to known CCM components to propose a model of a pH-gradient-based CCM, and we discuss how this CCM can be further investigated.

60 APPLIED LIFE SCIENCES↗

Cationic Effect of Ferrous Ions on Sulfide Capacity of CaO-Fe{sub t}O-Al{sub 2}O{sub 3}-SiO{sub 2} Slag System

The cationic effect of ferrous ions on the sulfide capacity of CaO-Fe{sub t}O-Al{sub 2}O{sub 3}-SiO{sub 2} slags was studied from the viewpoint of the ionic structure in the slag using micro-Raman spectroscopy. In the cation-excess region (M{sup 2+}/2(Fe{sup 3+} + Al{sup 3+}) > 1.0), the sulfide capacity was directly proportional to the basicity of the slags, owing to the S{sup 2−} stabilizing effect of excess cations. However, in the cation-deficient region (M{sup 2+}/2(Fe{sup 3+} + Al{sup 3+}) < 1.0), the sulfide capacity was independent of the basicity of the slags owing to the deficiency of cations required for charge compensation with Al{sup 3+} and Fe{sup 3+}. The cation-substitution effect on the sulfide capacity of the CaO-rich slags (Fe{sub t}O/(Fe{sub t}O + CaO < 0.5) exhibited a linear relationship with the Fe{sup 2+} content because Fe{sup 2+} had a stronger affinity with S{sup 2−} compared to that with Ca{sup 2+}. However, in the Fe{sub t}O-rich slags (Fe{sub t}O/(Fe{sub t}O + CaO > 0.5), the sulfide capacity decreased with the increase of the Fe{sup 2+} content owing to the Q{sup n} unit affinity of the Fe{sup 2+} ion. The sulfide capacity was determined by the competition between the Q{sup n} unit affinity and stability of the S{sup 2−} ion, depending on the type of cation. Therefore, the partial covalent bonding between the M{sup 2+} cations (M: Ca, Fe) and aluminosilicate affected the ionic interactions with the S{sup 2−} ions.

36 MATERIALS SCIENCE↗

Defect Thermodynamics and Transport Properties of Proton Conducting Oxide BaZr 1–x Y x O 3–δ (x ≤ 0.1) Guided by Density Functional Theory Modeling

Density functional theory-based thermodynamic modeling was performed to determine the effect of humidity and H 2 /O 2 gas pressure on the defect chemistry and transport properties of proton conducting oxide BaZr 1-x Y x O 3-δ (x ≤ 0.1) in the temperature range of 800–1200K, relevant for solid oxide fuel/electrolysis cell applications. The first-principles charge defect analysis was carried out to obtain the defect energetic ensembles as a function of Fermi level as well as the dependence of the hydration and oxidation reaction energies on complex defect-dopant configurations. It is shown that oxygen vacancies introduced to compensate for the extra Ba vacancies may cause a slight increase in the concentration of hydroxyl and proton species upon hydration of Ba deficient BaZr 1-x Y x O 3-δ , while the overall proton diffusivity is predicted to decrease with increased proton hopping barriers upon trapping near the Ba vacancies. The developed defect model is further demonstrated to be able to describe the bulk defect chemistry and transport properties of BaZr 0.9 Y 0.1 O 3-δ under the solid oxide cell operating conditions. Finally, the theoretical framework developed in this work further allows the inclusion of configurational, energetic and electronic characteristics of the defects that can be used as a complementary tool to experimental measurements for testing various mechanistic pathways or to provide essential mechanistic data.

36 MATERIALS SCIENCE↗

Miscanthus × giganteus Responses to Nitrogen Fertilization and Harvest Timing in Illinois, USA

Renewable energy continues to be of interest in the USA due to concerns about the long-termed availability and the environmental impact of fossil fuels. Miscanthus × giganteus is a warm-season perennial bioenergy feedstock grass that has a long growing season, is high yielding, requires limited inputs, and will likely become an important renewable energy crop in the USA. This research studied the effects of N application rates and harvest timings on yields and biomass quality of a 4-year-old stand of M. × giganteus in Urbana, IL, USA. Plots received 0, 56, 112, 156, or 224 kg N ha –1 , and harvests were conducted at five dates between August and March in the 2009, 2010, and 2011 growing seasons. Miscanthus × giganteus production increased with N applications up to 112 kg ha –1 . Harvesting biomass before senescence, August through November, produced significantly more biomass compared to harvesting biomass after senescence. However, early harvest reduced biomass yields in the following years. Here, nitrogen fertilization compensated for the yield losses, but the yield gap between early and late harvest continually increased. Harvesting M. × giganteus after senescence optimized long-term productivity, reduced the need for N fertilization, and increased carbon and ash content in the harvested biomass, while harvesting before senescence not only removes N from the plant but also reduces remobilization of other nutrients and carbohydrates in autumn.

09 BIOMASS FUELS↗

Assessing the Effectiveness of Large-Scale Environmental Restoration: Challenges and Opportunities

A recent National Academies consensus report addresses monitoring and assessment of cumulative effects of large-scale and multiple restoration projects within the context of long-term environmental change. Fines and penalties from the Deepwater Horizon oil spill in the Gulf of Mexico (GoM) have supported hundreds of restoration projects at spatial scales not often possible in the past. Here, in this paper, the report committee members and staff provide personal reflections from our time working on the study. We found that gaps in data collection, issues with data accessibility, and a lack of synthesis and analysis are hindering the ability to answer a basic question: What are the impacts of these many restoration efforts on improving ecosystem health and productivity in the GoM at the regional and Gulf wide scale? Restoration efforts are occurring in environments where many trends are changing and exhibiting higher variability than in the past, suggesting that previously successful restoration practices may no longer be adequate to compensate for the effects of environmental changes and variability. Our proposed approach to these challenges includes employing emerging monitoring technologies; using conceptual models; devising an adaptive management framework; rethinking restoration outcome goals; assessing cumulative effects; and undertaking rigorous synthesis and analysis of existing information on long-term environmental trends and restoration efforts. Restoration scientists and practitioners working in the GoM have an unprecedented opportunity to demonstrate large-scale environmental recovery if advances in monitoring, synthesis, assessment, and action are taken quickly. We are cautiously optimistic that, with mid-course adjustments, continued progress toward large-scale environmental recovery is possible.

54 ENVIRONMENTAL SCIENCES↗

Challenges and Opportunities of Integrating Electric Vehicles in Electricity Distribution Systems

Increased charging needs from widespread adoption of battery electric vehicles (EVs) will impact electricity demand. This will likely require a combination of potentially costly distribution infrastructure upgrades and synergistic grid-transportation solutions such as managed charging and strategic charger placement. Fully implementing such strategic planning and control methods - including business models and mechanisms to engage and compensate consumers - can minimize or even eliminate required grid upgrades. Moreover, there are also opportunities for EV charging to support the grid by helping solve existing and emerging distribution system challenges associated with increasing distributed energy resources (DERs) such as solar generation and battery energy storage. This paper reviews the potential impacts of EV charging on electricity distribution systems and describes methods from the literature to efficiently integrate EVs into distribution systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Further Development of the Tamped Richtmyer-Meshkov Instability Method and Application to Molybdenum Dynamic Strength Calibration and Tabulation

The high pressure and high strain rate dynamic strength of Mo is experimentally and computationally investigated in the 3–20 GPa stress, 50–600 C temperature, and 10 5 –10 6 /s strain rate regimes using a modified tamped Richtmyer-Meshkov instability (RMI) method. Modifications to the tamped RMI method include a method to determine loading states during strain, a new strength calibration function based on interface shape, and a robust uncertainty quantification method. These modifications improve fidelity of the tamped RMI method, allowing evaluation of the compensating effects of pressure hardening, strain rate hardening, strain hardening, and thermal softening. The new calibration function based on interface shape is not limited to sinusoidal corrugations and could be applied to additional interface shapes. Plate impact experiments are performed at Argonne National Laboratory’s Advanced Photon Source’s Dynamic Compression Sector operated by Washington State University (DCS), driving a planar shock front through a corrugated Mo-D 2 O or Mo-C 8 F 18 interface, forcing the corrugation to significantly deform. The extent of interfacial deformation, RMI growth, is experimentally observed using X-ray phase contrast imaging at the DCS. RMI jet lengths and jet shapes are extracted from the experimental radiographs, then used to calibrate numerical simulations performed with the Sandia National Laboratories (SNL) hydrocode CTH. Mo yield strength, Y, as a function of shock pressure, P, strain rate, $\dot{\varepsilon }$, accumulated strain, ϵ, relative volumetric compression, RD , and temperature, T , is determined for each impact experiment and presented. The calibrated Mo yield strength values range 1.2–1.8 GPa, with strength generally decreasing as the impact stress increases. This trend is likely caused by thermal softening or strain localization. The tabular yield strength versus loading condition data presented in this paper can be used to fit complex strength models.

Voorhees, T. J. [Sandia National Lab. (SNL-CA), Li↗

Numerical and experimental investigation of the geometry dependent layer-wise evolution of temperature during laser powder bed fusion of Ti–6Al–4V

Abstract Laser powder bed fusion (L-PBF) is currently the additive manufacturing process with the widest industrial use for metal parts. Yet some hurdles persist on the way to a widespread industrial serial production, with reproducibility of the process and the resulting part properties being a major concern. As the geometry changes, so do the local boundary conditions for heat dissipation. Consequently, the use of global, geometry-independent processing parameters, which are today’s state of the art, may result in varying part properties or even defects. This paper presents a numerical simulation as a method to predict the geometry-dependent temperature evolution during the build. For demonstration, an overhang structure with varying angles towards the build platform was manufactured using Ti–6Al–4V. A calibrated infrared camera was integrated into a commercial L-PBF system to measure the temperature evolution over time for a total build height of 10 mm, and the results are used for validation of the simulation. It is shown that the simulation is capable of predicting the temperature between layers. The deviations between simulation and measurement remain in single digit range for smaller overhang structures (90°, 60° and 45°). For large overhang structures (30°), the simulation tends to over-predict the temperatures up to 15 °C. Experiments with varying process parameters showed the feasibility of energy reduction as compensation of the heat accumulation produced by overhang structures.

Li, Gefei (ORCID:0000000174837952)↗

GeantV: Results from the Prototype of Concurrent Vector Particle Transport Simulation in HEP

Full detector simulation was among the largest CPU consumers in all CERN experiment software stacks for the first two runs of the Large Hadron Collider. In the early 2010s, it was projected that simulation demands would scale linearly with increasing luminosity, with only partial compensation from increasing computing resources. The extension of fast simulation approaches to cover more use cases that represent a larger fraction of the simulation budget is only part of the solution, because of intrinsic precision limitations. The remainder corresponds to speeding up the simulation software by several factors, which is not achievable by just applying simple optimizations to the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport code in order to benefit from features of fine-grained parallelism, including vectorization and increased locality of both instruction and data. This paper provides an extensive presentation of the results and achievements of this R&D project, as well as the conclusions and lessons learned from the beta version prototype.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ion Beam Figuring System for Synchrotron X-Ray Mirrors Achieving Sub-0.2-µrad and Sub-0.5-nm Root Mean Square

Abstract Optics with high-precision height and slope are increasingly desired in numerous industrial fields. For instance, Kirkpatrick–Baez (KB) mirrors play an important role in synchrotron X-ray applications. A KB system is composed of two aspherical, grazing-incidence mirrors used to focus an X-ray beam. The fabrication of KB mirrors is challenging due to the aspherical departure of the mirror surfaces from base geometries and the high-quality requirements for slope and height residuals. In this paper, we present the process of manufacturing an elliptical cylinder KB mirror using our in-house-developed ion beam figuring (IBF) and metrology technologies. First, the key aspects of figuring and finishing processes with IBF are illustrated in detail. The effect of positioning error on the convergence of the residual slope error is highlighted and compensated. Finally, inspection and cross-validation using different metrology instruments are performed and used as the final validation of the mirror. Results confirm that relative to the requested off-axis ellipse, the mirror has achieved 0.15-µrad root mean square (RMS) and 0.36-nm RMS residual slope and height errors, respectively, while maintaining the initial 0.3-nm RMS microroughness.

36 MATERIALS SCIENCE↗

Moderate active Fe 3+ doping enables improved cationic and anionic redox reactions for wide-voltage-range sodium storage

Layered metal oxides are promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical specific capacity and wide Na + diffusion channels. However, the irreversible phase transitions and cationic/anionic redoxes cause fast capacity decay. Herein, P2-type Na 0.67 Mg 0.1 Mn 0.8 Fe 0.1 O 2 (NMMF-1) cathode material with moderate active Fe 3+ doping has been designed for sodium storage. Uneven Mn 3+ /Mn 4+ distribution is observed in NMMF-1 and the introduction of Fe 3+ is beneficial for reducing the Mn 3+ contents both at the surface and in the bulk to alleviate the Jahn–Teller effect. The moderate Fe 3+ /Fe 4+ redox can realize the best tradeoff between capacity and cyclability. Therefore, the NMMF-1 demonstrates a high capacity (174.7 mAh g -1 at 20 mA g -1 ) and improved cyclability (78.5% over 100 cycles) in a wide-voltage range of 1.5–4.5 V (vs. Na + /Na). In-situ X-ray diffraction reveals a complete solid-solution reaction with a small volume change of 1.7% during charge/discharge processes and the charge compensation is disclosed in detail. This study will provide new insights into designing high-capacity and stable layered oxide cathode materials for SIBs.

25 ENERGY STORAGE↗

Ultrahigh temperature in situ transmission electron microscopy based bicrystal coble creep in Zirconia II: Interfacial thermodynamics and transport mechanisms

This work uses a combination of stress dependent single grain boundary Coble creep and zero-creep experiments to measure interfacial energies, along with grain boundary point defect formation and migration volumes in cubic ZrO 2 . These data, along with interfacial diffusivities measured in a companion paper are then applied to analyzing two-particle sintering. The analysis presented here indicates that the large activation volume, v * = v f + v m primarily derives from a large migration volume and suggests that the grain boundary rate limiting defects are delocalized, possibly due to electrostatic interactions between charge compensating defects. The discrete nature of the sintering and creep process observed in the small-scale experiments supports the hypothesis that grain boundary dislocations serve as sources and sinks for grain boundary point defects and facilitate strain during sintering and Coble creep. Model two-particle sintering experiments demonstrate that initial-stage densification follows interface reaction rate-limited kinetics.

36 MATERIALS SCIENCE↗

From bulk to surface: Structure and dynamics of amorphous alumina from deep potential molecular dynamics

Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio -quality models of amorphous Al 2 O 3 bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 Å, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al–O bonds, and hosts a broad population of under-coordinated motifs (notably AlO 3 and OAl 2 ) whose abundances are governed by glass stability. These under-coordinated surface motifs exhibit distinct vibrational signatures and occur as locally paired Lewis acid and Brønsted base sites consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, surface relaxation and the glass-transition temperature remain comparable to their bulk counterparts, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure–property relationships in disordered oxide interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distributed strain sensing using Bi-metallic coated fiber optic sensors embedded in stainless steel

Silica fiber optic sensors are resistant to corrosive environments and high temperatures, making them attractive candidates for harsh conditions found in nuclear and aerospace industries. Moreover, fibers can be deployed remotely for continuous measuring of spatially distributed temperatures and strains. Here, this study investigated embedding a Ni/Cu bi-metallic coated fiber in a stainless-steel 316 (SS316) matrix using laser powder bed fusion towards functionalizing metal components for site-specific health monitoring. The embedded fiber was continuously interrogated during controlled heating to 1000°C. The measured fiber strains were similar to the expected differential thermal strains between the fiber and the SS316 matrix, until divergent behavior was observed at temperatures >500°C. No debonding at the matrix–coating–fiber interfaces was observed during microscopy, but significant interactions between the coatings and matrix resulted in diffusion-driven chemistry variations and Kirkendall void formation. Applying the strain-lag theory revealed plastic behavior in the Ni coating at temperatures >500°C, limiting the strain transfer to the fiber at higher temperatures. It was estimated that the elastic modulus in the Ni coating had decreased from ~200 GPa at room temperature to below 40 GPa, starting at 600°C. The low elastic modulus above 600°C is within the margin of what the tangent modulus would be in the case of bilinear isotropic hardening. Regardless of the divergent strain transfer at higher temperatures, the fiber was exposed to the equivalent of 1.9 % engineering strain at 1000°C, but measured only a 0.7 % engineering strain due to the poor strain transfer. Although compensating for the plastic behavior of Ni proved challenging, the bonding of a brittle silica fiber to a metal matrix surviving to 1000°C invites potential iterations on coating material for future application. For example, the embedded fiber is sufficient for acoustic energy transfer, realizing high temperature distributed acoustic sensing.

36 MATERIALS SCIENCE↗