Noncentrosymmetric Tetrel Pnictides RuSi[subscript 4]P[subscript 4] and IrSi[subscript 3]P[subscript
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Lee, Shannon↗
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Results for “LASERS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Flexible CO 2 Sensor Architecture with Selective Nitrogen Functionalities by One‐Step Laser‐Induced Conversion of Versatile Organic Ink
Abstract Nitrogen‐containing carbons (NC) are a class of sustainable materials for selective CO 2 adsorption. A versatile concept is introduced to fabricate flexible NC‐based sensor architectures for room‐temperature sensing of CO 2 in a one‐step laser conversion of primary films cast from abundant precursors. By the unidirectional energy impact in conjunction with depth‐dependent attenuation of the laser beam, a layered sensor heterostructure with a porous transducer and active sensor layer is formed. Comprehensive microscopic and spectroscopic cross‐sectional analyses confirm the preservation of the high content of imidazolic nitrogen in the sensor. The performance is optimized in terms of material morphology, chemical composition, and surface chemistry to achieve a linear relative resistive response of up to Δ R / R 0 = −14.3% (10% of CO 2 ). Thermodynamic analysis yields Δ ads H values of −35.6 and 34.1 kJ·mol −1 for H 2 O and CO 2 , respectively. The sensor is operable even in humid environments (e.g., ∆ R / R 0,RH = 80% = 0.53%) and shows good performance upon strong mechanical deformation.
flexible gas sensors↗
Magnetic‐Field‐Switchable Laser via Optical Pumping of Rubrene
Abstract Volumetric optical imaging of magnetic fields is challenging with existing magneto‐optical materials, motivating the search for dyes with strong magnetic field interactions, distinct emission spectra, and an ability to withstand high photon flux and incorporation within samples. Here, the magnetic field effect on singlet‐exciton fission is exploited to demonstrate spatial imaging of magnetic fields in a thin film of rubrene. Doping rubrene with the high‐quantum yield dye dibenzotetraphenylperiflanthene (DBP) is shown to enable optically pumped, slab waveguide lasing. This laser is magnetic‐field‐switchable: when operated just below the lasing threshold, application of a 0.4 T magnetic field switches the device between nonlasing and lasing modes, accompanied by an intensity modulation of +360%. This is thought to be the first demonstration of a magnetically switchable laser, as well as the largest magnetically induced change in emission brightness in a singlet‐fission material to date. These results demonstrate that singlet‐fission materials are promising materials for magnetic sensing applications and could inspire a new class of magneto‐optical modulators.
36 MATERIALS SCIENCE↗
Sub‐0.6 eV Inverted Metamorphic GaInAs Cells Grown on Inp and GaAs Substrates for Thermophotovoltaics and Laser Power Conversion
Abstract Inverted metamorphic Ga 0.3 In 0.7 As photovoltaic converters with sub‐0.60 eV bandgaps grown on InP and GaAs are presented. Threading dislocation densities are 1.3 ± 0.6 × 10 6 and 8.9 ± 1.7 × 10 6 cm −2 on InP and GaAs, respectively. The devices generate open‐circuit voltages of 0.386 and 0.383 V, respectively, under irradiance producing a short‐circuit current density of ≈10 A cm −2 , yielding bandgap‐voltage offsets of 0.20 and 0.21 V. Power and broadband reflectance measurements are used to estimate thermophotovoltaic (TPV) efficiency. The InP‐based cell is estimated to yield 1.09 W cm −2 at 1100 °C versus 0.92 W cm −2 for the GaAs‐based cell, with efficiencies of 16.8 versus 9.2%. The efficiencies of both devices are limited by sub‐bandgap absorption, with power weighted sub‐bandgap reflectances of 81% and 58%, respectively, the majority of which is assumed to occur in the graded buffers. The 1100 °C TPV efficiencies are estimated to increase to 24.0% and 20.7% in structures with the graded buffer removed, if previously demonstrated reflectance is achieved. These devices also have application to laser power conversion in the 2.0–2.3 µm atmospheric window. Peak laser power converter efficiencies of 36.8% and 32.5% are estimated under 2.0 µm irradiances of 1.86 and 2.81 W cm −2 , respectively.
14 SOLAR ENERGY↗
Cell-Type-Specific Proteomics Analysis of a Small Number of Plant Cells by Integrating Laser Capture Microdissection with a Nanodroplet Sample Processing Platform
Plant organs and tissues contain multiple cell types, which are well organized in 3-dimensional structure to efficiently perform physiological functions such as homeostasis, response to environmental perturbation, pathogen infection. It is critically important to perform molecular measurements at the cell-type-specific level to discover mechanisms and unique features of cell populations that govern differentiation and respond to external perturbations. Although mass spectrometry-based proteomics has been demonstrated as an enabling discovery tool to study plant physiology, conventional approaches require millions of cells to generate robust biological conclusions. Such requirements mask the cell-to-cell heterogeneities and limit the comprehensive profiling of plant proteins at spatially resolved and cell-type-specific resolutions. This protocol describes a recently-developed proteomics workflow for studying a small number of plant cells by integrating laser capture microdissection, microfluidic nanodroplet-based sample preparation, with ultrasensitive liquid chromatography-mass spectrometry. Using poplar as a model tree species, we provide detailed protocols, including plant tissue harvest, tissue preparation, cryosectioning, laser microdissection, protein digestion, mass spectrometry measurement, and data analysis. We show the workflow enables the precise identification and quantification of thousands of proteins from hundreds of isolated plant root and leaf cells.
59 BASIC BIOLOGICAL SCIENCES↗
Enhanced Laser-Induced Graphene Microfluidic Integrated Sensors (LIGMIS) for On-Site Biomedical and Environmental Monitoring
The convergence of microfluidic and electrochemical biosensor technologies offers significant potential for rapid, in-field diagnostics in biomedical and environmental applications. Traditional systems face challenges in cost, scalability, and operational complexity, especially in remote settings. Addressing these issues, laser-induced graphene microfluidic integrated sensors (LIGMIS) are presented as an innovative platform that integrates microfluidics and electrochemical sensors both comprised of laser-induced graphene. This study advances the LIGMIS concept by resolving issues of uneven fluid transport, increased hydrophobicity during storage, and sensor biofunctionalization challenges. Key innovations include Y-shaped reservoirs for consistent fluid flow, hydrophilic polyethyleneimine coatings to maintain wettability, and separable microfluidic and electrochemical components enabling isolated electrode nanoparticle metallization and biofunctionalization. Multiplexed electrochemical detection of the neonicotinoid imidacloprid and nitrate ions in environmental water samples yields detection limits of 707 nm and 10 -5.4 m with wide sensing ranges of 5–100 µm and 10 -5 –10 -1 m, respectively. Similarly, uric acid and calcium ions are detected in saliva, demonstrating detection limits of 217 nm and 10 -5.3 m with sensing ranges of 10–50 µm, and 10 -5 –10 -2.5 m, respectively. Overall, this biosensing demonstrates the capability of the LIGMIS platform for multiplexed detection in biologically complex solutions, with applications in environmental water quality monitoring and oral cancer screening.
environmental monitoring↗
Laser-induced selective local patterning of vanadium oxide phases
The same elements can form different compounds with widely different physical properties. Synthesis of a single-phase material is commonly achieved by controlling experimental conditions. Synthesizing materials that incorporate multiple specific spatially distributed chemical phases is often challenging, especially if different phases must be organized into well-defined spatial patterns. Here, we present an efficient solid reaction laser annealing (SRLA) approach to directly write regions of different local chemical compositions. We demonstrate the practical utility of our approach by locally writing microscale patterns of distinct chemical phases in vanadium oxide thin films. Specifically, we achieved the controlled local recrystallization of a uniform V 2 O 3 matrix into VO 2 , V 3 O 5 , and V 4 O 7 regions exhibiting sharp 1st- and 2nd-order metal–insulator phase transitions over a wide range of critical temperatures, i.e., a characteristic feature of select vanadium oxides that is extremely sensitive to even minute structural or compositional imperfections. We utilized the local chemical phase writing to pattern spiking oscillators with distinct electrical behavior directly in the thin film sample without employing elaborate lithography fabrication. Our laser tuning local chemical composition opens a pathway to synthesize a wide range of artificially micropatterned composite materials, with precision and control unattainable in conventional material synthesis methods.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Synthesis of a 316L stainless steel-copper composite by laser melting
This paper demonstrates a laser melting method to produce a metal matrix composite with a higher thermal conductivity compared to 316 L stainless steel using a Jettable Cu ink. A novel canister was used to control the oxygen level during laser processing to emulate a hybrid inkjet-powder bed fusion technique for doping the stainless steel powder bed with Cu precursor ink. Here, the thermal conductivity of the composite was found to be 187% higher than that of 316 L stainless steel, while the microhardness decreased by 39%. Microstructural results show opportunities to further enhance the thermal conductivity and mechanical properties of the composite by eliminating interfacial cracking.
36 MATERIALS SCIENCE↗
Selective laser melting of 304L stainless steel: Role of volumetric energy density on the microstructure, texture and mechanical properties
The role of volumetric energy density on the microstructural evolution, texture and mechanical properties of 304L stainless steel parts additively manufactured via selective laser melting process is investigated. 304L is chosen because it is a potential candidate to be used as a matrix in a metal matrix composite with nanoparticles dispersion for energy and high temperature applications. The highest relative density of 99 %±0.5 was achieved using a volumetric energy density of 1400 J/mm 3 . Both XRD analysis and Scheil simulation revealed the presence of a small trace of the delta ferrite phase, due to rapid solidification within the austenitic matrix of 304L. Here, a fine cellular substructure ranged between 0.4–1.8 μm, was detected across different energy density values. At the highest energy density value, a strong texture in the direction of [100] was identified. At lower energy density values, multicomponent texture was found due to high nucleation rate and the existing defects. Yield strength, ultimate tensile strength, and microhardness of samples with a relative density of 99 % were measured to be 540 ± 15 MPa, 660 ± 20 MPa and 254 ± 7 HV, respectively and higher than mechanical properties of conventionally manufactured 304L stainless steel. Heat treatment of the laser melted 304L at 1200 °C for 2 h, resulted in the nucleation of recrystallized equiaxed grains followed by a decrease in microhardness value from 233 ± 3 HV to 208 ± 8 HV due to disappearance of cellular substructure.
304L stainless steel↗
Correlations between thermal history and keyhole porosity in laser powder bed fusion
Additive manufacturing has the potential to revolutionize the production of metallic components as it yields near net shape parts with complex geometries and minimizes waste. At the present day, additively manufactured components face qualification and certification challenges due to the difficulty in controlling defects. This has driven a significant research effort aimed at better understanding and improving processing controls – yielding a plethora of in-situ measurements aimed at correlating defects with material quality metrics of interest. In this work, we develop machine-learning methods to learn correlations between thermal history and subsurface porosity for a variety of print conditions in laser powder bed fusion. Un-normalized surface temperatures (in the form of black-body radiances) are obtained using high-speed infrared imaging and porosity formation is observed in the sample cross-section through synchrotron x-ray imaging. To demonstrate the predictive power of these features, we present four statistical machine-learning models that correlate temperature histories to subsurface porosity formation in laser fused Ti-6Al4V powder.
36 MATERIALS SCIENCE↗
The origin and formation of oxygen inclusions in austenitic stainless steels manufactured by laser powder bed fusion
The origins of nano-scale oxide inclusions in 316L austenitic stainless steel (SS) manufactured by laser powder bed fusion (L-PBF) was investigated by quantifying the possible intrusion pathways of oxygen contained in the precursor powder, extraneous oxygen from the process environment during laser processing, and moisture contamination during powder handling and storage. When processing the fresh, as-received powder in a wellcontrolled environment, the oxide inclusions contained in the precursor powder were the primary contributors to the formation of nano-scale oxides in the final additive manufactured (AM) product. These oxide inclusions were found to be enriched with oxygen getter elements like Si and Mn. By controlling the extraneous oxygen level in the process environment, the oxygen level in AM produced parts was found to increase with the extraneous oxygen level. The intrusion pathway of this extra oxygen was found to be dominated by the incorporation of spatter particles into the build during processing. Moisture induced oxidation during powder storage was also found to result in a higher oxide density in the AM produced parts. SS 316L powder free of Si and Mn oxygen getters was processed in a well-controlled environment and resulted in a similar level of oxygen intrusion. Finally, microhardness testing indicated that the oxide volume fraction increase from extraneous oxygen did not influence hardness values. However, a marked decrease in hardness was found for the humidified and Si-Mn free AM processed parts.
36 MATERIALS SCIENCE↗
Types of spatter and their features and formation mechanisms in laser powder bed fusion additive manufacturing process
Spatter causes defect formation, powder redistribution and contamination in laser powder bed fusion (LPBF) additive manufacturing process. It is critical to distinguish different types of spatter and understand their features and formation mechanisms. This work reveals the features and formation mechanisms of five unique types of spatter during the LPBF process by in-situ high-speed, high-energy x-ray imaging. Spatters observed during LPBF testing are quantified by their speed, size, and direction. Distinct quantifiable characteristics for each type of spatter are identified. Finally, effects of the laser power, scan speed, and ambient pressure on spatter formation and features are unraveled. A spatter formation map for AlSi10Mg alloy is constructed.
36 MATERIALS SCIENCE↗
Synthesis of precipitation-strengthened Al-Sc, Al-Zr and Al-Sc-Zr alloys via selective laser melting of elemental powder blends
Selective laser melting is used to create Al-1.5Sc, Al-1.5Zr and Al-0.75Sc-0.75Zr (at.%) alloys from blends of elemental Al, Sc, and Zr powders. This study investigates elemental alloying elements (Sc and Zr) which are high-melting and highly reactive, unlike previous work which focused on more concentrated elemental additions of lower-melting, lower-reactivity Cu and Si to aluminum. High-speed in situ synchrotron x-ray imaging and diffraction show that the 20–30 μm Al, Sc, and Zr powders fully melt and sufficiently mix in the molten state to create, on solidification, a homogeneous distribution of primary, micron-size L12 precipitates (Al 3 Sc, Al 3 Zr, and Al 3 (Sc,Zr), respectively) and nucleate micron-size Al matrix grains, as confirmed by SEM imaging of cross-sections. Here, a second laser pass, simulating a realistic additive-manufacturing build condition, fully remelts the initial volume which shows, after solidification, the same Al 3 (Sc,Zr) L1 2 primary micro-precipitates and very fine Al grains. After aging at 300–400°C, the alloys show large increases in hardness, consistent with an exceptionally high number density (1.4 × 10 24 m –3 ) and volume fraction (2.5%) of secondary Al 3 (Sc,Zr) nano-precipitates with a Sc-rich core and Zr-rich shell, as measured via atom-probe tomography.
36 MATERIALS SCIENCE↗
Laser powder bed fusion of Inconel 718 on 316 stainless steel
The joining of Inconel 718 and 316 stainless steel has notable industrial importance. However, traditional arc-welding has many issues. In particular, the formation of the detrimental Nb-rich Laves phase in the heat affected zone can promote crack initiation and propagation, which leads to poor mechanical properties. The small heat input and the rapid solidification of laser powder bed fusion (PBF) has the potential to suppress this problem. Despite the infancy of the multi-material PBF, it is of interest to investigate the relationship among the process parameter, the microstructure at the materials joining point, and the mechanical performance. In this study, we used high-speed x-ray imaging to in-situ monitor the printing of Inconel 718 tracks on a 316H SS substrate via laser powder bed fusion, followed by post-build characterization and testing with SEM, XRD and nanoindentation. We observed that a higher linear energy density resulted in a more diffused interface and a smaller compositional gradient, but as a trade-off, generated more keyhole pores and thermal cracks. Furthermore, we also showed that the built layer exhibited chemical inhomogeneity at two length scales: a tens-of-mu m-scale compositional vortex due to the melt flow, and a sub-mu m-scale Nb-rich dendritic structure due to the non-equilibrium solidification that led to the formation of the Laves phase. It was inferred that the chemical inhomogeneity may benefit the mechanical properties at the interface by providing more interlocking between the two materials and also by limiting the effect of the brittle Laves phase to potentially short range.
36 MATERIALS SCIENCE↗
A new procedure for implementing the modified inherent strain method with improved accuracy in predicting both residual stress and deformation for laser powder bed fusion
As a metal additive manufacturing (AM) process, laser powder bed fusion (L-PBF) has been widely used to produce parts with complex geometries. The large thermal gradient caused by the fast, intense, and repeated laser scanning induces significant residual deformation and stress to the as-built parts, which increase manufacturing difficulty and geometrical inaccuracy as a result. The modified inherent strain (MIS) method exploiting multiscale process simulations was developed to simulate residual deformation accurately and efficiently. However, the existing procedure of implementing the MIS method is found to give inaccurate residual stress prediction. Here in this work, a new implementation procedure for the MIS method is proposed to improve the simulation accuracy of residual stress without degrading the residual deformation prediction. The new procedure concerns the application of inherent strains to the part-scale layer-by-layer finite element model to obtain residual stress and deformation field. While the existing implementation of the part-scale MIS model involves only mechanical properties at ambient temperature, the new procedure adds one more solution step employing mechanical properties at an elevated temperature determined from the inherent strain extraction step. Both numerical and experimental studies are conducted to validate the proposed new implementation procedure. It shows that by using the new procedure, the MIS-based simulation can predict both residual stress and deformation of as-built L-PBF metal parts with good accuracy.
36 MATERIALS SCIENCE↗
Nanoparticle-enhanced absorptivity of copper during laser powder bed fusion
We report laser powder bed fusion (LPBF) of pure copper for thermal and electrical applications is hampered by its low near-infrared absorptivity and high thermal diffusivity. These material properties make it very difficult to localize the thermal energy needed to produce high density 3D printed parts. Modification of metal powders via nanoparticle additives is a promising approach to increasing absorptivity, but the effect of nanoparticles on absorptivity and melting behavior during LPBF is not well understood. In this study, we developed an in situ calorimetry system to measure effective absorptivity during LPBF on copper substrates. We decorated copper substrates using three nanoparticle systems (CuS, TiB 2 , multilayer graphene flakes) and demonstrated an enhanced absorptivity of the decorated substrates relative to pure copper. Graphene nanoflakes resulted in the highest improved absorption relative to pure copper from 0.09 to 0.48, due to their stability at high laser scanning powers. A thermomechanical model with convective heat transfer provided confidence in the measurements by reproducing the experimental melt pool traces. Full 3D cylindrical prints demonstrated an improvement in relative density of the copper-graphene powder prints (in the range of 0.930–0.992), relative to that of as-purchased copper powder prints (in the range of 0.854–0.972). This work provides a fundamental study of nanoparticle-enabled LPBF of highly reflective metals and demonstrates a viable route for expanding the library of reliably printable metals.
36 MATERIALS SCIENCE↗
Remarkable enhancement in thermal conductivity of stainless-steel leveraging metal composite via laser powder bed fusion: 316L-Cu composite
This work aimed to significantly enhance the thermal conductivity of the SS matrix by fabricating a metal composite SS-Cu system utilizing a laser powder bed fusion process. The impact of process parameters on the microstructure of SS-Cu samples is investigated. Here, the processing and post-processing factors that influence the effective thermal conductivity of the metal composite SS-Cu system are discussed. Then, the effective thermal conductivity and mechanical properties of the SS-Cu composite are measured at room temperature and operating temperature of 300 °C. The optimized laser powder bed fusion parameters led to low Marangoni convection, high cooling rate, greater macro-segregation, and higher thermal conductivity values albeit at the cost of ductility in SS-Cu metal composite likely due to the presence of the unmelted powder particles. As-printed SS-60 vol % Cu and annealed SS-60 vol % Cu had 2.5X and 6.6X thermal conductivity enhancement, respectively. During annealing, phase separation, partial melting of Cu, and formation of a continuous network of Cu surrounding SS play a key role in enhancing the thermal conductivity of the SS-Cu metal composite structure.
36 MATERIALS SCIENCE↗
Localized keyhole pore prediction during laser powder bed fusion via multimodal process monitoring and X-ray radiography
Systematic fault detection and control during laser powder bed fusion (L-PBF) has been a long-standing objective for system manufacturers and researchers in the additive manufacturing (AM) industry. This manuscript investigates a data fusion approach for detection of keyhole porosity formation during laser irradiation of Ti-6Al-4V substrates by concurrent recording of thermally induced optical emission measured using both off-axis and coaxial photodiode sensors, and acoustic emission. Subsurface defect formation was monitored via high-speed synchrotron X-ray imaging at 20,000 frames per second, enabling temporal registration of keyhole pore formation events to the monitoring signals at a resolution of 50 µs. We developed data fusion machine learning (ML) models for localized prediction of keyhole pore formation at various time scales ranging from 0.5 ms to 2 ms. The signal segments were featurized using two independent approaches: (1) power spectral density (PSD) and (2) highly comparative time series analysis (HCTSA) framework. The extracted features from different sensor modalities were fused together to construct a multimodal feature space and sequential feature selection was used to determine the most informative features for training the ML models. The predictive performance was evaluated for three classifying algorithms: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Gaussian Naive Bayes (GNB). As a result, pore formation events were predicted with up to 0.95 F1-score, 1.0 recall and 0.94 accuracy. The most heavily weighted features indicate that model performance is chiefly governed by the acoustic monitoring signal, with a secondary contribution from the optical emission sensors.
36 MATERIALS SCIENCE↗