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At least 199 records · Page 11

Relating Molecular Properties to the Persistence of Marine Dissolved Organic Matter with Liquid Chromatography–Ultrahigh-Resolution Mass Spectrometry

Marine dissolved organic matter (DOM) contains a complex mixture of small molecules that eludes rapid biological degradation. Spatial and temporal variations in the abundance of DOM reflect the existence of fractions that are removed from the ocean over different time scales, ranging from seconds to millennia. However, it remains unknown whether the intrinsic chemical properties of these organic components relate to their persistence. Here, we elucidate and compare the molecular compositions of distinct DOM fractions with different lability along a water column in the North Atlantic Gyre. Our analysis utilized ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry at 21 T coupled to liquid chromatography and a novel data pipeline developed in CoreMS that generates molecular formula assignments and metrics of isomeric complexity. Clustering analysis binned 14 857 distinct molecular components into groups that correspond to the depth distribution of semilabile, semirefractory, and refractory fractions of DOM. The more labile fractions were concentrated near the ocean surface and contained more aliphatic, hydrophobic, and reduced molecules than the refractory fraction, which occurred uniformly throughout the water column. These findings suggest that processes that selectively remove hydrophobic compounds, such as aggregation and particle sorption, contribute to variable removal rates of marine DOM.

54 ENVIRONMENTAL SCIENCES↗

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

A Bayesian approach to time-domain photonic Doppler velocimetry analysis

Photonic Doppler velocimetry (PDV) is an established technique for measuring the velocities of fast-moving surfaces in high-energy-density experiments. In the standard approach to PDV analysis, the short-time Fourier transform (STFT) is used to generate a spectrogram from which the velocity history of the target is inferred. The user chooses the form, duration, and separation of the window function. Here, in this study, we present a Bayesian approach to infer the velocity directly from the PDV oscilloscope trace, without using the spectrogram for analysis. This is clearly a difficult inference problem due to the highly periodic nature of the data, but we find that with carefully chosen prior distributions for the model parameters, we can accurately recover the injected velocity from synthetic data. We validate this method using PDV data collected at the STAR two-stage light gas gun at Sandia National Laboratories, recovering shock-front velocities in quartz that are consistent with those inferred using the STFT-based approach and are interpolated across regions of low signal-to-noise data. Although this method does not rely on the same user choices as the STFT, we caution that it can be prone to misspecification if the chosen model is not sufficient to capture the velocity behavior. Analysis using posterior predictive checks can be used to establish whether a better model is required, although more complex models come with additional computational cost, often taking more than several hours to converge when sampling the Bayesian posterior. We, therefore, recommend it be viewed as a complementary method to that of the STFT-based approach.

Allison, James R. [First Light Fusion Ltd., Yarnto↗

Joint cosmological fits to DESI-DR1 full-shape clustering and weak gravitational lensing in configuration space

We present a joint $3\times2$-pt cosmological analysis of auto- and cross-correlations between the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) Bright Galaxy Survey (BGS) and Luminous Red Galaxy (LRG) samples and overlapping shear measurements from the KiDS-1000, DES-Y3 and HSC-Y3 weak lensing surveys. We perform our analysis in configuration space and, in addition to the cosmic shear correlation functions for each weak lensing dataset, we fit the tangential shear of the weak lensing source galaxies around DESI lens galaxies. Finally, we make use of the anisotropic BGS and LRG clustering information by fitting the full shape of the two-point correlation function multipoles measured over the full DESI-DR1 footprint, presenting the first full-shape analysis of DESI measurements in configuration space. We find that the addition of weak lensing information serves to improve, with respect to the clustering-only case, the measurements of the power spectrum amplitude parameters $\ln(10^{10}A_{\rm{s}})$ and $σ_{12}$ by $15\%$ and $36\%$, respectively. It also improves measurements of the linear bias of the lens galaxies by $15-20\%$, depending on the tracer. Our results show excellent consistency, regardless of the weak lensing survey considered, and are furthermore consistent with a companion analysis that fits $3\times2$-pt correlations including DESI projected clustering measurements, as well as the results published by the weak lensing collaborations themselves. Our measured values for weak lensing amplitude are $S_{8}^{\mathrm{DESI\times HSC}}=0.787\pm0.020$, $S_{8}^{\mathrm{DESI\times DES}}=0.791\pm0.016$, $S_{8}^{\mathrm{DESI\times KiDS}}=0.771\pm0.017$, which are $1.9σ-2.9σ$ below the $S_8$ value preferred by Planck. Finally, our clustering-only results are in good agreement with the Fourier space full-shape analysis of all DESI tracers.

Semenaite, A. [Swinburne U., Ctr. Astrophys. Super↗

The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: N-body Mock Challenge for Galaxy Clustering Measurements

We develop a series of N-body data challenges, functional to the final analysis of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) galaxy sample. The challenges are primarily based on high-fidelity catalogues constructed from the Outer Rim simulation - a large box size realization (3h(-1) Gpc) characterized by an unprecedented combination of volume and mass resolution, down to 1.85 x 10(9) h(-1)M(circle dot). We generate synthetic galaxy mocks by populating Outer Rim haloes with a variety of halo occupation distribution (HOD) schemes of increasing complexity, spanning different redshift intervals. We then assess the performance of three complementary redshift space distortion (RSD) models in configuration and Fourier space, adopted for the analysis of the complete DR16 eBOSS sample of Luminous Red Galaxies (LRG5). We find all the methods mutually consistent, with comparable systematic errors on the Alcock-Paczynski parameters and the growth of structure, and robust to different HOD prescriptions - thus validating the robustness of the models and the pipelines used for the baryon acoustic oscillation (BAO) and full shape clustering analysis. In particular, all the techniques are able to recover and alpha(11) to within 0.9 per cent, and f sigma(8) to within 1.5 per cent. As a by-product of our work, we are also able to gain interesting insights on the galaxy-halo connection. Our study is relevant for the final eBOSS DR16 'consensus cosmology', as the systematic error budget is informed by testing the results of analyses against these high-resolution mocks. In addition, it is also useful for future large-volume surveys, since similar mock-making techniques and systematic corrections can be readily extended to model for instance the Dark Energy Spectroscopic Instrument (DESI) galaxy sample.

cosmology: theory, large-scale structure of Univer↗

MXene Reinforced Thermosetting Composite for Lightning Strike Protection of Carbon Fiber Reinforced Polymer

Ti 3 C 2 – a member of the MXenes (2D transition metal carbides and nitrides) family, is investigated as an effective filler to improve the electrical, mechanical, and thermal properties of divinylbenzene (DVB) thermosetting resin. Consequently, its performance as a lightning strike protection (LSP) coating for carbon fiber reinforced polymer (CFRP) is evaluated. Polyaniline (PANI) – dodecylbenzene sulfonic acid (DBSA) complex is used to cure the DVB resin. The synergic effect of MXenes (with surface that is negatively charged) with polyaniline (positive charge) shows electrostatic bonding and improved electrical conductivity in the composite. We also find that the addition of MXenes at 2 wt% into the PANI-DVB composite shows ≈139%, 10%, and 9% improvement in electrical conductivity, flexural strength, and flexural modulus, respectively, compared to the neat PANI-DVB composite. The composites are investigated using various material characterization techniques including Fourier transforms infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, and scanning electron microscopy. Furthermore, MXenes-DVB is utilized to create a conductive thermosetting coating on top of a CFRP substrate and tested against a lightning strike of 100 kA. CFRP with MXenes-DVB coating reduced the surface damage from 40.61 cm 2 (reference CFRP panel) to 13.29 cm 2 (CFRP coated with MXenes-DVB).

36 MATERIALS SCIENCE↗

Geometrical quasi-ballistic effects on thermal transport in nanostructured devices

In this work, we employ thermoreflectance thermal imaging to directly measure the steady-state two-dimensional (2D) temperature field generated by nanostructured heat sources deposited on silicon substrate with different geometrical configurations and characteristic sizes down to 400nm. The analysis of the results using Fourier’s law not only breaks down as size scales down, but it also fails to capture the impact of the geometry of the heat source. The substrate effective Fourier thermal conductivities fitted to wire-shaped and circular-shaped structures with identical characteristic lengths are found to display up to 40% mismatch. Remarkably, a hydrodynamic heat transport model reproduces the observed temperature fields for all device sizes and shapes using just intrinsic Si parameters, i.e., a geometry and size-independent thermal conductivity and nonlocal length scale. The hydrodynamic model provides insight into the observed thermal response and of the contradictory Fourier predictions. We discuss the substantial Silicon hydrodynamic behavior at room temperature and contrast it to InGaAs, which shows less hydrodynamic effects due to dominant phonon-impurity scattering.

42 ENGINEERING↗

Carbon monoxide chemistry of α-V70I Mo-nitrogenase: Evidence from EPR- and IR-monitored photolysis – or, what a difference a methyl makes

A critical step in the global nitrogen cycle is the conversion of dinitrogen into biologically accessible ammonia. In Nature this is accomplished by the nitrogenase (N 2 ase) family of enzymes. Carbon monoxide (CO) has long been known as an inhibitor of dinitrogen reduction by N 2 ase, but it can also be a substrate of the enzyme, when it is catalytically reduced to hydrocarbons. Understanding the CO interactions with N 2 ases are thus relevant to both dinitrogen fixation and Fischer-Tropsch-like chemistry. Here, in this work, the interaction of CO with the α-V70I variant of Azotobacter vinelandii MoFe N 2 ase was investigated using electron paramagnetic resonance (EPR) and infrared (IR) monitored photolysis of bound CO under cryogenic conditions. This was supplemented by further analysis of stopped-flow Fourier transform IR (SF-FT-IR) data under turnover conditions. The α-V70I variant adds a single methyl group close to the FeMo-cofactor active site, and the results show that this inhibits and slows, but does not substantially chemically change, the binding of CO to the FeMocofactor. The EPR spectra of both the hi-CO and lo-CO states closely resemble those from the wild-type enzyme. Similarly, the SF-FT-IR spectra of CO inhibited α-V70I and wild-type enzyme are strikingly similar, showing only small shifts in band energies which allow better interpretation of the published wild-type spectra. The extra carbon does, however, impact and inhibit the photochemical release and migration of CO at cryogenic temperatures, resulting in novel CO-bound species. These include a product species, termed Lo-1*, which may involve CO photochemically migrating on the FeMo-cofactor.

Carbon monoxide↗

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

Here we present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.

42 ENGINEERING↗

Wood-reinforced composites by stereolithography with the stress whitening behavior

In this study, poplar wood flour at various concentrations (1–10 wt%) is incorporated into a methacrylate-based resin via solution blending to fabricate wood-reinforced composites using stereolithography apparatus (SLA) 3D printing. Differential scanning calorimetry (DSC) along with Fourier transform infrared spectroscopy (FTIR) analysis shows the presence of a small amount of residual monomer in the printed samples. For the printed composites, the glass transition temperature (T g ) from dynamic mechanical analysis (DMA) decreases as more wood flour is incorporated, which indicates an increase in free volume occupied by polymer chains. The tensile strength is improved up to 17.3% from 21.1 MPa (no wood flour) to 24.7 MPa (1.0 wt% wood flour). The highest Young’s modulus reaches 323.8 MPa (2.0 wt% wood flour), which is 1.9-fold of that of the sample without wood flour. Moreover, the composites show “stress whitening” with the addition of wood flour during the uniaxial drawing. Morphology analysis of the tested samples show that the formation of microcraze and microvoids likely causing the stress whitening. This is the first study that demonstrates wood flour can be utilized in SLA 3D printed wood plastic composites (WPC) which can reinforce the printed products with a modest loading amount.

36 MATERIALS SCIENCE↗

A Quantitative Examination of Catalyst Component Impacts on Hydrogen Adsorption and Spillover

Hydrogen spillover is a widely recognized but poorly understood surface phenomenon. We coupled volumetric chemisorption with Fourier transform infrared spectroscopy, thermogravimetric analysis, and acid–base titrations to quantify the roles of metal (Pt, Au) and support chemistry (anatase, rutile, P25 titania) on spillover. We show that metal identity has little to no impact on the amount of spillover hydrogen. Spillover pressure dependence is essentially the same on Au/TiO 2 and Pt/TiO 2 , indicating H 2 adsorption is equilibrated across both the metal and support. Conversely, spillover is highly sensitive to support surface chemistry, as rutile TiO 2 stabilizes ∼5× more surface hydrogen than anatase TiO 2 . This change is due to a combination of factors, including the rutile surface’s higher proton affinity, stabilized surface electronic states, and larger surface entropy. This work highlights the utility of Au/MO x catalysts as control materials for spillover, as they enable quantitative evaluation of H 2 adsorption on active metals and spillover onto the support.

Adsorption↗

Windowed Fourier transform and cross-correlation algorithms for molecular tagging velocimetry

In this study, simulated and experimental molecular tagging velocimetry (MTV) images have been analyzed with a technique commonly used to process grid images on surfaces, the windowed Fourier transform with local spectrum analysis (WFT-LSA). A systematic synthetic image study of the modulation transfer function (MTF) and error tendencies of the WFT-LSA was performed and compared with a PIV-style cross-correlation algorithm to see if advanced strategies such as iterative image deformation can improve analysis of gridded images with high noise levels. Testing of single-pass algorithms showed that in typical MTV images, the WFT-LSA yields significantly lower bias errors than cross-correlation (CC) at displacements greater than 1 pixel but slightly higher random error at all displacements and image conditions. Analysis of the MTF shows that CC provided better resolution of spatial fluctuations than the WFT-LSA in many combinations of grid size and interrogation window. Tests of image deformation algorithms showed that the gap in performance between CC and WFT-LSA is maintained even as both methods improve. Additionally, WFT-LSA and CC methods are applied to real MTV experiments in high-speed gas jet flows. A preliminary analysis of phosphorescence lifetime provided by acetone vapor excited at 266 nm is used for assessing the required gas speeds for making MTV application feasible. The application of WFT-LSA to real MTV images demonstrates the ability of the algorithm to handle further real-world effects that could not be considered in the synthetic image analysis, like reduced signal-to-noise ratio and non-uniform intensity of the tagging grid across the image introduced by the actual laser beam energy distribution. With experimental images, CC is more accurate with shear flows but less robust to high noise levels than WFT-LSA, as predicted by the synthetic image analysis.

42 ENGINEERING↗

Discovery and adaptation of microbes that degrade oxidized low-density polyethylene films

There is a growing interest in developing a methodology for effectively cleaving carbon–carbon (C–C) bonds in polymer backbones through bioconversion processes that utilize microorganisms and their enzymes. This upsurge of interest is driven by the goal of achieving a circular economy. Polyolefin post-consumer plastics are a substantial source of carbon, but the recycling potential is severely limited. Upcycling routes are needed for converting polyolefin post-consumer plastics into value-added products while concurrently mitigating adverse environmental effects. These materials contain carbon-based chemicals that can, in principle, serve as the feedstock for microbial metabolism. Some microbes have been reported to grow on polyolefin plastics, but the rate of biodegradation is insufficient for industrial processes. In this study, low-density polyethylene (LDPE) films were subjected to two mild ozone-based oxidation treatments, which facilitated biodegradation. The degree of oxidation was determined by Fourier transform infrared spectroscopy via analysis of the carbonyl index (1,710/1,460 cm −1 ), which ranged from 0.3 to 2.0, and also via analysis of the carboxylic acid content. Following oxidation of the films, studies were conducted to investigate the ability of a panel of polyvinyl alcohol-degrading microbes to degrade the oxidized films. A defined minimal medium was used to cultivate and assess microbial growth on the oxidized films. Following 45 days of cultivation, the most effective strains were further cultivated up to three additional generations on the oxidized film substrates to improve their ability to degrade the oxidized LDPE films. After these enrichments, we identified a strain from the third generation of Pseudomonas sp. Rh926 that exhibited significant cell growth and reduced the oxidized LDPE film mass by 25% in 30 days, demonstrating an enhanced capacity for degrading the oxidized LDPE films.

Adaptation↗

Accurate field-level weak lensing inference for precision cosmology

We present miko, a catalog-to-cosmology pipeline for general flat-sky field-level inference, which provides access to cosmological information beyond the two-point statistics. In the context of weak lensing, we identify several new field-level analysis systematics (such as aliasing, Fourier mode-coupling, and density-induced shape noise), quantify their impact on cosmological constraints, and correct the biases to a percent level. Next, we find that model misspecification can lead to both absolute bias and incorrect uncertainty quantification for the inferred cosmological parameters in realistic simulations. The Gaussian map prior infers unbiased cosmological parameters, regardless of the true data distribution, but it yields overconfident uncertainties. The log-normal map prior quantifies the uncertainties accurately, although it requires careful calibration of the shift parameters for unbiased cosmological parameters. Here, we demonstrate systematics control down to the 2% level for both models, making them suitable for ongoing weak lensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community

Nitrogen (N) fertilizers in agriculture suffer losses by volatilization of N to the air, surface runoff and leaching into the soil, resulting in low N use efficiency (NUE) (< 50%) and raising severe environmental pollutions. Controlled- release nitrogen fertilizers (CRNFs) can control the release of N nutrients to NUE in crop production. Different methods were used to develop new CRNFs. However, different CRNF technologies are still underdeveloped due to inadequate controlling on N releasing time and/or unsustainable diffusion. The study on the influences of CRNF processing parameters on microbial conditions are lacking when the CRNFs composed of various bio-ingredients such as biochar, composts, and biowaste. The complexity of processing methods, material biodegradability, and other physical properties make current CRNFs of questionable value in agricultural production. This research aims to develop a novel biochar-compost-based controlled-release urea fertilizer (BCRUF) to preserve microbial properties carried by the compost. The BCRUF was synthesized by pelletizing the 50:50 (dry, wt/wt) mixture of biochar and compost. BCRUF was loaded with urea and then spray-coated with polylactic acid (PLA). The releasing time of two types of BCRUFs, coated and uncoated with PLA, for 80% of N release in water was up to 6 h at three different temperatures (4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally smart N (ESN) fertilizer. The releasing time of coated BCRUF for 80% N release in soil was up to 192 h (8 days). Fourier-transform infrared spectroscopy (FTIR) analysis revealed that no new functional groups were found in the release solution, indicating no new chemical hazards generated. The differential scanning calorimetry (DSC) tests also verified that its thermal stability could be up to 160 °C. The microbe populations in the BCRUF pellets were reduced after the pelleting and drying processes in BCRUF fabrication, but a few bacteria can endure in the air-drying process. BCRUF pellets soaked in water for 4 days retained some bacteria. The BCRUF showed very promising characteristics to improve NUE and sustainability in agricultural production.

58 GEOSCIENCES↗

Chemical Vapor Deposition of Zirconium Compounds: A Review

Coatings of zirconium compounds are used in a wide variety of fields, yet an understanding and descriptions of deposition mechanisms are scant in the public literature. The mechanisms of deposition for metallic zirconium, ZrC, ZrN, ZrO 2 , ZrB 2 , and zirconium silicides are discussed based on the direct vapor deposition research of those compounds where possible or compared to complementary titanium systems when direct research is lacking. Both inorganic and organometallic deposition systems are discussed. As a class of compounds, an understanding of the vapor deposition mechanisms can be significantly improved by investigations on metallic zirconium deposition by zirconium halides and hydrogen and by in situ analysis techniques such as Fourier-transform infrared (FTIR) spectroscopy or x-ray photoelectron spectroscopy (XPS).

organometallic↗

Investigation of the Effect of Atmospheric Plasma Treatment in Nanofiber and Nanocomposite Membranes for Piezoelectric Applications

In this work, we report the effect of steady-state atmospheric plasma (Corona discharge) in nanofibers and nanocomposite membranes for piezoelectric applications. The investigation was performed in PVDF (Poly vinylidene fluoride) nanofibers, CNT (Carbon Nanotubes)-reinforced PVDF nanocomposites, and PAN (Poly acrylonitrile) nanofiber membranes. Steady-state plasma was generated with a high voltage power source with 1 mA discharge current output and 6 kV discharge voltage, and the gap between tip and the material was maintained to be 1 cm. For the fabrication of nanofibers and nanocomposite membranes, an electrospinning method was used. The electrospinning parameters, such as flow rate and voltage, were optimally tuned for obtaining uniform nanofibers and nanomembranes. Along with the plasma treatment, heat treatment above the glass transition temperature was also conducted on the nanofiber membranes. Using a Scanning Electron Microscope (SEM), the morphology of the nanofibers was observed. X-ray Diffraction (XRD) demonstrated the polycrystallinity of the nanofibers. Fourier Transform Infrared Spectroscopy (FTIR) analysis of the PVDF nanofibers shows a peak at 796 cm−1 representing α-phase (C-H rocking) in the control sample which is absent in the treated samples. Raman spectroscopy of PVDF nanofibers identifies a Raman shift from 873 cm−1 to 877 cm−1 (denoting β-phase) for plasma-treated samples only. Electron Paramagnetic Resonance (EPR) concludes that the intensity of the free radicals increases from 1.37 to 1.46 (a.u.) after plasma treatment. Then, sensors were fabricated from the PVDF nanofibers, MWCNT-reinforced PVDF nanofibers, and PAN nanofibers to characterize their piezoelectric properties. The impact test results showed that the atmospheric plasma and heat-treated samples had 86%, 277%, and 92% increases of the d33 value (piezoelectric coefficient) in the case of PVDF nanofibers, MWCNT-reinforced nanofibers, and PAN nanofibers, respectively. It was also observed that the capacitance of the nanofiber membranes has increased due to the plasma treatment.

Biochemistry & Molecular Biology↗

Formation of Nano- and Micro-Scale Surface Features Induced by Long-Range Femtosecond Filament Laser Ablation

In this work, we study the characteristics of femtosecond-filament-laser–matter interactions and laser-induced periodic surface structures (LIPSS) at a beam-propagation distance up to 55 m. The quantification of the periodicity of filament-induced self-organized surface structures was accomplished by SEM and AFM measurements combined with the use of discrete two-dimensional fast Fourier transform (2D-FFT) analysis, at different filament propagation distances. The results show that the size of the nano-scale surface features increased with ongoing laser filament processing and, further, periodic ripples started to form in the ablation-spot center after irradiation with five spatially overlapping pulses. The effective number of irradiating filament pulses per spot area affected the developing surface texture, with the period of the low spatial frequency LIPSS reducing notably at a high pulse number. The high regularity of the filament-induced ripples was verified by the demonstration of the angle-of-incidence-dependent diffraction of sunlight. This work underlines the potential of long-range femtosecond filamentation for energy delivery at remote distances, with suppressed diffraction and long depth focus, which can be used in biomimetic laser surface engineering and remote-sensing applications.

36 MATERIALS SCIENCE↗