Anders Kaestner

Nonequilibrium water dynamics in the rhizosphere: How mucilage affects water flow in soils

The flow of water from soil to plant roots is controlled by the properties of the narrow region of soil close to the roots, the rhizosphere. In particular, the hydraulic properties of the rhizosphere are altered by mucilage, a polymeric gel exuded by the roots. In this paper we present experimental results and a conceptual model of water flow in unsaturated soils mixed with mucilage. A central hypothesis of the model is that the different drying/wetting rate of mucilage compared to the bulk soil results in nonequilibrium relations between water content and water potential in the rhizosphere. We coupled this nonequilibrium relation with the Richards equation and obtained a constitutive equation for water flow in soil and mucilage. To test the model assumptions, we measured the water retention curve and the saturated hydraulic conductivity of sandy soil mixed with mucilage from chia seeds. Additionally, we used neutron radiography to image water content in a layer of soil mixed with mucilage during drying and wetting cycles. The radiographs demonstrated the occurrence of nonequilibrium water dynamics in the soil-mucilage mixture. The experiments were simulated by numerically solving the nonequilibrium model. Our study provides conceptual and experimental evidences that mucilage has a strong impact on soil water dynamics. During drying, mucilage maintains a greater soil water content for an extended time, while during irrigation it delays the soil rewetting. We postulate that mucilage exudation by roots attenuates plant water stress by modulating water content dynamics in the rhizosphere.

Spatiotemporal computed tomography of dynamic processes

Modern computed tomography (CT) equipment allowing fast 3-D imaging also makes it possible to monitor dynamic processes by 4-D imaging. Because the acquisition time of various 3-D-CT systems is still in the range of at least milliseconds or even hours, depending on the detector system and the source, the balance of the desired temporal and spatial resolution must be adjusted. Furthermore, motion artifacts will occur, especially at high spatial resolution and longer measuring times. We propose two approaches based on nonsequential projection angle sequences allowing a convenient postacquisition balance of temporal and spatial resolution. Both strategies are compatible with existing instruments, needing only a simple reprograming of the angle list used for projection acquisition and care with the projection order list. Both approaches will reduce the impact of artifacts due to motion. The strategies are applied and validated with cold neutron imaging of water desorption from originally saturated particles during natural air-drying experiments and with x-ray tomography of a polymer blend heated during imaging.

Gas Evolution in Operating Lithium-Ion Batteries Studied In Situ by Neutron Imaging.

Gas generation as a result of electrolyte decomposition is one of the major issues of high-performance rechargeable batteries. Here, we report the direct observation of gassing in operating lithium-ion batteries using neutron imaging. This technique can be used to obtain qualitative as well as quantitative information by applying a new analysis approach. Special emphasis is placed on high voltage LiNi0.5Mn1.5O4/graphite pouch cells. Continuous gassing due to oxidation and reduction of electrolyte solvents is observed. To separate gas evolution reactions occurring on the anode from those associated with the cathode interface and to gain more insight into the gassing behavior of LiNi0.5Mn1.5O4/graphite cells, neutron experiments were also conducted systematically on other cathode/anode combinations, including LiFePO4/graphite, LiNi0.5Mn1.5O4/Li4Ti5O12 and LiFePO4/Li4Ti5O12. In addition, the data were supported by gas pressure measurements. The results suggest that metal dissolution in the electrolyte and decomposition products resulting from the high potentials adversely affect the gas generation, particularly in the first charge cycle (i.e., during graphite solid-electrolyte interface layer formation).

Visualization of Root Water Uptake: Quantification of Deuterated Water Transport in Roots Using Neutron Radiography and Numerical Modeling

Neutron radiography traces the transport of deuterated water in soil and roots to reconstruct the water flow across the root tissue and along the xylem. Our understanding of soil and plant water relations is limited by the lack of experimental methods to measure water fluxes in soil and plants. Here, we describe a new method to noninvasively quantify water fluxes in roots. To this end, neutron radiography was used to trace the transport of deuterated water (D2O) into roots. The results showed that (1) the radial transport of D2O from soil to the roots depended similarly on diffusive and convective transport and (2) the axial transport of D2O along the root xylem was largely dominated by convection. To quantify the convective fluxes from the radiographs, we introduced a convection-diffusion model to simulate the D2O transport in roots. The model takes into account different pathways of water across the root tissue, the endodermis as a layer with distinct transport properties, and the axial transport of D2O in the xylem. The diffusion coefficients of the root tissues were inversely estimated by simulating the experiments at night under the assumption that the convective fluxes were negligible. Inverse modeling of the experiment at day gave the profile of water fluxes into the roots. For a 24-d-old lupine (Lupinus albus) grown in a soil with uniform water content, root water uptake was higher in the proximal parts of lateral roots and decreased toward the distal parts. The method allows the quantification of the root properties and the regions of root water uptake along the root systems.

Root responses to soil Ni heterogeneity in a hyperaccumulator and a non-accumulator species.

We compared root responses of the Ni-hyperaccumulator plant Berkheya coddii Rossler with the non-accumulator plant Cicer arietinum L. to Ni heterogeneity in soil. We grew plants in growth containers filled with control soil, homogeneously spiked, and heterogeneously spiked soil with Ni concentrations of 62 and 125 mg kg(-1). Neutron radiography (NR) was used to observe the root distribution and the obtained images were analysed to reveal the root volumes in the spiked and unspiked segments of the growth container. There was no significant difference in root distribution pattern of B. coddii among different concentrations of Ni. Unlike B. coddii, the roots of C. arietinum initially grew into the spiked segments. However, the later developing roots did not penetrate the spiked segment suggesting an avoidance strategy. Our results indicate that, B. coddii does not forage towards the Ni-rich patches, although presence of Ni in soil changes its root morphology.

On-line monitoring of hygroscopicity and dimensional changes of wood during thermal modification by means of neutron imaging methods

Abstract European beech (Fagus sylvatica L.) and Norway spruce [Picea abies (L.) Karst.] have been thermally modified in a combined air-steam atmosphere between 70°C and 150°C and pressures up to 4 bar, and the changes of dimensions and moisture contents (MC) of the samples were studied in-situ by means of neutron imaging (NI). This non-invasive testing method offers unique opportunities. NI is highly sensitive for hydrogen and thus well suited for monitoring the MC changes, although some metals (e.g., Al), indispensable for sample environments under high temperature and pressure, are practically transparent to neutrons. The results show that the modification induced changes of MC and dimensions both in radial and tangential direction can well be determined by NI. Dimensional changes from water saturation to oven-dry state, the sorption isotherms, and the differential swelling were observed. Additionally, the sorption behaviour at 20°C was investigated after thermal modification and colour measurements were carried out before and after the thermal treatment.

Quantitative Neutron Dark-field Imaging through Spin-Echo Interferometry.

Neutron dark-field imaging constitutes a seminal progress in the field of neutron imaging as it combines real space resolution capability with information provided by one of the most significant neutron scattering techniques, namely small angle scattering. The success of structural characterizations bridging the gap between macroscopic and microscopic features has been enabled by the introduction of grating interferometers so far. The induced interference pattern, a spatial beam modulation, allows for mapping of small-angle scattering signals and hence addressing microstructures beyond direct spatial resolution of the imaging system with high efficiency. However, to date the quantification in the small angle scattering regime is severely limited by the monochromatic approach. To overcome such drawback we here introduce an alternative and more flexible method of interferometric beam modulation utilizing a spin-echo technique. This novel method facilitates straightforward quantitative dark-field neutron imaging, i.e. the required quantitative microstructural characterization combined with real space image resolution. For the first time quantitative microstructural reciprocal space information from small angle neutron scattering becomes available together with macroscopic image information creating the potential to quantify several orders of magnitude in structure sizes simultaneously.

Quantification of the sensitivity range in neutron dark-field imaging

In neutron grating interferometry, the dark-field image visualizes the scattering properties of samples in the small-angle and ultra-small-angle scattering range. These angles correspond to correlation lengths from several hundred nanometers up to several tens of micrometers. In this article, we present an experimental study that demonstrates the potential of quantitative neutron dark-field imaging. The dark-field signal for scattering from different particle sizes and concentrations of mono-dispersive polystyrene particles in aqueous solution is compared to theoretical predictions and the good agreement between measurements and calculations underlines the quantitative nature of the measured values and reliability of the technique with neutrons.

A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction

There has been a rapid expansion of multi-modal imaging techniques in tomography. In biomedical imaging, patients are now regularly imaged using both single photon emission computed tomography (SPECT) and x-ray computed tomography (CT), or using both positron emission tomography and magnetic resonance imaging (MRI). In non-destructive testing of materials both neutron CT (NCT) and x-ray CT are widely applied to investigate the inner structure of material or track the dynamics of physical processes. The potential benefits from combining modalities has led to increased interest in iterative reconstruction algorithms that can utilize the data from more than one imaging mode simultaneously. We present a new regularization term in iterative reconstruction that enables information from one imaging modality to be used as a structural prior to improve resolution of the second modality. The regularization term is based on a modified anisotropic tensor diffusion filter, that has shape-adapted smoothing properties. By considering the underlying orientations of normal and tangential vector fields for two co-registered images, the diffusion flux is rotated and scaled adaptively to image features. The images can have different greyscale values and different spatial resolutions. The proposed approach is particularly good at isolating oriented features in images which are important for medical and materials science applications. By enhancing the edges it enables both easy identification and volume fraction measurements aiding segmentation algorithms used for quantification. The approach is tested on a standard denoising and deblurring image recovery problem, and then applied to 2D and 3D reconstruction problems; thereby highlighting the capabilities of the algorithm. Using synthetic data from SPECT co-registered with MRI, and real NCT data co-registered with x-ray CT, we show how the method can be used across a range of imaging modalities.

Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction.

X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.