Calculated Diffusion Coefficients Research Articles

Sustainable approach to dye adsorption: hemp-based activated carbon as an effective adsorbent

ABSTRACT In industry, the use of dyes that threaten human health is increasing day by day. RB 19 (Reactive Blue 19, Remazol brilliant blue R), one of the most common dyes that adversely affect natural life, is the subject of this article. In this article, the waste parts of the hemp plant (root, stem and other) were evaluated for use in scientific studies. Hemp wastes were carbonised at 500°C at a heating rate of 10°C/min for 1 hour in the N2 atmosphere. Chemical activation was then carried out with 1:4 potassium hydroxide (KOH) at 800°C under the same conditions. Activated carbon (AC) used as an adsorbent was characterised by elemental analysis (73.3% C, 0.3% H, 0.46% N, 0.02% S and 25.92% O), XRD, SEM, BET and FT-IR analysis. Activated carbon (AC) with 850 μm size, 1858.70 m2/g surface area was obtained by chemical activation of carbonised hemp waste with KOH. SEM images showed that the activated carbon is structurally similar to a honeycomb. Kinetic parameters were analysed with six different equations (Intra Particle Diffusion, Pseudo First, Pseudo Second, Elovich, Avrami, Bangham) and adsorption mechanism with eight different equations (Henry, Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Koble-Corrigan, Flory-Huggins, Harkin-Jura). According to the calculated diffusion coefficient (19.299), it is concluded that diffusion is externally controlled. The Intra-Particle Diffusion constant (75.34) indicated that the outer adsorption layer of activated carbon was thick. When the correlation coefficients of the equations were examined according to the kinetic analysis results, the highest correlation coefficient was observed in the Pseudo-First kinetic model for all temperatures. However, it was determined that it also fits the Bangham and Avrami models. Since Bangham and Avrami models have high regression coefficients (0.96–0.99), it can be said that adsorption also fits these models. Also, the negative Gibbs Free Energy values indicate that adsorption can occur spontaneously and is thermodynamically favourable.

Study of helium diffusion in yttria: A multiscale approach based on the density functional theory and kinetic Monte Carlo, with transmission electron microscopy and thermo-desorption spectroscopy

A known issue for future nuclear reactors is helium accumulation inside the steel structure materials, responsible for structural issues such as embrittlement and cracking. One possible solution is using new types of reinforced steel, such as oxide dispersion strengthened (ODS) steel. It consists of adding oxide nanoparticles to the Fe-based material, especially yttrium oxide (yttria, Y2O3), improving its properties. Therefore, one first step is understanding the helium diffusion inside this system. Very little is known about helium inside yttria, with most studies being theoretical ones. Based on this context, this work proposes a combined theoretical and experimental multiscale approach to investigate helium diffusion inside yttria.The theoretical approach starts with the density functional theory, used to model the atomic yttria cell and determine helium insertion sites. The transitions between the sites were described using the Nudged Elastic Bond (NEB) method. Kinetic Monte Carlo was then employed to obtain the interstitial diffusion coefficient expression for the first time for this material. It showed a limited diffusion at temperatures below 600 K, which may indicate a tendency for He to be blocked in the oxide. Then, the charged vacancies were explored. It showed that the vacancy further reduces helium diffusion. Finally, it was demonstrated that helium spreads across different vacancies and interstitial sites.The experimental part involved implanting helium ions at 50 keV in samples with nanometric or micrometric grains. Then, the specimens were characterised with transmission electron microscopy (TEM) and thermo-desorption spectroscopy (TDS) techniques. TEM did not evidence detectable bubbles even at the highest studied fluence (1 × 1016 cm−2). The TDS highlighted different mechanisms for helium diffusion and the grain size's role, providing a novel model for diffusion coefficient calculation based on interstitial diffusion.

Lower Band Chorus Wave Scattering Causing the Extensive Morningside Diffuse Auroral Precipitation During Active Geomagnetic Conditions: A Detailed Case Study

AbstractThe diffuse aurora is a natural phenomenon observed over the Earth's polar region. Compared with the nightside diffuse aurora, the brightness of the dayside diffuse aurora (0600–1800 magnetic local time (MLT)) is relatively weak, thus requiring more stringent observation conditions. Therefore, the current understanding of what causes the dayside diffuse aurora is still quite limited. Here, we present an intense morningside diffuse aurora (0600–1000 MLT) event observed on 1 January 2016 during the recovery phase of the substorm, using conjugate observations of wave and particle spectrum from the Radiation Belt Storm Probes and auroral emission from the Special Sensor Ultraviolet Spectrographic Imagers on the Air Force Defense Meteorological Satellite Program (DMSP/SSUSI). We perform calculations of diffusion coefficients and simulations of the electron fluxes for this event. Our results show that the chorus waves are the primary contributors to the formation of the morningside diffuse aurora, with precipitated electron energies ranging from a few keV to tens of keV. The lower band chorus shows significant pitch angle scattering efficiency for electrons with energies from 5 to 20 keV. The upper band chorus waves induce acceleration effects on 1–20 keV electrons. We suggest that the upper band chorus waves accelerate low‐energy electrons to higher energies, enabling them to engage in the scattering process of the lower band chorus waves. Our study makes a contribution to recent research on the formation mechanisms of diffuse aurora and deepens our understanding of wave‐particle interactions leading to dayside electron precipitation.

Unraveling the characteristics of adsorption and diffusion of oxygen atoms on the surface of Zr and ZrO2 crystals with point defects from molecular dynamic simulations

Unveiling the characteristics of adsorption and diffusion of oxygen atoms on the surface of zirconium alloys at microscale is significant during the initial stages of zirconium oxide layer formation in PWRs or LWRs. In this work, Adsorption and diffusion of oxygen atoms on the surface of Zr and ZrO2 crystals have been investigated using molecular dynamic simulations. A special focus of this work is on the diffusion coefficient calculation based on our developed unbiased approach. The results show that a weak effect of temperature on the adsorption rate of ZrO2. The greater influence of grain boundary orientation than the concentration of Frenkel defects on the adsorption rate of oxygen atoms. The number of oxygen atoms that diffuse deep into the studied samples after adsorption on the free surface increases with increasing temperature. Moreover, for crystals that have a certain concentration of Frenkel defects in the volume, the diffusion coefficients are greater than for defect-free crystals. The diffusion coefficient of adsorbed oxygen atoms is smaller for crystal system with grain boundary of Zr/Zr. This distinct feature may be solving the experimental puzzle of oxidation rate of zirconium alloys under neutron irradiation.

Development of diffusive gradients in thin-films technique for monitoring polycyclic aromatic hydrocarbons in coastal waters

Addressing the challenge of accurately monitoring polycyclic aromatic hydrocarbons (PAHs) in aquatic systems, this study employed diffusive gradients in thin-films (DGT) technique to achieve methods detection limits as low as 0.02 ng L−1 to 0.05 ng L−1 through in situ preconcentration and determination of time-integrated concentrations. The efficacy of the developed DGT samplers was validated under diverse environmental conditions, demonstrating independence from factors such as pH (5.03–9.01), dissolved organic matter (0–20 mg L−1), and ionic strength (0.0001–0.6 M). Notably, the introduction of a novel theoretical approach to calculate diffusion coefficients based on solvent-accessible volume tailored for PAHs significantly enhanced the method’s applicability, particularly for organic pollutants with low solubility. Field deployments in coastal zones validated the DGT method against traditional grab sampling, with findings advocating a 4 to 7-day optimal deployment duration for balancing sensitivity and mitigating lag time effects. These results provide a sophisticated, efficient solution to the persistent challenge of monitoring hydrophobic organic pollutants in aquatic environments, broadening the scope and applicability of DGT in environmental science and providing a robust tool for researchers.

Dynamics accelerate the kinetics of ion diffusion through channels: Continuous-time random walk models beyond the mean field approximation.

Ion channels are proteins that play a significant role in physiological processes, including neuronal excitability and signal transduction. However, the precise mechanisms by which these proteins facilitate ion diffusion through cell membranes are not well understood. This is because experimental techniques to characterize ion channel activity operate on a time scale too large to understand the role of the various protein conformations on diffusion. Meanwhile, computational approaches operate on a time scale too short to rationalize the observed behavior at the microscopic scale. In this paper, we present a continuous-time random walk model that aims to bridge the scales between the atomistic models of ion channels and the experimental measurement of their conductance. We show how diffusion slows down in complex systems by using 3D lattices that map out the pore geometry of two channels: Nav1.7 and gramicidin. We also introduce spatial and dynamic site disorder to account for system heterogeneity beyond the mean field approximation. Computed diffusion coefficients show that an increase in spatial disorder slows down diffusion kinetics, while dynamic disorder has the opposite effect. Our results imply that microscopic or phenomenological models based on the potential of mean force data overlook the functional importance of protein dynamics on ion diffusion through channels.

Evaluation of multi-layer urban canopy model (MLUCM) for urban microclimate predictions at different urban contexts

Modeling tools are often used to obtain a better understanding of the characteristics of urban microclimates. Among the different approaches to physics-based modeling, urban canopy models tend to be computationally faster than computational fluid dynamics (CFD) simulations. However, the evaluation of current urban canopy models for different urban characteristics is still limited, especially for wind speed. This study aims to evaluate the potential usability of the existing urban canopy model for microclimate variable prediction in different urban contexts, specifically the vertical city weather generator (VCWG) v1.4.5, which can predict microclimate variables at different vertical heights. The measurement data used in model evaluation were obtained from 248 weather stations in Seoul, Republic of Korea. The results showed that among the input parameters, a few variables had significant impact on the wind speed prediction results, namely, the turbulent coefficient during unstable conditions, the pressure gradient coefficient, and the aerodynamic roughness length. The discrepancy in wind-speed prediction tended to be lower during the summer season, with lower wind speeds at the rural weather station. Further investigations also addressed the significant parameters of wind speed prediction related to the calculation of the turbulent diffusion coefficient and pressure gradient.

Computing solubility and thermodynamic properties of H2O2 in water

Hydrogen peroxide plays a key role in many environmental and industrial chemical processes. We performed classical Molecular Dynamics and Continuous Fractional Component Monte Carlo simulations to calculate thermodynamic properties of H2O2 in aqueous solutions. The quality of the available force fields for H2O2 developed by Orabi and English (2018) [67], and by Cordeiro (2014) [69] was systematically evaluated. To assess which water force field is suitable for predicting properties of H2O2 in aqueous solutions, four widely used water force fields were used, namely the TIP3P, TIP4P/2005, TIP5P-E, and a modified TIP3P force field. While the computed densities of pure H2O2 in the temperature range of 253 - 353 K using the force field by Orabi & English are in excellent agreement with experimental results, the densities using the force field by Cordeiro are underestimated by 3%. The TIP4P/2005 force field in combination with the H2O2 force field developed by Orabi & English can predict the densities of H2O2 aqueous solution for the whole range of H2O2 mole fractions in very good agreement with experimental results. The TIP4P/2005 force field in combination with either of the H2O2 force fields can predict the viscosities of H2O2 aqueous solutions for the whole range of H2O2 mole fractions in reasonably good agreement with experimental results. The computed diffusion coefficients for H2O2 and water molecules using the TIP4P/2005 force field with either of the H2O2 force fields are almost constant for the whole range of H2O2 mole fractions. Hydrogen bond analysis showed a steady increase in the number of hydrogen bonds with the solute concentrations in H2O2 aqueous solutions for all combinations except for the Cordeiro-TIP5P-E and Orabi-TIP5P-E systems, which showed a minimum at intermediate concentrations. The Cordeiro force field for H2O2 in combination with either of the water force fields can predict the Henry coefficients of H2O2 in water in better agreement with experimental values than the force field by Orabi & English.

Study on test of free and total SO42- in cement-based materials subjected to sulfate attack by conductivity titration

It is necessary to accurately, efficiently, and economically test SO42- in cementitious materials subjected to sulfate attack for the calculation of diffusion coefficient, estimating damage degree and analysis of corrosion mechanism. In this study, the test of free and total SO42- in cementitious materials was investigated by conductivity titration. The results show that the key to test SO42- by conductivity titration is removement of the influential ions such as H+ and OH- with higher molar conductivity. In the test of free SO42-, HCl or CO2 can be used to eliminate the effect of OH- or OH- and Ca2+. In the test of total SO42-, the combination of Ag2O with Ag2CO3 or the combination of Ag2O with CO2 can be used to eliminate the effect of H+, Cl-, and Ca2+ where Ag2O and CO2 is more applicable to eliminate influential ions because CO2 is easily controlled by CO2 generator. The ultrasonic can be used to clean the AgCl attached to the surface of Ag2O to increase the hydrolysis reaction of Ag2O. To eliminate the effect of reaction between Ag+ from hydrolysis reaction of Ag2O and Cl- from the conventional titrant of BaCl2 on titration endpoint, the Ba(NO3)2 is chosen as a new titrant.

First principles calculation of composition dependence tracer and interdiffusion with phase change in γ/γ′ superalloy: A case study of Ir/Ir3Nb

In this work, the composition dependent tracer and interdiffusion coefficient with phase change in γ/γ′ Ir/Ir3Nb superalloy are studied by means of first-principles calculation together with nudged elastic band, and quasi−harmonic thermodynamics. The formulae scattered in the literature for composition dependence tracer diffusion coefficient are summarized and executed using first principles calculation. Each term in the newly derived formulae, such as energy barrier, jump frequency, defect concentration, correlation, solvent enhancement factor, effective escape frequency, etc. is meticulously calculated. We find the composition dependent tracer diffusion coefficient of Nb in L12 γ′-Ir3Nb phase is contributed mainly from the antisite bridge rather than five-frequency model proposed in FCC γ-Ir dilute solid solution. The faster diffuser is Nb in γ-Ir, while Ir in γ′-Ir3Nb. Based on the tracer diffusion coefficient, the interdiffusion coefficient is obtained using Darken-Manning equation. The composition profile and phase boundary movement of γ/γ′ Ir/Ir3Nb superalloy are evaluated through an analytical solution of Matano-Boltzmann equations. The calculated diffusion coefficients and composition profile are in good agreement with experiments. Our findings not only serve as a successful example for the quantitative calculation of composition dependent tracer diffusion coefficient, but also shed lights on the physics behind the diffusion in intermetallics.

Calculating diffusion coefficients from molecular dynamics simulations for modelling foam processes of polypropylene: Investigating different process conditions and blowing agents

The choice of blowing agent is very important in foaming processes. In an earlier work the use of molecular dynamics simulations for the estimation of the diffusion coefficients of different blowing agents was discussed at elevated temperatures above the melting point. Therein it was shown that these simulations can give valuable information on blowing agent diffusion in polypropylene. The aim of the recent work is to expand this discussion to the simulation of different influences like pressure, blowing agent mixtures and blowing agents with higher molecular weight at temperatures above the melting point of PP. First a pressure range applied on the combined system of polymer and blowing agent, reasonable for the foam processing is discussed and their influence on the diffusion coefficients for CO2 in polypropylene is evaluated via MD simulations. The next step is the investigation of the influence of mixing a blowing agent with a co-blowing agent. The last part is the presentation of diffusion coefficients for different organic solvents, namely 2-propanol, acetone, ethyl acetate and butyl acetate which could be used as potential co-blowing agents. For both, the change in pressure and the mixing of blowing agents for the systems in question only small influences on the diffusion coefficients was discovered. The results of the diffusion coefficients for the different organic solvents are compared to each other and with former results, considered different molecular structure, size and polarities and are found to be reasonable.

Quantitative MRI-based radiomics analysis identifies blood flow feature associated to overall survival for rectal cancer patients.

Radiomics objectively quantifies image information through numerical metrics known as features. In this study, we investigated the stability of magnetic resonance imaging (MRI)-based radiomics features in rectal cancer using both anatomical MRI and quantitative MRI (qMRI), when different methods to define the tumor volume were used. Second, we evaluated the prognostic value of stable features associated to 5-year progression-free survival (PFS) and overall survival (OS). On a 1.5T MRI scanner, 81 patients underwent diagnostic MRI, an extended diffusion-weighted sequence with calculation of the apparent diffusion coefficient (ADC) and a multiecho dynamic contrast sequence generating both dynamic contrast-enhanced and dynamic susceptibility contrast (DSC) MR, allowing quantification of Ktrans, blood flow (BF) and area under the DSC curve (AUC). Radiomic features were extracted from T2w images and from ADC, Ktrans, BF and AUC maps. Tumor volumes were defined with three methods; machine learning, deep learning and manual delineations. The interclass correlation coefficient (ICC) assessed the stability of features. Internal validation was performed on 1000 bootstrap resamples in terms of discrimination, calibration and decisional benefit. For each combination of image and volume definition, 94 features were extracted. Features from qMRI contained higher prognostic potential than features from anatomical MRI. When stable features (> 90% ICC) were compared with clinical parameters, qMRI features demonstrated the best prognostic potential. A feature extracted from the DSC MRI parameter BF was associated with both PFS (p = 0.004) and OS (p = 0.004). In summary, stable qMRI-based radiomics features was identified, in particular, a feature based on BF from DSC MRI was associated with both PFS and OS.

Towards hybrid quantum mechanical/molecular mechanical simulations of Li and Na intercalation in graphite - force field development and DFTB parametrisation.

In this work a previously established QM/MM simulation protocol for the treatment of solid-state interfaces was extended towards the treatment of layered bulk materials enabling for instance investigation of metal intercalation in graphitic carbon materials. In order to study the intercalation of Li in graphite, new density functional tight binding (DFTB) parameters for Li have been created. Molecular dynamics (MD) simulations at constant temperatures (273.15, 298.15 and 323.15 K) have been carried out to assess the performance of the presented DFTB MD simulation approach. The intercalation of variable lithium and sodium content was investigated via z-distribution functions and analysis of the diffusivity in the direction parallel to the graphene plane. Both the calculated diffusion coefficients and the activation energy in case of lithium are in good agreement with experimental data. The comparison of the QM/MM MD simulation results provide detailed insights into the structural and dynamical properties of intercalated metal ions.

UNDERSTANDING THE ROLE OF DIFFUSION IN THE SEPARATION OF RARE EARTH ELEMENTS IN WATER-n-HEXANE SYSTEMS: A MOLECULAR DYNAMICS SIMULATION STUDY

Liquid-liquid extraction is one of the methods for separating rare earth elements (REE) in the presence of an extractant. The separation of REE ions, complex with an extractant, involves interfacial migrations that are influenced by the diffusion of the respective ions. Therefore, we performed molecular dynamics simulations on REE ions (La3+, Sm3+, Eu3+, Gd3+, and Tb3+) in a water-n-hexane system to determine if each ion exhibited a distinct diffusion coefficient. By employing molecular dynamics simulations, we calculated diffusion coefficients for these ions based on the Einstein relation. The diffusion coefficients for La3+, Sm3+, Eu3+, Gd3+, and Tb3+ were found to be 4.21×10–6, and 3.96×10–6, 4.57×10–6, 4.17×10–6, and 5.19×10–6 cm2/s, respectively. However, statistical analysis via the Kruskal-Wallis test revealed no significant variance in the diffusion coefficients (p-value greater than 0.05), indicating that diffusion is not a rate-limiting factor in REE separation. The findings suggest that effective mixing during extraction can eliminate the role of diffusion as a differentiating factor in REE separation. Overall, this study offers critical insights into optimizing REE extraction processes

Comparison of the Interaction and Structure of Lignin in Pure Systems and in Asphalt Media by Molecular Dynamics Simulations.

Lignin is a class of organic aromatic polymers contributing to the rigidity and strength of plants and has been proposed as a modifier to improve asphalt performance on road pavement. However, contradicting experimental results on the lignin miscibility in asphalt were found from different studies, and lignin has been found to self-assemble in different solutions. Thus, investigating the interaction and microstructure of lignin in asphalt media in molecular detail is necessary. Molecular dynamics (MD) simulations using both the LAMMPS program with the OPLS-aa force field and the NAMD program with the CHARMM force field have been conducted on pure lignin (including lignin monomer, dimer, and polymer with 17 and 31 units) and their mixtures with model asphalt molecules at different temperatures. Consistent results were observed from both programs and force fields in terms of density, hydrogen bonds, diffusion coefficient, radius of gyration, and radial distribution function. Glass transition was observed in the pure lignin systems based on density and diffusion coefficient calculations at different temperatures. Lignin can form intramolecular hydrogen bonds and intermolecular hydrogen bonds with other lignin and 1,7-dimethylnapthalene in the asphalt mixture, which has dependence on temperature and lignin chain length. Correlating the lignin size and chain length using the power-law relationship showed that lignin polymers in pure systems are in quasi-relaxed structures at different temperatures; lignin molecules stay in quasi-relaxed structures in asphalt mixtures at high temperatures but in collapsed structures at low temperatures. Implementing lignin monomer, dimer, and polymer into the model asphalt mixture can improve its density. Although lignin in different chain lengths aggregates in asphalt, lignin can modify the packing between different components in asphalt media at different temperatures. The work suggests that temperature can significantly influence the miscibility of lignin polymer in asphalt and that lignin can function as both a modifier and a resin in asphalt.

Deep learning-based magnetic resonance imaging reconstruction for improving the image quality of reduced-field-of-view diffusion-weighted imaging of the pancreas.

It has been reported that deep learning-based reconstruction (DLR) can reduce image noise and artifacts, thereby improving the signal-to-noise ratio and image sharpness. However, no previous studies have evaluated the efficacy of DLR in improving image quality in reduced-field-of-view (reduced-FOV) diffusion-weighted imaging (DWI) [field-of-view optimized and constrained undistorted single-shot (FOCUS)] of the pancreas. We hypothesized that a combination of these techniques would improve DWI image quality without prolonging the scan time but would influence the apparent diffusion coefficient calculation. To evaluate the efficacy of DLR for image quality improvement of FOCUS of the pancreas. This was a retrospective study evaluated 37 patients with pancreatic cystic lesions who underwent magnetic resonance imaging between August 2021 and October 2021. We evaluated three types of FOCUS examinations: FOCUS with DLR (FOCUS-DLR+), FOCUS without DLR (FOCUS-DLR-), and conventional FOCUS (FOCUS-conv). The three types of FOCUS and their apparent diffusion coefficient (ADC) maps were compared qualitatively and quantitatively. FOCUS-DLR+ (3.62, average score of two radiologists) showed significantly better qualitative scores for image noise than FOCUS-DLR- (2.62) and FOCUS-conv (2.88) (P < 0.05). Furthermore, FOCUS-DLR+ showed the highest contrast ratio (CR) between the pancreatic parenchyma and adjacent fat tissue for b-values of 0 and 600 s/mm2 (0.72 ± 0.08 and 0.68 ± 0.08) and FOCUS-DLR- showed the highest CR between cystic lesions and the pancreatic parenchyma for the b-values of 0 and 600 s/mm2 (0.62 ± 0.21 and 0.62 ± 0.21) (P < 0.05), respectively. FOCUS-DLR+ provided significantly higher ADCs of the pancreas and lesion (1.44 ± 0.24 and 3.00 ± 0.66) compared to FOCUS-DLR- (1.39 ± 0.22 and 2.86 ± 0.61) and significantly lower ADCs compared to FOCUS-conv (1.84 ± 0.45 and 3.32 ± 0.70) (P < 0.05), respectively. This study evaluated the efficacy of DLR for image quality improvement in reduced-FOV DWI of the pancreas. DLR can significantly denoise images without prolonging the scan time or decreasing the spatial resolution. The denoising level of DWI can be controlled to make the images appear more natural to the human eye. However, this study revealed that DLR did not ameliorate pancreatic distortion. Additionally, physicians should pay attention to the interpretation of ADCs after DLR application because ADCs are significantly changed by DLR.

Nanosecond Laser Irradiation for Interface Bonding Characterization

Hydrophilic direct bonding is nowadays widely used in microelectronics for SOI substrate fabrication and 3D integration. Trapped water at the bonding interface plays a key role in the adhesion and adherence mechanisms [1]. Previous studies also reported that water could penetrate the bonding interface. This may modify the radial inhomogeneity of water [2]. However, this reported technique requires specific Silicon-to-Silicon bonding, lacks precision and needs additional characterizations (XRR, FTIR) to quantify the amount of trapped water at the bonding interface. In this work, we present an original methodology that can both accurately characterize and quantify water imbibition.Pulsed nanosecond laser annealing enables to reach extremely high temperatures, above the silicon melting point (1414°C), for very short durations (from a few tens of ns to a few hundred ns). These annealing conditions result in silicon surface melt. The beginning of melting is heterogeneous and leads to a particular surface topology with the formation of molten islands during laser annealing [3]. Recrystallization of these molten islands results in a localized increase of roughness (see fig. 1a). This roughness can exceed the direct bonding critical roughness. Non-bonded areas, i.e. bonding defects, can then be intentionally and precisely placed at the direct bonding interface.In a first step, bonding defects were thus formed along a wafer diameter with a 2 mm pitch. Then, using high-resolution acoustic microscopy, the bonding defects radii evolution was measured over time after direct bonding and without annealing (see fig. 1b). A progressive growth of defect radii was evidenced when getting closer and closer to the wafer edge. An additional water amount coming from the clean room atmosphere resulted in silicon oxidation at room temperature and di-hydrogen generation. Di-hydrogen was then trapped by bonding defects. In other words, bonding defects acted as humidity sensors. We could then record the penetration length and plot it as a function of the square root of time (fig. 1c). The penetration rate is the equivalent of a diffusion coefficient that could be calculated for both Silicon-to-Silicon and Silicon-to-Oxide bonding. We noted a very good agreement with Tedjini’s results for Silicon-to-Silicon bonding [2]. Meanwhile the calculated diffusion coefficient for Silicon-to-Oxide bonding was surprisingly about twice higher.Second, a bonding defect network with the same 2 mm pitch in both X and Y direction was created. After direct bonding, various duration 500°C temperature anneals were performed. The defects radii evolution was once again measured. As it increased over time, we could write the Griffith equilibrium between elastic (due to defect pressure) and surface (γ) energies. Describing defects as circular blisters, the amount of di-hydrogen trapped molecules could then be calculated. Plotting this number of H2 molecules, N, as a function of the annealing time (fig. 1d), we observe that a plateau was reached, meaning that all the di-hydrogen produced in the network was collected in the bonding defects. The water amount responsible for this di-hydrogen generation could then be evaluated and compared to data from other measurements. REFERENCES [1] F. Fournel, C. Martin-Cocher, D. Radisson, V. Larrey, E. Beche, C. Morales, P. A. Delean, F. Rieutord, and H. Moriceau, “Water Stress Corrosion in Bonded Structures”, ECS Journal of Solid State Science and Technology, 4 (5) P124-P130 (2015)[2] Tedjini M, Fournel F, Moriceau H, Larrey V, Landru D, Kononchuk O, et al. Interface water diffusion in silicon direct bonding. Appl Phys Lett. 12 sept 2016;109(11):111603.[3] L. Dagault, S. Kerdilès, P. Acosta Alba, J.-M. Hartmann, J.-P. Barnes, P. Gergaud, E. Scheid, and F. Cristiano, Investigation of Recrystallization and Stress Relaxation in Nanosecond Laser Annealed Si1−xGex/Si Epilayers, Appl. Surf. Sci. 527, 146752 (2020). Figure 1

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes.

We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion in crystalline inorganic solids, predicting Li-ion diffusion coefficients within 1 order of magnitude of molecular dynamics simulations at the same level of theory while being several orders of magnitude faster. The speed and transferability of our workflow make it well-suited for extensive and efficient screening studies of crystalline solid-state ion conductor candidates and promise to serve as a platform for diffusion prediction even up to the density functional level of theory.

Multiparametric bone MRI targeting aides lesion selection for CT-guided sclerotic bone biopsies in metastatic castrate resistant prostate cancer

BackgroundBone biopsies in metastatic castrate-resistant prostate cancer (mCRPC) patients can be challenging. This study’s objective was to prospectively validate a multiparametric bone MRI (mpBMRI) algorithm to facilitate target lesion selection in mCRPC patients with sclerotic bone disease for subsequent CT-guided bone biopsies.Methods20 CT-guided bone biopsies were prospectively performed between 02/2021 and 11/2021 in 17 mCRPC patients with only sclerotic bone disease. Biopsy targets were selected based on MRI, including diffusion-weighted (DWI) and T1-weighted VIBE Dixon MR images, allowing for calculation of the apparent diffusion coefficient (ADC) and the relative fat-fraction (rFF), respectively. Bone marrow with high DWI signal, ADC < 1100 µm2/s and rFF < 20% was the preferred biopsy target. Tumor content and NGS-feasibility was assessed by a pathologist. Prognostic routine laboratory blood parameters, target lesion size, biopsy tract length, visual CT density, means of HU, ADC and rFF were compared between successful and unsuccessful biopsies (p < 0.05 = significant).ResultsOverall, 17/20 (85%) biopsies were tumor-positive and next-generation genomic sequencing (NGS) was feasible in 13/18 (72%) evaluated samples. Neither laboratory parameters, diameter, tract length nor visual CT density grading showed significant differences between a positive versus negative or NGS feasible versus non-feasible biopsy results (each p > 0.137). Lesion mean HU was 387 ± 187 HU in NGS feasible and 493 ± 218 HU in non-feasible biopsies (p = 0.521). For targets fulfilling all MRI selection algorithm criteria, 13/14 (93%) biopsies were tumor-positive and 10/12 (83%) provided NGS adequate tissue.ConclusionsMultiparametric bone MRI can facilitate target lesion selection for subsequent CT-guided bone biopsy in mCPRC patients with sclerotic metastases.Trial registrationCommittee for Clinical Research of the Royal Marsden Hospital registration number SE1220.

Pressure-dependent characteristics of the diffusion coefficient during the gas desorption process in coal cuttings: Numerical modelling and analysis

Determining the diffusion coefficient is crucial in coalbed methane development. Existing models have limitations, as they often apply only to spherical systems, cannot describe nonlinear adsorption, and do not quantify the impact of gas pressure on diffusion coefficients. Additionally, traditional trial methods struggle to accurately compute diffusion coefficients in numerical solutions. To address these challenges, our study builds two unipore diffusion models (EPDDM and PPDDM) by introducing exponential and power pressure-dependent diffusion coefficients, considering three-dimensional coordinates and Langmuir adsorption. And then proposes a diffusion coefficient determination method using a particle swarm optimization algorithm. Through desorption experiments, numerical modelling, and model comparisons, we analyze the evolution law of diffusion coefficient, gas pressure, and desorption volume during the desorption process. Our results show that the proposed models quantitatively depict the positive correlation between diffusion coefficient and gas pressure. Furthermore, they accurately reflect changes in desorption volume. During early-stage desorption, the diffusion coefficient of EPDDM is 1.63–1.85 times greater than that of PPDDM, while their desorption volumes are similar. This observation motivates the proposal of a more versatile Logistic pressure-dependent diffusivity model, aiming to unify the above two models. These achievements are anticipated to serve as a foundational framework for exploring the mechanisms governing gas diffusion.