Non-ambient Conditions Research Articles

Kinetics of Temperature-Modulated Water Splitting: Enhancing Efficiency for Hydrogen Generation Using Cu-Doped Nico-Layered Double Hydroxides

Ensuring the efficiency of an electrocatalyst under non-ambient conditions especially at high temperature, is crucial for their facile integration in industrial electrolysers. Varying temperatures governs the thermodynamic and kinetics aspects of water electrolysis by altering reactions rates, conductivity, and adsorption-desorption mechanism. This directly impacts the extent of hydrogen/oxygen evolution reactions (HER/OER). This study demonstrates that the Cu-doped trimetallic NiCoLDHs nanocatalysts shows significant improvement in overpotential ~20% and 10% for OER, and HER, respectively, compared to room temperature electrolysis. Further, to evaluate the effect of elevated temperatures on the kinetics of HER/OER, activation energies were calculated. For HER, the activation energy was found to be 14.4 kJ mol-1, while for OER, it was ~23 kJ mol-1. Density functional theory calculations were carried out to determine the electronic and band structure of the electrocatalysts. The results explains the reasons of increase in their electronic conductivity and electrocatalytic activity for HER/OER at elevated temperatures.

Deep Learning Based 3D Resolution Recovery for Breakthrough Imaging of Electrochemical Energy Devices

Many energy materials can only be understood within the context of the (often sealed) devices they make up. Batteries and fuel cells contain intricate mixtures of materials with features and arrangements that span across many orders of magnitude in size and operate under non-ambient conditions. In these devices, the microstructures of the constituent materials and how they are arranged with respect to each other is directly linked to the device performance and degradation behaviors. Complicating matters, opening the devices for inspection and analysis can irreversibly alter the very microstructures in question and can pose safety hazards to researchers if not done correctly. Furthermore, critical material and device properties such as tortuosity or ion transport pathways can only be accurately quantified in 3D. As such, observing microstructures and their evolution in 3D and in their native state is essential for developing a robust understanding of how to engineer new battery and fuel cell materials and architectures with improved performance.X-ray microscopy (XRM) provides a unique method for observing these microstructures in 3D at high resolutions without needing to open them. However, microscopy techniques like XRM make tradeoffs between FOV and resolution, which can pose challenges for strongly multiscale systems like batteries and fuel cells. For example, if images are acquired at high enough resolution to observe critical features like electrode particle sizes in lithium-ion batteries or gas diffusion layer fiber weaves, catalyst distributions, and microporous layer cracks in polymer electrolyte fuel cells, the field of view of that image is restricted to a small local region of the sample. This means that broader defect distributions or larger scale inhomogeneities will be missed. Additionally, for quantitative analysis applications, this means that statistical relevance will be sacrificed because of the limited analysis volume at the appropriate resolution. And for computational modelling efforts, device level phenomena will not be captured well due to the restricted field of view.Advances in modern AI-based resolution recovery methods combined with the non-destructive multiscale imaging capabilities of X-ray microscopy have allowed researchers to overcome this dependency between resolution and field of view to produce 3D images with both high resolution and large field of view. We present here examples of applying these methods to applications in lithium-ion battery and polymer electrolyte fuel cell research [1].[1] Wang, Y.D., Meyer, Q., Tang, K. et al. Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning. Nat Commun 14, 745 (2023).

AI-Powered 3D Image Reconstruction for Analyzing Lithium Ion Battery Microstructures at the Nanoscale

A clean energy future will rely heavily on lithium-ion batteries to shift away from carbon-based energy sources. These devices are closed off from the outside world and operate under highly non-ambient conditions (e.g., liquid electrolytes, air-free environments). Their performance is largely driven by the 3D microstructures of the internal components and their evolutions. For example, breached layers in batteries due to lithium dendrite growth can lead to catastrophic failures and safety concerns. As such, imaging the internal microstructures and processes is important for observing and measuring device construction details and understanding how defects are distributed and change performance during operation. In particular, 3D imaging allows for analysis of features and parameters that can only be fully understood in 3D, like porosity and tortuosity, and can also provide realistic microstructural input for 3D modelling and simulation approaches.Within this scope, X-ray microscopy provides a unique method to image electrochemical devices because of the non-destructive nature of the technique. Modern x-ray microscopes enable 3D imaging even at the nanoscale, bringing capabilities once reserved for the synchrotron into the laboratory. Advances in tomographic image reconstruction have allowed researchers to increasingly maximize the impact of x-ray microscopy data through higher image quality and enabling faster data acquisition schemes. Recently, artificial intelligence (AI) has been incorporated into these algorithms, dramatically increasing the performance and capability of the technique. Here, we apply multiple novel reconstruction technologies that leverage AI to dramatically improve the performance of laboratory-based nanoscale x-ray microscopes, showing examples of improvements in imaging lithium-ion battery electrode materials.We show how AI-powered tomographic reconstruction can reveal new levels of detail in lithium-ion battery materials and enable up to 10 times faster data collection across the micrometer and nanometer length-scales. These capabilities shift the paradigm in volume analysis for electrochemical devices and give researchers unprecedented insight into the detailed microstructures that drive device performance, enabling new levels of understanding and helping to power the drive to a clean energy future.

High-throughput and high-resolution powder X-ray diffractometer consisting of six sets of 2D CdTe detectors with variable sample-to-detector distance and innovative automation system.

The demand for powder X-ray diffraction analysis continues to increase in a variety of scientific fields, as the excellent beam quality of high-brightness synchrotron light sources enables the acquisition of high-quality measurement data with high intensity and angular resolution. Synchrotron powder diffraction has enabled the rapid measurement of many samples and various in situ/operando experiments in nonambient sample environments. To meet the demands for even higher throughput measurements using high-energy X-rays at SPring-8, a high-throughput and high-resolution powder diffraction system has been developed. This system is combined with six sets of two-dimensional (2D) CdTe detectors for high-energy X-rays, and various automation systems, including a system for automatic switching among large sample environmental equipment, have been developed in the third experimental hutch of the insertion device beamline BL13XU at SPring-8. In this diffractometer system, high-brilliance and high-energy X-rays ranging from 16 to 72 keV are available. The powder diffraction data measured under ambient and various nonambient conditions can be analysed using Rietveld refinement and the pair distribution function. Using the 2D CdTe detectors with variable sample-to-detector distance, three types of scan modes have been established: standard, single-step and high-resolution. A major feature is the ability to measure a whole powder pattern with millisecond resolution. Equally important, this system can measure powder diffraction data with high Q exceeding 30 Å-1 within several tens of seconds. This capability is expected to contribute significantly to new research avenues using machine learning and artificial intelligence by utilizing the large amount of data obtained from high-throughput measurements.

Electrical and optical properties of environmental friendly Li(1‐x)Smx/3NbO3 ceramics for high‐temperature energy storage applications

AbstractThis research article delves into the synthesis and characterization of Li(1‐x)Sm(x/3)NbO3 ceramic, employing a high‐energy ball milling process. The investigation explores the incorporation of Sm3+ at the Li+1 site across a range of compositions (x = 0, 0.01, 0.02, 0.03, 0.04, 0.05). Structural analysis, using x‐ray diffraction (XRD) and Rietveld structural refinement, establishes that within the investigated composition range, no significant changes in the crystal structure are evident. The x‐ray photoelectron spectroscopy revealed the presence of oxygen vacancies as well as the stable oxidation state of different elements like O2−, Nb5+, Sm3+, and Li1+. At sintering temperature 1050°C, the average grain sizes vary approximately from 1.5 to 3.8 μm for different compositions with regular grain morphology. The UV‐Vis analysis reveals a noteworthy reduction in the band gap to 3.09 eV for the x = 0.01 composition. Photoluminescence studies exhibit distinct green, orange, and red bands, with the highest intensity observed for x = 0.01, showcasing promising optical properties. The dielectric permittivity of Sm‐substituted compositions surpasses the response of pure LiNbO3, demonstrating an increasing trend with temperature in the frequency range 100 Hz‐1 MHz intriguingly, no Curie temperature is observed up to 500°C for any composition. The polarization vs electric field hysteresis loop response highlights better polarization characteristics at the room temperature and maximum polarization is 0.66 μC/cm2 for the composition x = 0.05. The energy storage response of the developed compositions is investigated, which reveals a maximum efficiency of 46.64% for x = 0.04 in Li(1‐x)Sm(x/3)NbO3. The tunable optical properties, enhanced dielectric response, and notable energy efficiency of these high TC ceramics suggest their utility across diverse applications. These findings not only contribute to the understanding of functional ceramic materials but also pave the way for their optimized utilization in advanced technological applications, particularly in energy storage devices under nonambient conditions at high temperatures.

Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality.

The isothermal compressibility (i.e., related to the asymptotic number variance) of equilibrium liquid water as a function of temperature is minimal under near-ambient conditions. This anomalous non-monotonic temperature dependence is due to a balance between thermal fluctuations and the formation of tetrahedral hydrogen-bond networks. Since tetrahedrality is a many-body property, it will also influence the higher-order moments of density fluctuations, including the skewness and kurtosis. To gain a more complete picture, we examine these higher-order moments that encapsulate many-body correlations using a recently developed, advanced platform for local density fluctuations. We study an extensive set of simulated phases of water across a range of temperatures (80-1600K) with various degrees of tetrahedrality, including ice phases, equilibrium liquid water, supercritical water, and disordered nonequilibrium quenches. We find clear signatures of tetrahedrality in the higher-order moments, including the skewness and excess kurtosis, which scale for all cases with the degree of tetrahedrality. More importantly, this scaling behavior leads to non-monotonic temperature dependencies in the higher-order moments for both equilibrium and non-equilibrium phases. Specifically, under near-ambient conditions, the higher-order moments vanish most rapidly for large length scales, and the distribution quickly converges to a Gaussian in our metric. However, under non-ambient conditions, higher-order moments vanish more slowly and hence become more relevant, especially for improving information-theoretic approximations of hydrophobic solubility. The temperature non-monotonicity that we observe in the full distribution across length scales could shed light on water's nested anomalies, i.e., reveal new links between structural, dynamic, and thermodynamic anomalies.

High temperature structure and vibrational properties of ScXO4 (X= V5+ and P5+): A comparative study

ScVO4 and ScPO4 represent the zircon (xenotime) type structures with smallest trivalent cations, and that enable them to host both transition metal and rare-earth ions for applied optical materials. Thus, their crystal chemistry and thermophysical properties becomes relevance for their application in non-ambient conditions. In this report, high temperature crystal chemistry and vibrational properties of ScVO4 and ScPO4, as observed from in situ high temperature powder XRD and Raman spectroscopic studies, are reported. The comparative analyses of the results indicate that, though both are isostructural, they show drastically different thermal expansion behavior. In case of ScVO4, the c-axis shows significantly larger expansion compared to a-axis, while in ScPO4 the thermal expansion along and a and c-axes are more or less similar. At ambient condition, the thermal expansion anisotropy in ScPO4 and ScVO4 are 1.02 and 3.97, respectively. Additionally, ScPO4 shows relatively lower coefficient of volume thermal expansion compared to ScVO4, (αv = 23.64 × 10−6 K−1 for ScPO4 and 26.09 × 10−6 K−1 for ScVO4), and is contributed by the expansion of ScO8 units in their structures. The thermal expansion coefficients of ScO8 unit in ScPO4 and ScVO4 are 36.3 × 10−6 K−1 and 39.1 × 10−6 K−1, respectively. Temperature evolution of Raman modes indicates weakening of all the modes, except a symmetric stretching mode, with increasing temperature. The anharmonic analyses of the Raman modes indicate that implicit contributions in ScVO4 and ScPO4 are appreciably higher than the explicit contributions, and hence the changes in mode wavenumbers with volume play dominating role in governing their thermal expansion behaviors. Further, it is concluded that ScPO4 is characterized by more or less like rigid unit cell compared to ScVO4.

Hydrogen-bond transformations of confined water and abnormal mechanical responses of hydrated AlPO4-11 framework under in situ high pressure

The behaviors of water under non-ambient conditions, especially in confinement environment, have long been of special interest due to the important roles in biological and geological processes. Here, we have performed an infrared spectroscopic investigation on the pressure-induced hydrogen-bond transformation of water in one-dimensional, elliptical channels of AlPO4-11. Upon compression, the hydrogen-bonds of confined water strengthen and water molecules transform from tetrahedral coordination configuration to low and intermediate configurations, which may be a high-density disordered state. This transformation is distinct from the commonly accepted liquid–solid and solid–solid phase transition in bulk water. Stronger hydrogen-bonds are formed and a further transformation of hydrogen-bonded water takes place in the hydrostatic environment of Ar than the case without pressure transmitting medium (PTM). In addition, the mechanical compressible behaviors and framework deformation of the host matrix are also discussed. X-ray diffraction study shows that the hydrated AlPO4-11 exhibits an unexpected high compressibility in Ar. Its bulk modulus before framework collapse is 14.1 GPa, 4 ∼ 5 times smaller than that in silicone. The anisotropic axial compressibilities of AlPO4-11 demonstrate that the ellipticity of the channel cross-section increases in silicone oil while it decreases in Ar because the relatively contractive behavior along minor axis direction is slowed down. Such pressure-induced responses are ascribed to the complex Ar-H2O-framework interaction after Ar penetration. This study offers us a new knowledge of crystal-fluid interaction in determining the mechanical behaviors of open-framework materials under high pressure and provides implications for the water evolution and circulation in water-carrying natural zeolites under extreme geological conditions in nature.

3D atomic structure from a single X-ray free electron laser pulse

X-ray Free Electron Lasers (XFEL) are cutting-edge pulsed x-ray sources, whose extraordinary pulse parameters promise to unlock unique applications. Several new methods have been developed at XFELs; however, no methods are known, which allow ab initio atomic level structure determination using only a single XFEL pulse. Here, we present experimental results, demonstrating the determination of the 3D atomic structure from data obtained during a single 25 fs XFEL pulse. Parallel measurement of hundreds of Bragg reflections was done by collecting Kossel line patterns of GaAs and GaP. To the best of our knowledge with these measurements, we reached the ultimate temporal limit of the x-ray structure solution possible today. These measurements open the way for obtaining crystalline structures during non-repeatable fast processes, such as structural transformations. For example, the atomic structure of matter at extremely non-ambient conditions or transient structures formed in irreversible physical, chemical, or biological processes may be captured in a single shot measurement during the transformation. It would also facilitate time resolved pump-probe structural studies making them significantly shorter than traditional serial crystallography.

In-situ microscopy methods for imaging high-temperature microstructural processes – Exploring the differences and gaining new potentials

In-situ high-temperature microscopy techniques provide crucial insights into materials under non-ambient conditions. This study compares confocal laser scanning and scanning electron microscopy for material characterization at elevated temperatures. Thereby, investigations are made regarding their imaging capabilities, limitations, and the general information obtained. Two alloys, Cu-20 m.% Sn and W-10 m.% Re, are used as case studies to demonstrate the applicability of the techniques. By studying phenomena such as grain growth, phase transformations, and thermal crack, we gain important insights to understand mechanical properties and thermal behavior better. This comprehensive analysis aids in selecting the most appropriate microscopy technique based on the research objectives. Overall, this study helps advance high-temperature materials science and promotes progress in several areas requiring accurate materials characterization under high thermal conditions.

Predicting the lifetime of CPVC under increasing temperature and crosshead speed

CPVC is an increasingly popular material for plumbing pipes and other applications that require strong and temperature-resistant material. This resin is created using a chlorination process, giving it Chlorine levels that range from 63 to 69% and thus a unique set of characteristics that make it ideal for certain applications. CPVC's combination of corrosion-resistance and low installation costs make it a great substitute for copper in environments with non-ambient conditions such as higher temperatures. This makes it an economic choice for many projects that require smaller budgets. With a variety of applications, CPVC provides a great alternative requiring strong and durable material. The aim of this paper is to characterize the mechanical characteristics of chlorinated PVC (CPVC). Tensile tests were carried on the compounds at different temperatures ranging from -20 to 90°C and crosshead speeds from 5 to 500 mm/min. The results were analyzed to determine how crosshead speed and temperature affected on the mechanical characteristics of CPVC specimens. Two damage models are then developed, one model obtained through by adapting the unified theory version and the other quasi-experimental static model based on ultimate stress. These models allow us to evaluate the damage evolution of CPVC samples and to determine the safety and maintenance intervals of this material.

Thermal Degradation of Polycrystalline Ni-Rich Cathodes, New Insights from Total Scattering and Machine-Learning Assisted Tomography

Alkali metal-based batteries (e.g., lithium batteries) are considered the most effective energy storage candidate for portable electronics, power grids, and electric vehicles due to their considerable energy density, power density, cycle life, safety, and competitive prices. The Ni-rich Co-less ternary LiNi x Mn y Co1-x-y O2 (NMC) (Ni>80%) is one of the candidate materials due to its high discharge capacity (>200 mAh g-1) and high energy density (>750 Wh kg-1). However, the thermal stability of charged Ni-rich NMCs is inferior, following a general negative correlation between Ni content and stability. Such severer degradation in Ni-rich NMCs might lead to dysfunctionality, thermal runaway, and eventually catastrophic failure and explosion of batteries, raising enormous safety concerns. Therefore, it is critical to understand the thermal behavior of charged Ni-rich NMC cathode from different perspectives in order to conduct material design for better thermal stability.After literature survey of typical and widely used probes by this community (e.g., diffraction, spectroscopy, imaging), we found these approaches subject to compromise to some degree in the experimental design, resulting in an inadequate description of the thermal degradation mechanism. Here we offer two novel approaches, neutron total scattering and energy-resolved 3D nano-tomography, to probe the reaction and evolution of the charged NMCs under non-ambient conditions in real-time. Such in situ measurements were only accomplished by deliberate experimental design at beamlines and deep integrations of neutron or synchrotron facilities with battery science. In situ heating neutron scattering captures the transition of crystal structure in reciprocal space (by Rietveld refinements), as well as of the local atomic framework in real space (by pair distribution function analysis). Moreover, machine learning algorithms were applied to the 3D nano-tomography datasets to reveal the detailed microstructural and oxidation state progression inside the charged particles. Thereafter, we discussed the key factors which have previously been overlooked by the community and offer constructive suggestions on particle design for thermally stable cathodes from our unique perspective.The work was supported by the National Science Foundation under Grant no. DMR-1832613 (F.L.). The machine-learning assisted tomography analysis was partially supported from NASA under 80NSSC21M0333 and NSF under NSF-2119688 (X.-D.Z)

Going beyond the conventional in operando XRD to understand battery cell performance under non-ambient conditions

Going beyond the conventional <i>in operando</i> XRD to understand battery cell performance under non-ambient conditions

Synthesis of Fe and La doped SnO2 system in ambient and non-ambient conditions: Effect on lattice structure, chemical state, optical and dielectric properties

The effect of Fe and La doping in SnO2 structure have been investigated by synthesizing the material using mechanical alloying and post-heat treatment under ambient and non-ambient atmospheres. The material has been characterized by employing Powder X-ray Diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), UV–Visible spectroscopy, and Broadband dielectric spectroscopy. The material has formed bi-phased lattice structure, consisting of tetragonal phased SnO2 structure (space group P 42/m n m) and a secondary phase, for the samples that were mechanically alloyed in air and heat treated in different atmospheres. The α-Fe2O3 (space group R- 3 c) has been identified as the secondary phase for Fe doped SnO2 system and small amount (5%.) of La2O3 (cubic structure with space group I a-3) has been identified as the secondary phase for mechanically alloyed (in air) La doped SnO2 system. The N2 atmosphere played a crucial role in forming the single-phased SnO2 structure in mechanically as-alloyed samples and also for determination of the phase fraction in bi-phased lattice structure during the incorporation of Fe and La in SnO2 system. XPS confirmed the multiple charge states for Fe (Fe3+, Fe2+, Fe0) and Sn (Sn4+, Sn2+) ions. The bandgap energy in the Fe and La-doped SnO2 system has reduced in the range of 2.18 eV–2.37 eV and 2.81 eV–2.90 eV, respectively in comparison to band gap ∼ 3.6-3.8 eV for SnO2 system. The band gap reduction has been controlled mainly by the SnO fraction in SnO2 structure. The electrical conductivity of Fe and La-doped samples has been found in the order of ∼ 10−7 S/cm to 10−9 S/cm. The Fe-doped samples have shown higher electrical conductivity than the La-doped samples. The nitrogen environment during mechanical alloying or heat-treatment played a significant role in determining high electrical conductivity and dielectric constant, and low dielectric loss constant of the samples.

High-Throughput Condensed-Phase Hybrid Density Functional Theory for Large-Scale Finite-Gap Systems: The SeA Approach.

High-throughput electronic structure calculations (often performed using density functional theory (DFT)) play a central role in screening existing and novel materials, sampling potential energy surfaces, and generating data for machine learning applications. By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal DFT and furnish a more accurate description of the underlying electronic structure, albeit at a computational cost that often prohibits such high-throughput applications. To address this challenge, we have constructed a robust, accurate, and computationally efficient framework for high-throughput condensed-phase hybrid DFT and implemented this approach in the PWSCF module of Quantum ESPRESSO (QE). The resulting SeA approach (SeA = SCDM + exx + ACE) combines and seamlessly integrates: (i) the selected columns of the density matrix method (SCDM, a robust noniterative orbital localization scheme that sidesteps system-dependent optimization protocols), (ii) a recently extended version of exx (a black-box linear-scaling EXX algorithm that exploits sparsity between localized orbitals in real space when evaluating the action of the standard/full-rank operator), and (iii) adaptively compressed exchange (ACE, a low-rank approximation). In doing so, SeA harnesses three levels of computational savings: pair selection and domain truncation from SCDM + exx (which only considers spatially overlapping orbitals on orbital-pair-specific and system-size-independent domains) and low-rank approximation from ACE (which reduces the number of calls to SCDM + exx during the self-consistent field (SCF) procedure). Across a diverse set of 200 nonequilibrium (H2O)64 configurations (with densities spanning 0.4-1.7 g/cm3), SeA provides a 1-2 order-of-magnitude speedup in the overall time-to-solution, i.e., ≈8-26× compared to the convolution-based PWSCF(ACE) implementation in QE and ≈78-247× compared to the conventional PWSCF(Full) approach, and yields energies, ionic forces, and other properties with high fidelity. As a proof-of-principle high-throughput application, we trained a deep neural network (DNN) potential for ambient liquid water at the hybrid DFT level using SeA via an actively learned data set with ≈8,700 (H2O)64 configurations. Using an out-of-sample set of (H2O)512 configurations (at nonambient conditions), we confirmed the accuracy of this SeA-trained potential and showcased the capabilities of SeA by computing the ground-truth ionic forces in this challenging system containing >1,500 atoms.

High-temperature and high-pressure thermodynamic properties of aqueous zinc sulfate solutions

A new method has been proposed to estimate the osmotic and activity coefficients of aqueous electrolyte solutions under non-ambient conditions on the basis of the Pitzer ion-interaction approach using the volumetric data. Following this method, a compact set of Pitzer ion-interaction parameters, valid within the temperature range 293.15 - 373.15 K, and pressure range 0.1 - 10 MPa have been obtained for aqueous ZnSO4 solutions. These parameters helped evaluate the osmotic and activity coefficients of this system to 3.0 mol∙kg−1. The pressure dependences of osmotic and activity coefficients have also been estimated using the equations derived by Rogers and Pitzer (1982). The results obtained by the method proposed in this research agree very well with those calculated using Rogers and Pitzer approach. The advantage of the method proposed here is that it directly provides a compact set of Pitzer ion-interaction parameters required for describing the osmotic and activity coefficients, in contrast to the other method. This study also provided important insight into the ion-association behavior of aqueous ZnSO4 solution with respect to temperature and pressure. Further, the apparent molar enthalpies have been estimated using appropriate temperature derivatives of the Pitzer ion-interaction parameters obtained in this study.

Fracture analysis of defect Chlorinated Poly Vinyl Chloride pipes based on burst pressure and prediction their fraction of life

Most Chlorinated Poly Vinyl Chloride (CPVC) resins contain 63-69 % chlorine, in particular those used for the extrusion of plumbing tubes, due to this chlorination of basic PVC, CPVC offers a mixture of corrosion resistance and low installation costs for its main applications requiring service in non-ambient conditions. CPVC replaces copper owing to its economic gain and by virtue of its pressure resistance characteristics. In this article, we have been interested in fracture analysis and damage modeling of CPVC tubes by subject CPVC samples to burst pressure tests. We performed a set of burst tests on virgin and artificially damaged CPVC pipe at different notch lengths, then submitted the specimens to burst pressure tests, in addition to recording the pressure and time during these tests for use in conducting the study. The results of the burst tests were exploited to estimate the damage and reliability of the material, these two parameters allow us to follow the degradation of the pipes used; subsequently, we determined a new relationship between these two parameters through the fraction life. This makes it possible to predict the moment of damage acceleration and to intervene at the right time for engaging predictive maintenance.

Protein Design Using Physics Informed Neural Networks

The inverse protein folding problem, also known as protein sequence design, seeks to predict an amino acid sequence that folds into a specific structure and performs a specific function. Recent advancements in machine learning techniques have been successful in generating functional sequences, outperforming previous energy function-based methods. However, these machine learning methods are limited in their interoperability and robustness, especially when designing proteins that must function under non-ambient conditions, such as high temperature, extreme pH, or in various ionic solvents. To address this issue, we propose a new Physics-Informed Neural Networks (PINNs)-based protein sequence design approach. Our approach combines all-atom molecular dynamics simulations, a PINNs MD surrogate model, and a relaxation of binary programming to solve the protein design task while optimizing both energy and the structural stability of proteins. We demonstrate the effectiveness of our design framework in designing proteins that can function under non-ambient conditions.

Atomistic study on reaction kinetics and reactivity of Ni/Al clad particles composites under shock loading.

In prior research on shock-induced reaction, the interfacial crystallization of intermetallics, which plays an important role in solid-state reaction kinetics, has not been explored in detail. This work comprehensively investigates the reaction kinetics and reactivity of Ni/Al clad particle composites under shock loading with molecular dynamics simulations. It is found that the reaction acceleration in a small particle system or the reaction propagation in a large particle system breaks down the heterogeneous nucleation and continuous growth of B2 phase at the Ni/Al interface. This makes the generation and dissolution of B2-NiAl show a staged pattern consistent with chemical evolution. Importantly, the crystallization processes are appropriately described by the well-established Johnson-Mehl-Avrami kinetics model. With the increase in Al particle size, the maximum crystallinity and growth rate of B2 phase decrease and the value of the fitted Avrami exponent decreases from 0.55 to 0.39, showing a good agreement with the solid-state reaction experiment. In addition, the calculations of reactivity reveal that the reaction initiation and propagation will be retarded, but the adiabatic reaction temperature can be elevated when Al particle size increases. An exponential decay relationship is found between the propagation velocity of the chemical front and the particle size. As expected, the shock simulations at non-ambient conditions indicate that elevating the initial temperature significantly enhances the reactivity of large particle systems and results in a power-law decrease in the ignition delay time and a linear-law increase in the propagation velocity.

Sulfur-Phenolate Exchange as a Mild, Fast, and High-Yielding Method toward the Synthesis of Sulfonamides.

Sulfonamides have many important biological applications, yet their synthesis often involves long reaction times under dry and non-ambient conditions. Here we report the synthesis of a large range of sulfonamides at room temperature using 4-nitrophenyl benzylsulfonate as a starting material. Sulfonamides were prepared from a wide range of aliphatic, linear, and cyclic amines, anilines, and N-methylanilines. The yields and reaction times observed here were comparable to or better than those reported previously, establishing sulfur-phenolate exchange as a viable alternative.