Crystal Model Research Articles

Probing the magnetic ground state of stretched diamond lattices NdTaO4 and NdNbO4: Impact of spin-orbit coupling and crystal electric field.

Magnetic systems, wherein competing degree of freedoms arising from spin orbit coupling and crystal electric field lead to non-trivial magnetic ground states, remains in the forefront of research in condensed matter physics. Here, we present a comprehensive investigation on three-dimensional rare-earth based spin systems NdTaO4 and NdNbO4, where the Nd ions sit on a stretched diamond lattice. No signatures of long-range ordering and spin freezing are observed down to 1.8 K, in both cases. The low temperature Curie-Weiss analysis indicate towards the dominance of antiferromagnetic interactions between Nd3+ spins. A three-level crystal electric field model clearly explain the nature of susceptibility curve. At low temperatures, heat capacity data exhibit two-level Schottky anomaly associated with ground state Kramer's doublet. Additionally, the low temperature magnetic behaviour is found reliable to effective spin (Jeff) = ½ ground state, suggesting the presence of quantum fluctuations in both cases. First-principle calculations reveal a significant value of orbital moment with inclusion of spin orbit coupling and reinforce the Jeff = ½ nature of the ground state.

Collective motion and its connection to the energy landscape in 2D soft crystals.

We examine the collective motion in computational models of a two-dimensional dusty plasma crystal and a charged colloidal suspension as they approach their respective melting transitions. To unambiguously identify rearrangement events in the crystal, we map the trajectory of configurations from an equilibrium molecular dynamics simulation to the corresponding sequence of configurations of local potential energy minima ("inherent structures"). This inherent structure (IS) trajectory eliminates the ambiguity that arises from localized vibrational motion. We find that the evolution of the IS trajectory in the crystal can be split into comparatively longer-lived ground states and shorter-lived discrete excited states. These discrete excited energy levels are a consequence of discrete numbers of defect clusters in the crystal. We find that the collective rearrangement occurs through different mechanisms: (i) small closed-loop motion in the ground states without the facilitation of defects, and (ii) much larger and complex open-ended particle motions in excited states that are facilitated by clusters of defects. In both cases, clusters of displacing particles can be separated into much smaller groups of replacing particles with a loop-like structure. In contrast to glass-forming liquids, the mass of the rearranging groups grows on heating towards the melting temperature rather than cooling. We find that crystal melting in these systems can be anticipated by the merging of the average time the crystal spends in the ground state with the average time in the excited states.

Topological phase transitions and switchable edge states for non-Hermitian Aubry-André-Harper model in photonic crystals

Topological phase transitions and switchable edge states for non-Hermitian Aubry-André-Harper model in photonic crystals

A non-isothermal phase-field crystal model with lattice expansion: analysis and benchmarks

Abstract We introduce a non-isothermal phase-field crystal model including heat flux and thermal expansion of the crystal lattice. The fundamental thermodynamic relation between internal energy and entropy, as well as entropy production, is derived analytically and further verified by numerical benchmark simulations. Furthermore, we examine how the different model parameters control density and temperature evolution during dendritic solidification through extensive parameter studies. Finally, we extend our framework to the modeling of open systems considering external mass and heat fluxes. This work sets the ground for a comprehensive mesoscale model of non-isothermal solidification including thermal expansion within an entropy-producing framework, and provides a benchmark for further meso- to macroscopic modeling of solidification.

Benchmarking protein language models for protein crystallization

The problem of protein structure determination is usually solved by X-ray crystallography. Several in silico deep learning methods have been developed to overcome the high attrition rate, cost of experiments and extensive trial-and-error settings, for predicting the crystallization propensities of proteins based on their sequences. In this work, we benchmark the power of open protein language models (PLMs) through the TRILL platform, a be-spoke framework democratizing the usage of PLMs for the task of predicting crystallization propensities of proteins. By comparing LightGBM / XGBoost classifiers built on the average embedding representations of proteins learned by different PLMs, such as ESM2, Ankh, ProtT5-XL, ProstT5, xTrimoPGLM, SaProt with the performance of state-of-the-art sequence-based methods like DeepCrystal, ATTCrys and CLPred, we identify the most effective methods for predicting crystallization outcomes. The LightGBM classifiers utilizing embeddings from ESM2 model with 30 and 36 transformer layers and 150 and 3000 million parameters respectively have performance gains by 3- than all compared models for various evaluation metrics, including AUPR (Area Under Precision-Recall Curve), AUC (Area Under the Receiver Operating Characteristic Curve), and F1 on independent test sets. Furthermore, we fine-tune the ProtGPT2 model available via TRILL to generate crystallizable proteins. Starting with 3000 generated proteins and through a step of filtration processes including consensus of all open PLM-based classifiers, sequence identity through CD-HIT, secondary structure compatibility, aggregation screening, homology search and foldability evaluation, we identified a set of 5 novel proteins as potentially crystallizable.

Scalable Synthesis of 2D ErOCl with Sub-meV Narrow Emissions at Telecom Band.

Van der Waals (vdWs) materials are promising candidates for hetero-integration with silicon photonics toward miniaturization and integration. VdWs materials like molybdenum telluride and black phosphorus, despite being prominent, exhibit air sensitivity, and their room temperature emissions can be significantly broadened by tens of meV. Here, a self-encapsulation strategy is developed to scalably synthesize robust 2D vdWs ErOCl with sub-meV narrow emissions at the telecom C-band. Diverse 2D rare earth materials are also grown via chemical vapor deposition (TmOCl, YbOCl, HoOCl, DyOCl, SmOCl, NdOCl, TbOCl, GdOCl, EuOCl, and PrOCl), demonstrating the strategy's generalizability. The as-grown ErOCl exhibits high crystalline quality and excellent ambientand thermal stability (300°C). Photoluminescence analysis reveals a series of narrow emissions across the visible to near-infrared spectrum. The ErOCl's emission at the telecom band is narrowest among 2D luminescent materials, and suitable for integrating with photonic chips. Temperature-dependent photoluminescence spectra facilitate the understanding of emission mechanisms, analyzed using a crystal field perturbation model. Moreover, these emissions can be tuned by external magnetic fields. This research not only pioneers a novel strategy for synthesizing 2D rare earth materials but also paves the way for innovative building blocks in the realm of on-chip optical communications.

The Dps Protein Protects Escherichia coli DNA in the Form of the Trimer.

The Dps protein is the major DNA-binding protein of prokaryotes, which protects DNA during starvation by forming a crystalline complex. The structure of such an intracellular DNA-Dps complex is still unknown. However, the phenomenon of a decrease in the size of the Dps protein from 90 Å to 69-75 Å during the formation of a complex with DNA has been repeatedly observed, and no explanation has been given. In this work, we show that during the formation of intracellular DNA-Dps crystals, the protein transitions to another oligomeric form: from a dodecameric (of 12 monomers), which has an almost spherical shape with a diameter of 90 Å, to a trimeric (of three monomers), which has a shape close to a torus-like structure with a diameter of 70 Å and a height of 40 Å. The trimer model was obtained through the molecular dynamic modeling of the interaction of the three monomers of the Dps protein. Placement of the obtained trimer in the electron density of in vitro DNA-Dps crystal allowed for the determination of the lattice parameters of the studied crystal. This crystal model was in good agreement with the SAXS data obtained from intracellular crystals of 2-day-old Escherichia coli cells. The final crystal structure contains a DNA molecule in the through channel of the crystal structure between the Dps trimers. It was discussed that the mechanism of protein transition from one oligomeric form to another in the cell cytoplasm could be regulated by intracellular metabolites and is a simple and flexible mechanism of prokaryotic cell transition from one metabolic state to another.

Novel D-Ribofuranosyl Tetrazoles: Synthesis, Characterization, In Vitro Antimicrobial Activity, and Computational Studies.

The goal of this study was to synthesize and evaluate new antimicrobial compounds. We specifically focused on the development of 2,5-disubstituted tetrazole derivatives containing the O-methyl-2,3-O-isopropylidene-(D)-ribofuranoside groups through N-alkylation reactions. The synthesized compounds were characterized using 1H and 13C nuclear magnetic resonance (NMR) spectroscopy. Their antibacterial activity was tested against Pseudomonas aeruginosa, Escherichia coli, Streptococcus fasciens, and Staphylococcus aureus. Density functional theory (DFT) was applied to examine the electronic properties, including the highest occupied molecular orbital (HOMO)-least unoccupied molecular orbital (LUMO) gap, hardness, softness, density of states (DOS), and molecular electrostatic potential. Additionally, crystal structure modeling of protein 7AZ5 was performed to study the binding affinities through hydrophobic interactions and hydrogen bonding. Molecular dynamics simulations were carried out for 100 ns and OPLS_2005 force field re performed to investigate the stability of 3c and 5c into 7AZ5 binding site. Root-mean-square deviation (RMSD), root mean square fluctuation (RMSF), and intermolecular interactions analysis showed that these two compounds may gave relative stability into the 7AZ5 binding site. Several of the N-ribofuranosyl tetrazole derivatives synthesized displayed a strong antibacterial activity. Compounds 1c and 5c were particularly effective, with a minimum inhibitory concentration (MIC) of 15.06 μM and 13.37 μM, respectively, against E. coli and S. aureus both surpassing the efficacy of chloramphenicol (19.34 μM) and ampicillin (28.62 μM). These compounds also displayed the highest binding energies in protein modeling, indicating strong interactions with the DNA polymerase sliding clamp of E. coli. Compounds 1c and 5c show promise as potent antibacterial agents with notable chemical stability and favorable binding profiles. These findings suggest that these derivatives may serve as valuable leads for the development of new antimicrobial drugs.

RAPID QUANTITATIVE ANALYSIS OF METHAMPHETAMINE BY PORTABLE NEAR-INFRARED SPECTROSCOPY AND PLS MODELING

To rapidly detect different types of methamphetamine in the field, a portable near infrared spectroscopy (NIR) method was used to model and analyze the collected samples. Transmission spectra of 359 methamphetamine crystal samples (content range of 7.5-99.4%) and 187 methamphetamine tablet samples (content range of 2.43-23.91%) were collected, first-order derivatives and the Savitaki-Golay smoothing method were applied for spectral preprocessing. The drug concentrations in the calibration and validation sample sets were analyzed using high-performance liquid chromatography. The partial least squares quantitative analysis models were built, and the quantitative models for methamphetamine crystals were 2.10, 2.12 and 2.19% for root mean square error of cross-validation (RMSECV), root mean square error of validation (RMSEV) and root mean square error of prediction (RMSEP), respectively; in contrast, RMSECV, RMSEV, and RMSEP of methamphetamine tablets were 0.78, 0.80, and 0.82%, respectively. The results of the internal cross-validation and the methodology review show that the measurements of the modeled results are consistent with the true values, and that the model has good stability and can be used for accurate field measurements. Therefore, real time sample analysis can be performed using NIR technology combined with chemometric models, which helps the police to determine the quality of drugs in a timely manner for case analysis.

Precipitation-controlled grain boundary engineering in a cast & wrought Ni-based superalloy

Grain boundary engineering (GBE) describes the various approaches to control the fraction and composition of special boundaries in designing engineering materials. For example, complex thermo-mechanical processing routes are harnessed to increase the fraction of Σ3 twin boundaries, bringing about improvements to strength, toughness, and corrosion properties in austenitic stainless steels. However, high-temperature gas turbine engine components designed for the most demanding applications must be manufactured from Ni-based superalloys. To provide the required high-temperature strength, their microstructures are highly complex and consist of an austenitic γ-matrix, γ' precipitates, and grain boundary (GB) carbides, and/or borides. GBE approaches for Ni-based superalloys have been reported to reduce in-service GB cracking via targeted engineering of the GB microstructure. However, the same complex microstructures severely limit the processability of the most advanced Ni-based superalloys required to develop the next generation gas turbine engines.To tackle this challenge, we propose precipitation-controlled GBE for Ni-based superalloys with limited formability, via formation of GB serrations and precipitation upon slow cooling. We showcase our approach by achieving controlled GB precipitation of GB-γ' and M6C carbides in the cast & wrought Ni-based superalloy René 41 via a simple heat treatment. Ductility improvements are predicted via crystal plasticity modeling due to increased slip transmission compatibility. Instead of generating additional Σ3 twin boundaries only, these interfaces are directly incorporated into the GB network. It is shown that precipitation-controlled GBE is enabled by GB-γ' nucleating heterogeneously on M6C whereby competitive coarsening of GB-γ' provides the driving force. The fundamental mechanisms of our GBE approach are discussed and summarized in a qualitative microstructural model.

Grain refinement and its effect of polycrystalline metals during high strain rate deformation: Crystal plasticity modeling

Grain refinement and its effect of polycrystalline metals during high strain rate deformation: Crystal plasticity modeling

Atomistic-Informed and Machine Learning–Assisted Crystal Plasticity Modeling for Material Interfaces

Atomistic-Informed and Machine Learning–Assisted Crystal Plasticity Modeling for Material Interfaces

Asymptotic growth rate of solutions to level‐set forced mean curvature flows with evolving spirals

AbstractHere, we study a level‐set forced mean curvature flow with evolving spirals and the homogeneous Neumann boundary condition, which appears in a crystal growth model. Under some appropriate conditions on the forcing term, we prove that the solution is globally Lipschitz. We then study the large time average of the solution and deduce the asymptotic growth rate of the crystal. Some large time behavior results of the solution are obtained.

Micromechanical analysis of spherulitic polymers in multiaxial and non-proportional fatigue crack nucleation

This study focused on understanding the fatigue response of anisotropic spherulitic polymers by employing a multiscale microscopic modeling approach. The crystal plasticity model together with the Arruda-Boyce model were used to describe the mechanical response of crystalline phase and amorphous. The fatigue behaviors and crack initiation were captured by Fatemi-Socie multiaxial criterion and continuous damage theory under multiaxial and non-proportional loading conditions. The sheaf-like structure of spherulitic polymers was considered to shed light on the anisotropic nature of fatigue failure. The results highlight the role of features of sheaf structure, e.g., initiation orientation, on the fatigue performance of spherulitic polymers, which have not been reported. The localized degradation of mechanical properties and the accumulation of fatigue damage were systematically discussed with various loading patterns. This study provided an in-depth understanding of potential fatigue mechanisms, offering robust support for fatigue resistance design in engineering applications.

Review on multi-scale mechanics fundamentals and numerical methods for electronics packaging interconnect materials

This paper examines multiscale theories and numerical methods for interconnect materials in electronic packaging, focusing on the interplay among micro-scale morphology, meso-scale structure, and macro-scale behavior to improve material reliability and performance prediction. It reviews advanced materials, such as sintered silver and lead-free solder, alongside methodologies like Molecular Dynamics (MD) simulations, cohesive modeling, crystal plasticity modeling, and phase-field modeling, to evaluate mechanical and thermal properties across scales and their long-term reliability. At the microscopic scale, MD simulations reveal the influence of atomic arrangements, grain orientations, and dislocation evolution on mechanical behavior. At the mesoscopic scale, phase-field and crystal plasticity models are combined to analyze pore evolution, grain sliding, and stress concentration under thermal cycling. Macroscopically, models like Anand and Unified Creep Plasticity (UCP) describe viscoplasticity, creep, and fatigue life, offering insights into performance under complex conditions. By systematically integrating diverse research methods and theoretical models, this review highlights the applicability of a multiscale coupling framework, providing a comprehensive understanding of the correlations between morphology, structure, and behavior. This framework serves as theoretical guidance for developing innovative packaging solutions and optimizing materials for high-density, low-power electronic devices.

Investigation of Appropriate Collector Selection for Hematite Removal from Pyrolusite and the Adsorption Mechanism on the Crystal Surface

This study examined the appropriate hematite (Fe2O3) collector for the concentration of pyrolusite (MnO2) in a reverse flotation. Actual ore flotation studies were performed to determine how sodium oleate, sodium dodecyl sulfonate, and oxidized paraffin soap affect hematite removal during reverse flotation of pyrolusite ore. In order to explore the flotation mechanism, simulation experiments were carried out. Firstly, the crystal models of pyrolusite and hematite were established. Then, in order to verify the reliability of the simulation results, the simulated XRD spectra of the crystal model were compared with the measured spectra. Finally, density functional theory and molecular dynamics modeling were used to study the interaction between collector molecules and mineral surfaces. The flotation test results show that oxidized paraffin soap is the best hematite collector and promotes its flotation, removing iron from pyrolusite. Molecular dynamics simulations and density functional theory show that the three collectors (oxidized paraffin soap, sodium oleate, and sodium dodecyl sulfonate) have a much stronger interaction with hematite than with pyrolusite. Therefore, it is possible to separate pyrolusite and hematite through flotation. The simulation results also show that oxidized paraffin soap has the highest adsorption strength and selectivity for hematite. This characteristic makes oxidized paraffin soap an excellent collector for effectively removing hematite from pyrolusite in the reverse flotation process.

Variational Models with Eulerian–Lagrangian Formulation Allowing for Material Failure

We investigate the existence of minimizers of variational models featuring Eulerian–Lagrangian formulations. We consider energy functionals depending on the deformation of a body, defined on its reference configuration, and an Eulerian map defined on the unknown deformed configuration in the actual space. Our existence theory moves beyond the purely elastic setting and accounts for material failure by addressing free-discontinuity problems where both deformations and Eulerian fields are allowed to jump. To do this, we build upon the work of Henao and Mora-Corral regarding the variational modeling of cavitation and fracture in nonlinear elasticity. Two main settings are considered by modeling deformations as Sobolev and SBV-maps, respectively. The regularity of Eulerian maps is specified in each of these two settings according to the geometric and topological properties of the deformed configuration. We present some applications to specific models of liquid crystals, phase transitions, and ferromagnetic elastomers. Effectiveness and limitations of the theory are illustrated by means of explicit examples.

Batch Cooling Crystallization of a Model System Using Direct Nucleation Control and High-Performance In Situ Microscopy

The aim of this study was to investigate the use of automated high performance in situ microscopy (HPM) for monitoring and direct nucleation control (DNC) during cooling crystallization. Compared to other techniques, HPM enables the detection of small crystals in the range of 1 to 10 μm. Therefore, a novel DNC-controlled variable was investigated to determine the potential improvement of the method. The laboratory system and process control software were developed in-house. A well-studied crystallization model system, the seeded batch cooling crystallization of α-glycine from water, was investigated under normal conditions and temperatures below 60 °C. It was postulated that length-weighted edge-to-edge counts in the range of 1 to 10 μm would be most sensitive to the onset of secondary nucleation and are therefore, used as a control variable. Linear cooling experiments were conducted to determine the initial setpoint for the DNC experiments. Three DNC experiments were then performed with different setpoints and an upper and lower counts limit. It was found that the DNC method can be destabilized with a low setpoint and narrow counts limits. In addition, the new controlled variable is highly sensitive to the formation of bubbles at the microscope window and requires careful evaluation. To address the advantages of the DNC method, an additional linear cooling experiment of the same duration was performed, and it was found that the DNC method resulted in a larger average crystal size. Overall, it can be concluded that the HPM method is suitable for DNC control and could be improved by modifying the image processing algorithm.

Dichromate Contaminated Water Treatment using Novel Crystal Violet Azo Dye- Sulphonated Poly(Glycidyl methacrylate) Nano-Composite Adsorbent

In this study, the Cr(VI) metal ions have been removed from dichromate-contaminated water using a novel Azo Dye-Sulphonated Poly (glycidyl methacrylate) nano-composite adsorbent for the first time. Crystal violet Azo dye model (CV) has been immobilized onto nano-sulfonated Poly (glycidyl methacrylate) particles (SPGMA) through the adsorption process to obtain the novel crystal violet Azo Dye-Sulphonated Poly (glycidyl methacrylate) nano-composite adsorbent (CV-SPGMA). The effect of the adsorption conditions on the removal process of Cr (VI) metal ions such as dichromate concentration, adsorption time, temperature, pH, adsorbent dose, and finally agitation speed on the Cr(VI) metal ions removal was studied. The Cr(VI) metal ions removal process has been characterized using isotherms, kinetics, and thermodynamics models. The developed novel CV-SPGMA nano-composite adsorbent chemical structure and morphology were characterized using characterization tools such as FTIR, TGA, and SEM-EDAX analyses before and after the adsorption process. The developmentof the novel CV-SPGMA nano-composite adsorbent for the removal of Cr(VI) ions from dichromate-contaminated waters under mild adsorption conditions opens a new field of multiuse of the same adsorbent in the removal of more than one contaminant.

Investigating Elastic Deformation of Ordered Precipitates by Ab Initio-Informed Phase-Field Crystal Modeling

Ni-based superalloys, essential for high-temperature applications, derive strength from coherent second-order precipitates that impede dislocation motion through coherency misfit and elastic mismatch. This study employs multi-component phase-field crystal (PFC) simulations to explore the elastic deformation of such precipitates. Using a binary ordered square structure for the precipitate and a single species square structure for the matrix, elastic properties and lattice parameters are fitted to data from ab initio density functional theory calculations for Ni and Ni3Ti systems. Simulations reveal a smooth strain gradient across the matrix–precipitate interface with coherency misfit influenced by precipitate size and strain state. These findings highlight the utility of PFC simulations for understanding strain distribution and deformation in precipitate–matrix systems with the potential to offer insights for both experimental and computational studies.