Computational Dynamics Research Articles

Tutorial on Molecular Latent Space Simulators (LSSs): Spatially and Temporally Continuous Data-Driven Surrogate Dynamical Models of Molecular Systems.

The inherently serial nature and requirement for short integration time steps in the numerical integration of molecular dynamics (MD) calculations place strong limitations on the accessible simulation time scales and statistical uncertainties in sampling slowly relaxing dynamical modes and rare events. Molecular latent space simulators (LSSs) are a data-driven approach to learning a surrogate dynamical model of the molecular system from modest MD training trajectories that can generate synthetic trajectories at a fraction of the computational cost. The training data may comprise single long trajectories or multiple short, discontinuous trajectories collected over, for example, distributed computing resources. Provided the training data provide sufficient sampling of the relevant thermodynamic states and dynamical transitions to robustly learn the underlying microscopic propagator, an LSS furnishes a global model of the dynamics capable of producing temporally and spatially continuous molecular trajectories. Trained LSS models have produced simulation trajectories at up to 6 orders of magnitude lower cost than standard MD to enable dense sampling of molecular phase space and large reduction of the statistical errors in structural, thermodynamic, and kinetic observables. The LSS employs three deep learning architectures to solve three independent learning problems over the training data: (i) an encoding of the high-dimensional MD into a low-dimensional slow latent space using state-free reversible VAMPnets (SRVs), (ii) a propagator of the microscopic dynamics within the low-dimensional latent space using mixture density networks (MDNs), and (iii) a generative decoding of the low-dimensional latent coordinates back to the original high-dimensional molecular configuration space using conditional Wasserstein generative adversarial networks (cWGANs) or denoising diffusion probability models (DDPMs). In this software tutorial, we introduce the mathematical and numerical background and theory of LSS and present example applications of a user-friendly Python package software implementation to alanine dipeptide and a 28-residue beta-beta-alpha (BBA) protein within simple Google Colab notebooks.

Quasi-Solid-State Conversion with Fast Redox Kinetics Enabled by a Sulfonamide-Based Electrolyte in Li-Organic Batteries.

The serious dissolution of organic electrode materials (e.g., perylene-3,4,9,10-tetracarboxylic dianhydride, PTCDA) in electrolytes is a major challenge, deteriorating their electrochemical performances and hindering the interpretation of the fundamental redox reaction mechanisms including the intrinsic kinetics and the solvent cointercalation. To address these issues, we propose a rationally designed sulfonamide-based electrolyte to enable a quasi-solid-state conversion (QSSC) of the PTCDA cathode by effectively suppressing its dissolution in the electrolyte. Benefiting from the QSSC, the Li||PTCDA cells can retain ∼95.8% of the original capacity after 300 cycles with both high and stable energy efficiencies >95%, even comparable to the layered transition-metal oxide cathodes, greatly outperforming an ether-based electrolyte with a high PTCDA solubility. The high energy efficiencies indicate that the QSSC of PTCDA has intrinsic fast redox kinetics. Furthermore, the solvent cointercalation mechanism was investigated by density functional theory/molecular dynamic calculations. This work develops a strategy for designing electrolytes for highly stable and efficient Li-organic batteries.

Terahertz time-domain investigation of atacamite: Spectral analysis and theoretical insights for cultural heritage applications

Spectroscopic methods based on terahertz (THz) radiation can represent an innovative approach in the Cultural Heritage field. Specifically, contemporary and historical pigments can exhibit unique fingerprints. However, despite the high selectiveness of terahertz technique, the origin of spectral characteristics is not often known. In this work, the characteristic terahertz-time-domain spectroscopy spectrum of atacamite is reported in the spectral range 0.1–3.7 THz along with ab initio calculation of lattice dynamics to assess the nature of experimental features. The obtained results enable the acquisition of reliable new data in Heritage sciences, which is essential for developing accurate reference pigment databases.

Modeling and analysis of nonlinear dynamics of axisymmetric vector nozzle based on deep neural network

Abstract The axisymmetric nozzle mechanism is the core part for thrust vectoring of aero engine, which contains complex rigid-flexible coupled multibody system with joints clearance and significantly reduces the efficiency in modeling and calculation, therefore the kinematics and dynamics analysis of axisymmetric vectoring nozzle mechanism based on deep neural network is proposed. The deep neural network model of the axisymmetric vector nozzle is established according to the limited training data from the physical dynamic model and then used to predict the kinematics and dynamics response of the axisymmetric vector nozzle. This study analyses the effects of joint clearance on the kinematics and dynamics of the axisymmetric vector nozzle mechanism by a data-driven model. It is found that the angular acceleration of the expanding blade and the driving force are mostly affected by joint clearance followed by the angle, angular velocity and position of the expanding blade. Larger joint clearance results in more pronounced fluctuations of the dynamic response of the mechanism, which is due to the greater relative velocity and contact force between the bushing and the pin. Since axisymmetric vector nozzles are highly complex nonlinear systems, traditional numerical methods of dynamics are extremely time-consuming. Our work indicates that the data-driven approach greatly reduces the computational cost while maintaining accuracy, and can be used for rapid evaluation and iterative computation of complex multibody dynamics of engine nozzle mechanism.

Novel chaotic image cryptosystem based on dynamic RNA and DNA computing

In view of the security problems of image encryption algorithms encoded by single DNA or RNA, to increase the randomness of the diffusion process and the uncertainty of the coding rules, we propose a combining dynamic RNA and DNA computing based chaotic image encryption algorithm, which has a more complicated encryption process for improving the security of the encryption algorithm and increases the difficulty of decoding. First, a new three-dimensional hyperchaotic map is proposed, which exhibits a rich set of dynamic behaviors. Second, the sequences generated by the proposed map are passed to NIST test with good randomness and implemented by digital signal processing hardware, which shows the feasibility of the proposed chaotic map for industrial applications. Second, the K-means algorithm is used to split the plaintext into two parts. Third, the chaotic sequence is used to displace and diffuse the two parts of the plaintext, respectively. Then, chaotic sequences were used to encode using dynamic DNA and RNA of these two parts, respectively. Then, the chaotic sequences were used to compute the dynamic DNA and RNA computing of these two parts, respectively. Finally, the cipher text is decoded accordingly. The experimental results show that compared with some related encryption algorithms, our method has higher security.

Promoting Cl2O Generation from the HOCl + HOCl Reaction on Aqueous/Frozen Air-Water Interfaces.

Hypochlorous acid (HOCl) is considered a temporary reservoir of dichlorine monoxide (Cl2O). Previous studies have suggested that Cl2O is difficult to generate from the reaction of HOCl + HOCl in the gas phase. Here, we demonstrate that Cl2O can be generated from the HOCl + HOCl reaction at aqueous/frozen air-water interfaces, which is confirmed by ab initio molecular dynamic calculations. Distinct from the one-step reaction in the gas phase, our results show that Cl2O generation from HOCl + HOCl on aqueous/frozen interfaces involves two elementary steps, namely, one HOCl deprotonation and one Cl-abstraction from the other HOCl. Specifically, the mechanisms of neutral/acidic catalysis from interfacial water/nitric acid and base catalysis from ammonia, methylamine and dimethylamine have been examined. For the former, HOCl deprotonation is the rate-limiting step, and the total k of Cl2O generation increases to 9.23 × 10-9-9.10 × 10-1 M-1 s-1 at the aqueous interface and 3.20 × 10-7-4.10 × 10-3 M-1 s-1 at the frozen interface, which is at least 23 and 25 orders of magnitude greater than that of gaseous k (3.31 × 10-32 M-1 s-1). For the latter, the rate-limiting step is changed to Cl-abstraction, whose total k dramatically increases to 1.40-8.97 × 107 M-1 s-1 at the aqueous interface and 7.12-9.99 × 106 M-1 s-1 at the frozen interface. Interestingly, the Cl2O production rates ranked in the order of dimethylamine < methylamine < ammonia and decreased with increasing catalytic alkalinity. These findings provide new insights for understanding other Cl2O sources beyond the ClONO2 + HOCl reaction.

QSLE-v1.0: A New Software Package for the Calculation of Coupled Quantum-Classical Dynamics in Condensed Phases Based on a Stochastic Approach.

Recently, a stochastic version of the quantum-classical Liouville equation has been proposed [Campeggio, J.; Cortivo, R.; Zerbetto, M. J. Chem. Phys. 2023, 158, 244104], to compute the coupled quantum-classical dynamics of molecules in condensed phases. The approach, called quantum-stochastic Liouville equation (QSLE), is based on coupling the time evolution of electronic states to a stochastic description of the relevant (classical) nuclear coordinates. Natural internal coordinates are used, i.e., bond lengths, bond angles, and dihedral angles. The approach is tailored to directly propagate the populations of the electronic states over time, based on a classical Fokker-Planck equation for the nuclear degrees of freedom coupled to a master equation for the jumps among the electronic states. The QSLE is a multiscale approach requiring many ingredients to be assembled in order to carry out the numerical solution. To make the approach accessible, a software package that handles the main (and most cumbersome) details of the numerical workflow has been implemented into the software package QSLE-v1.0, which is introduced in the present paper. Here, it is considered the case of one torsional nuclear coordinate and two nonadiabatic electronic potential energy surfaces. This is a very basic model for interpreting photoisomerization or charge transfer phenomena, but despite its simplicity, it can be applied even in complex systems where the relevant quantum/classical parts affecting the phenomena under study are highly localized. A sand-box model system for describing photoisomerization processes is reported to demonstrate the usage of the software package. QSLE-v1.0 is open source and distributed under the GPLv2.0 license.

Benchmark Investigation of SCC-DFTB Against Standard DFT to Model Phononic Properties in Two-Dimensional MOFs for Thermoelectric Applications.

Despite the importance of modeling lattice thermal conductivity in predicting thermoelectric (TE) properties, computational data on heat transport, especially from first-principles, in 2D metal-organic frameworks (MOFs) remain limited due to the high computational cost. To address this, we provide a benchmark of the performance of semiempirical self-consistent-charge density functional tight-binding (SCC-DFTB) methods against density functional theory (DFT) for monolayer, serrated, AA-stacked and/or AB-stacked Zn3C6O6, Cd3C6O6, Zn-NH-MOF, and Ni3(HITP)2 MOFs. Harmonic lattice dynamics calculations, including partial atomic contributions to phonon dispersions, are evaluated with both SCC-DFTB and DFT, whereas anharmonic transport (i.e., thermal conductivity) is evaluated with SCC-DFTB only. Our findings further suggest that unlike the other stacking geometries modeled, serrated Zn3C6O6, serrated Zn-NH-MOF, and wavy serrated Ni3(HITP)2 represent stable geometries. While Zn3C6O6 and Zn-NH-MOF exhibit a higher power factor than Ni3(HITP)2 (as found in our previous work), Zn-NH-MOF shows lower thermal conductivity, resulting in the highest thermoelectric figure of merit (ZT) among the studied MOFs.

Detection of a Planar Tetracoordinate Hydrogen within the Indium Framework by Quantum Dynamics Theory.

In this work, we consider the question how to detect the planar tetracoordination hydrogen geometry which was recently proposed by electronic structure calculations on the In4H+ system (Angew. Chem. Int. Ed. 2024, 63, e202317312; e202400927; e202403214). Keeping the C4v symmetry, a two-dimensional model of In4H+ is designed to build the nonadiabatic Hamiltonian operator with the lowest-lying singlet and triplet states coupled with spin-orbit coupling. The electronic energies in fitting the potential energy matrix are computed at either the MRCI or CCSD (T) level. Having constructed Hamiltonian, the multiconfigurational time-dependent Hartree product method predicts vibrational eigenstates for spectrum and recrossing probability of the proton. These quantum dynamics calculations predict a period of ∼60 fs for the proton recrossing the In4 moiety and further indicate that experimental observation of the D4h geometry for the triplet state is highly probable at room temperature even though the present MRCI and previous CASPT2 calculations (Angew. Chem. Int. Ed. 2024, 63, e202400927) both predict the C4v symmetry. To measure the C4v geometry, a low temperature of ≲30 K could be adopted. Despite the low temperature, the experiment might still miss the C4v geometry due to the nonzero recrossing probability of H at the low kinetic energy region. Further, a new type of hydrogen bonding in the D4h geometry is proposed to explain the interaction between the C4v geometries.

Unveiling the potential of lithium fluoride phosphate (Li2MPO4F, M = Fe, V, Mn) for the next generation of lithium-ion batteries: A comparative study based on first principles and molecular dynamic simulations

LiFePO4 (LFP) cathode with olivine crystal structure has been a key player in safe and affordable energy storage, owing to its low-cost iron and high electrochemical stability within a voltage range of commercial electrolytes (2.8–3.4 V). To maintain these benefits while enhancing its energy density, Li2MPO4F was developed by introducing fluorine (F) and replacing iron with other transition metals (M). However, previous studies on these materials primarily measured performance within a limited voltage window (e.g., 2.5–4.5 V), making it challenging to analyze their performance under advanced electrolytes with a broader voltage range. In this study, we took a novel approach by utilizing first principles and molecular dynamic calculations to investigate the electrochemical performance of Li2MPO4F with three types of transition metals (M = V, Fe, Mn). This unique methodology, which includes calculations on theoretical voltages, atomic structures, and diffusion coefficient after structural optimization, allowed us to predict the impact of transition metals on cathode performance. By closely comparing the expected results, this study discusses the pros and cons of each cation substitution and suggests suitable cathode materials for batteries with high energy density and superior rate capability.

Integrating Theoretical and Experimental Approaches to Unveil the Mechanical Properties of CuSbSe2 Thin Films

Abstract An exhaustive investigation of the mechanical characteristics of CuSbSe2 (CASe) thin films is conducted in this study by combining experimental nanoindentation methods with theoretical simulations. The Ab-initio Molecular Dynamics (AIMD) calculations are performed with the machine learning (ML) force fields. By employing the Vienna Ab-initio Simulation Package (VASP) based on Density Functional Theory (DFT), theoretical inquiries are carried out to identify crucial parameters, such as bonding characteristics, elastic constants, hardness, bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio. Experimental validation is conducted using nanoindentation to investigate load-dependent hardness and Young’s modulus in a manner that closely matches the theorized predictions. The anomalies between experimental and theoretical outcomes are ascribed to anisotropic behavior and grain boundaries. Furthermore, an investigation is conducted into the directional dependence of sound wave velocities in the CASe films, leading to the revelation of intricate elastic property details. By employing an integrated theoretical-experimental approach, the present attempt not only increases the knowledge concerning CASe films but also fortifies the relationship between theory and experiment, thereby bolstering the dependability of our results. The insights provided as a result of this paper facilitate the development of CASe film applications in a variety of technological fields in the future.&amp;#xD;

Robust Adaptive Control System of Variable Sampling Period for Cement Raw Mix Quality Control

The advanced quality control of the raw mix remains a priority for the cement industry, particularly in recent years, where large quantities of alternative fuels and raw materials are used in clinker production, aiming to reduce the CO2 footprint. This study presents an adaptive control system with a variable sampling period for regulating raw mix quality in the raw mill (RM) output in a process with four independent inputs and four outputs: the lime saturation factor (LSF), silica modulus (SM), alumina modulus (AM), and SO3. The three pillars of the system are (1) mill dynamics calculation using exclusively industrial data, (2) the design of the controllers to meet robustness criteria, and (3) performance enhancement through simulators. Our technique periodically adjusts the gains of the controllers based on the mill’s dynamic parameters, which are computed from raw mix laboratory analyses. The presented results correspond to more than 14,000 h of mill operation. The standard deviation of the LSF at the mill outlet ranged from 1.5 to 3, which is equivalent to 1 to 2 standard deviations of LSF reproducibility. The standard deviation of the other moduli was close to the corresponding reproducibility of each. The presented adaptive gain-scheduling controller for LSF can be applicable to a broad range of raw meal grinding systems.

Deciphering the topological landscape of glioma using a network theory framework

Glioma stem cells have been recognized as key players in glioma recurrence and therapeutic resistance, presenting a promising target for novel treatments. However, the limited understanding of the role glioma stem cells play in the glioma hierarchy has drawn controversy and hindered research translation into therapies. Despite significant advances in our understanding of gene regulatory networks, the dynamics of these networks and their implications for glioma remain elusive. This study employs a systemic theoretical perspective to integrate experimental knowledge into a core endogenous network model for glioma, thereby elucidating its energy landscape through network dynamics computation. The model identifies two stable states corresponding to astrocytic-like and oligodendrocytic-like tumor cells, connected by a transition state with the feature of high stemness, which serves as one of the energy barriers between astrocytic-like and oligodendrocytic-like states, indicating the instability of glioma stem cells in vivo. We also obtained various stable states further supporting glioma’s multicellular origins and uncovered a group of transition states that could potentially induce tumor heterogeneity and therapeutic resistance. This research proposes that the transition states linking both glioma stable states are central to glioma heterogeneity and therapy resistance. Our approach may contribute to the advancement of glioma therapy by offering a novel perspective on the complex landscape of glioma biology.

Evolution laws of charge mobility of transformer oil and pressboard material with temperature and electric field strength

Abstract Charge mobility, a pivotal parameter in the space charge analysis model for oil-pressboard insulation of converter transformer under DC electric fields, predominantly relies on theoretical or empirical data. The prevalent omission of empirical, measurement-based evaluations, combined with the neglect of temperature and electric field intensity effects, introduces uncertainties in the calculation of electric field and charge dynamics. Grounded on the principles of the electroacoustic pulse technique for space charge measurements, our investigation established a temperature-controlled platform to determine the charge-charge mobility in oil and pressboard insulation mediums. Utilizing diverse oil-pressboard insulation systems, this study identified the temporal patterns of both positive and negative charge mobilities and unravelled the mechanisms modulated by temperature and electric field intensity: 1) With increasing temperatures (from 20°C to 80°C) and intensifying electric field strengths (from 5kV/mm to 25kV/mm), the charge mobility within transformer oil and pressboard exhibits a rising trend. Notably, temperature variations exert the most significant influence, yielding amplifications up to 24.8 times. 2) The intrinsic properties of different transformer oils and oil-impregnated pressboards result in pronounced differences in their charge transport behaviours. Specifically, naphthenic-based oil demonstrates enhanced charge mobility relative to its paraffin-based counterpart. In contrast, transformer oils with higher kinematic viscosities exhibit diminished charge mobility compared to those with lower viscosities. 3) A linear relationship is observed between the oil absorption rate and electrical conductivity, aligning closely with the insulating pressboard's charge mobility. The evaluation of electric field and interface charge dynamics in oil-pressboard insulation under both DC and polarity-reversed conditions revealed that the electric field decay in naphthenic-based oil is more rapid than in paraffin-based oils. Moreover, both the magnitude and rate of interface charge accumulation in naphthenic-based oils exceed those in paraffin-based variants, further validating the accuracy of our charge mobility measurements and ensuing analysis.

A supramolecular approach towards the photorelease of encapsulated caged acids in water: 7-diethylaminothio-4-coumarinyl molecules as triggers.

Herein, we establish the release of aliphatic acids in water upon excitation of 7-diethylaminothio-4-coumarinyl derivatives encapsulated within the organic host octa acid (OA). The 7-diethylaminothio-4-coumarinyl skeleton, employed here as the trigger, photoreleases caged molecules from the excited triplet state, in contrast to its carbonyl analogue, where the same reaction is known to occur from the excited singlet state. Encapsulation in OA solubilizes molecules in water that are otherwise water-insoluble, and retains the used trigger within itself following the release of the aliphatic acid. Such supramolecular characteristics usher in new features to the photorelease methodology. The thiocarbonyl chromophore extends the absorption of coumarinyl trigger to visible range while enhancing the intersystem crossing (ISC) to the triplet state, making it the reactive state. Despite the non-polar environment within the OA capsules the photocleavage occurs in a heterolytic fashion to release the conjugate base and the used trigger as triplet carbocation in an adiabatic process. Interestingly, the triplet carbocation crosses to the ground singlet surface (closed shell singlet carbocation) with the help of water molecules, possibly aided by C = S chromophore. Utilizing the known excited state dynamics of related thiocoumarinyl and coumarinyl systems, we have identified a few of the important mechanistic features of the photorelease process of 7-diethylaminothio-4-coumarinyl derivatives. Ultrafast excited state dynamic studies and quantum chemical calculations planned should help us better understand the photorelease process so as to effectively exploit the proposed system for potential applications.

Plasmonic Nanocomposite for Visible Light‐Modulated Bimorph‐Actuator

AbstractSoft actuators have great potential applications in sophisticated movement and sensitive devices due to their flexible nature, good interaction, and precise control. However, existing carbon‐based optical actuators are limited in their response under visible light irradiation. The limited visible light absorbance of the carbon nanostructure brought the metallic nanoparticle into the soft actuators that can absorb visible light. This study introduces a new type of plasmonic photothermal‐bimorph actuator, using graphene oxide (GO), reduced graphene oxide (rGO), and silver nanorods (Ag NRs) to overcome the limitations of traditional optical actuators. The bimorph film is actuated by visible and near‐infrared light stimuli with various power densities showing reversible deformation behavior. The actuator shows significant bending associated with a ≈50° change in bending angle under visible light irradiation with a response time of ≈5 ± 1 sec. Furthermore, a smart photo‐controlled non‐contact switch is fabricated based on photo‐thermal conversion properties, demonstrating perfect integration of plasmonic bimorph actuators. The density functional theory based molecular dynamics calculations provide an additional understanding of the bending of actuators under external stimulus. Using illustrative demonstrations of actuators, these results hint at a method for generating multipurpose visible light‐based soft robots, supporting a new approach to developing an optical locking system.

One- and two-photon excitation dynamics using semiclassical electron force field model.

We have extended the semiclassical-based electron force-field simulation by introducing field-electron interaction to enable us to describe linear and nonlinear electronic excitation dynamics of a condensed matter system with low computational cost. To verify the simulation method, as a first step, numerical examples of interaction dynamics of simple systems (H atom, SiH4 molecule, and Si crystalline solid) with applied short electric field pulse as well as the obtained absorbed energies by the one- and two-photon excitations have been reported along with comparison with quantum dynamics calculations as reference.

Structural design and motion characteristics analysis of dual-mode active swing arm tracked robot

Focusing on the demand for complex terrain traversal capability of mobile robots, this paper presents a mobile and creep dual-mode tracked robot configuration with capability of autonomous extrication, in response to solving the problem of tracked robots trapped due to insufficient obstacle-crossing capability. Based on the geometrical characteristics of parallelogram and its dynamic computation on the ground, a topological configuration of mobile tracked mechanism with the ability of creep is studied. An integrated structural design method of mobile chassis that integrates the swing arm and the tracked mechanism is proposed and a dual-mode active swing arm tracked robot structural model is established. The mobile and creep characteristics of the dual-mode active swing arm tracked robot are revealed through comparative simulations in multiple working conditions; Through the prototype tests in such typical working conditions as climbing, turning and obstacle-crossing, the feasibility of creep for the robot is verified and it is proved that the obstacle-crossing ability can be effectively improved. The research results provide theoretical support for improving the adaptability and possibility of mobile robots in complex terrain.

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BackgroundThe maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, current state-of-the-art software tools are not able to leverage the massively parallel processing capabilities of modern GPUs with close-to-peak performance. This motivates the need for more efficient implementations.ResultsCUDASW++4.0 is a fast software tool for scanning protein sequence databases with the Smith-Waterman algorithm on CUDA-enabled GPUs. Our approach achieves high efficiency for dynamic programming-based alignment computation by minimizing memory accesses and instructions. We provide both efficient matrix tiling, and sequence database partitioning schemes, and exploit next generation floating point arithmetic and novel DPX instructions. This leads to close-to-peak performance on modern GPU generations (Ampere, Ada, Hopper) with throughput rates of up to 1.94 TCUPS, 5.01 TCUPS, 5.71 TCUPS on an A100, L40S, and H100, respectively. Evaluation on the Swiss-Prot, UniRef50, and TrEMBL databases shows that CUDASW++4.0 gains over an order-of-magnitude performance improvements over previous GPU-based approaches (CUDASW++3.0, ADEPT, SW#DB). In addition, our algorithm demonstrates significant speedups over top-performing CPU-based tools (BLASTP, SWIPE, SWIMM2.0), can exploit multi-GPU nodes with linear scaling, and features an impressive energy efficiency of up to 15.7 GCUPS/Watt.ConclusionCUDASW++4.0 changes the standing of GPUs in protein sequence database search with Smith-Waterman alignment by providing close-to-peak performance on modern GPUs. It is freely available at https://github.com/asbschmidt/CUDASW4.

Effect of Metal Artifacts in Cone-beam Computed Tomography on Accuracy of Implant Placement by Static and Dynamic Computer- Assisted Implant Surgery: An In Vitro Study.

This study evaluates the impact of metal artifacts in cone-beam computed tomography (CBCT) on the accuracy of static and dynamic computer-assisted implant surgery (CAIS) techniques. An implant was placed on each of thirty 3D-printed models embedded with Cobalt-Chrome strips to simulate metal artifacts by Porcelain-fused-to-metal (PFM), utilizing these CAIS techniques: radiographic template (RT) (n=10), radiographic markers (RM) (n=10), and dynamic navigation (DN) (n=10). Trueness and precision were analyzed by comparing 3D global deviation and the difference in implant positions at the neck, apex, depth, and angle in initial planned and final placed scans. DN exhibited significantly lower 3D global trueness deviation to RT (p = 0.022) and lower angular deviation compared to both RT (p = 0.003) and RM (p = 0.002). RM showed greater trueness at the implant neck compared to DN (p = 0.005) and better depth trueness than RT (p = 0.001) and DN (p = 0.027). DN demonstrated higher precision in implant angulation than RM (p = 0.011) and RT (p = 0.041). In the presence of metal artifacts, both DN and RM techniques offered greater trueness in specific implant positions compared to RT. However, DN proved to be the most precise method for implant placement.