Force Matching Research Articles

Reparameterization of Non-Bonded Parameters for Copper Ions in Plastocyanin: An Adaptive Force Matching Study.

Molecular mechanics rely on existing experimental and theoretical inputs to confidently calculate the trajectories of molecular systems. These calculations, however, are often hindered by missing force field parameters. A notable subject of this problem is metal centers of proteins. This study parameterized, through an adaptive force matching (AFM) workflow, the copper cofactor of plastocyanin in its two oxidation states. New 12-6 Lennard-Jones (LJ) parameters and atomic partial charges were generated to complete the non-bonded description of the copper site. Our models show uniform distorted tetrahedral structures for reduced plastocyanin, Cu(I), and oxidized plastocyanin, Cu(II). These structures align with the QM/MM MD results and existing crystallography studies. TD-DFT calculations, meanwhile, showed that conformations with elongated axial Cu-SMet and shortened equatorial Cu-SCys bonds retain the experimental UV-Vis profile of blue copper (BC) proteins, thus signifying the importance of Cu-S interactions on BC proteins' unique spectroscopic properties.

Anisotropic molecular coarse-graining by force and torque matching with neural networks.

We develop a machine-learning method for coarse-graining condensed-phase molecular systems using anisotropic particles. The method extends currently available high-dimensional neural network potentials by addressing molecular anisotropy. We demonstrate the flexibility of the method by parametrizing single-site coarse-grained models of a rigid small molecule (benzene) and a semi-flexible organic semiconductor (sexithiophene), attaining structural accuracy close to the all-atom models for both molecules at a considerably lower computational expense. The machine-learning method of constructing the coarse-grained potential is shown to be straightforward and sufficiently robust to capture anisotropic interactions and many-body effects. The method is validated through its ability to reproduce the structural properties of the small molecule's liquid phase and the phase transitions of the semi-flexible molecule over a wide temperature range.

Structure and thermodynamics of liquid ruthenium and ruthenium-based alloys from ab initio and classical molecular dynamics with embedded atom model potentials

The combination of classical and ab initio molecular dynamics simulations for computing structural and thermodynamic properties of metallic liquids is illustrated on the example of ruthenium and ruthenium-based alloys. The classical simulations used embedded atom model (EAM) potentials parametrized with the force matching method. The ab initio reference data were obtained using two electronic structure codes implementing the density functional theory plane wave/pseudopotential method. Several methodological aspects in the determination of structural and thermodynamic properties in the liquid phase are examined, first for pure ruthenium. The efficiency of this combined method is finally illustrated on the structure and the pressure of ternary alloys of platinum group metals of interest in the treatment of nuclear wastes.

Modeling and Optimization of a Large-Load Magnetic Levitation Gravity Compensator

This article presents the modeling and optimization design of a large load magnetic levitation gravity compensator. The proposed magnetic levitation gravity compensator comprises three layers of two-dimensional (2D) permanent magnet arrays. The middle mover layer can generate a large passive levitation force to compensate for the gravity of large loads in some magnetic levitation systems, such as the measurement framework in lithography machines or large space optical equipment to be tested on the ground. To accurately predict the passive levitation force, an improved magnetic charge model is proposed, in which the actual working points of each permanent magnet (PM) are considered. The accuracy of the improved model is verified via three-dimensional (3D) finite element simulation. Genetic algorithm (GA) is then adopted as the parameter optimization method to reduce the levitation force stiffness within the effective vertical displacement to the greatest extent possible. Compared with the levitation force performance without parameter optimization, the sensitivity of the levitation force with vertical displacement is significantly reduced. In addition, the mechanical structure is designed, and the mechanical strength is checked. Finally, a magnetic levitation gravity compensator prototype with a passive levitation force of 6200 N is manufactured and tested. The tested values of the levitation force match well with the analytical and simulation results. The tested levitation force stiffness within 4 mm is less than 50 N/mm and basically remains unchanged, which is a superior performance for magnetic levitation systems.

Simulating a flexible water model as rigid: Best practices and lessons learned.

Two ways to create rigid versions of flexible models are explored. The rigid model can assume the Model's Geometry (MG) as if the molecule is not interacting with any other molecules or the ensemble averaged geometry (EG) under a particular thermodynamic condition. Although the MG model is more straightforward to create, it leads to relatively poor performance. The EG model behaves similarly to the corresponding flexible model (the FL model) and, in some cases, agrees even better with experiments. While the difference between the EG and the FL models is mostly a result of flexibility, the MG and EG models have different dipole moments as a result of an effective induction in the condensed phase. For the three water models studied, the property that shows the most difference is the temperature dependence of density. The MG version of the water model by adaptive force matching for ice and liquid does not possess a temperature of maximum density, which is attributed to a downshift of the putative liquid-liquid phase transition line, leading to the hypothesized second critical point of liquid water to manifest at negative pressure. A new three-phase coexistence method for determining the melting temperature of ice is also presented.

Force/moment tracking performance during constant-pose, force-varying, bilaterally symmetric, hand-wrist tasks.

Bilateral movement is widely used for calibration of myoelectric prosthesis controllers, and is also relevant as rehabilitation therapy for patients with motor impairment and for athletic training. Target tracking and/or force matching tasks can be used to elicit such bilateral movement. Limited descriptive accuracy data exist in able-bodied subjects for bilateral target tracking or dominant vs non-dominant dynamic force matching tasks requiring more than one degree of freedom (DoF). We examined dynamic trajectory (0.75Hz band-limited, white, uniform random) constant-posture, hand open-close, wrist pronation-supination target tracking and matching tasks. Tasks were normalized to maximum voluntary contraction (MVC), spanning a±30% MVC force range, in four 1-DoF and 2-DoF tasks: (1, 2) unilateral dominant limb tracking with/without visual feedback, and (3, 4) bilateral dominant/non-dominant limb tracking with mirror visual feedback. In 12 able-bodied subjects, unilateral tracking error with visual feedback averaged 10-15%MVC, but up to 30%MVC without visual feedback. Bilateral matching error averaged∼10%MVC and was affected little by visual feedback type, so long as feedback was provided. In 1-DoF bilateral tracking, the dominant side had statistically lower error than the non-dominant side. In 2-DoF bilateral tracking, the side providing mirror visual feedback exhibited lower error than the opposite side. In 2-DoF tasks (assumed to be more challenging than their constituent 1-DoF tracking tasks), hand grip force errors grew disproportionately larger than those of each wrist DoF. In unilateral 1-DoF tasks, both hand vs target and wrist vs target latency averaged 250-350ms. In unilateral 2-DoF tasks, wrist vs target latency also averaged 250-350ms, while hand vs target latency averaged>500ms. These results provide guidance on bilateral 2-DoF hand-wrist performance in target tracking, and dominant vs non-dominant force matching tasks.

Computer Simulations of a Twist Bend Nematic (NTB): A Coarse-Grained Simulation of the Phase Behaviour of the Liquid Crystal Dimer CB7CB

In recent years, a number of achiral liquid crystal dimer molecules have been shown to exhibit nematic–nematic phase transitions. The lower temperature phase has been identified as the NTB phase, which demonstrates emergent chirality in the spontaneous formation of a heliconical structure. Recent fully atomistic simulations of the molecule CB7CB (1,7-bis-4-(4′-cyanobiphenyl) heptane), a dimer with an odd number of carbon spacers between the mesogenic parts of the molecule, have captured the NTB–N–I phase sequence, providing a picture of the order at a molecular level. In this paper, we use atomistic simulations of CB7CB to develop a coarse-grained model using systematic coarse graining in the NTB phase. We use both force matching (in the form of the MS-CG method) and iterative Boltzmann inversion (IBI) methodologies. Both techniques capture the heliconical order within the NTB phase. Moreover, the model developed via force matching is shown to provide an excellent representation of the atomistic simulation reference model and, remarkably, demonstrates good transferability across temperatures, allowing the NTB–N and N–I phase transitions to be simulated. We also compare results with those of a Martini 3-based coarse-grained model.

Effects of far-infrared radiation lamp therapy on recovery from muscle damage induced by eccentric exercise

ABSTRACT The present study investigated the effects of a far-infrared radiation (FIR) lamp therapy on changes in muscle damage and proprioception markers after maximal eccentric exercise of the elbow flexors (EF: Study 1) and the knee flexors (KF: Study 2) in comparison to a sham treatment condition. In each study, 24 healthy sedentary women were assigned to a FIR or a sham treatment group (n = 12/group). They performed 72 maximal EF eccentric contractions (Study 1) or 100 maximal KF eccentric contractions (Study 2) with their non-dominant limbs. They received a 30-min FIR (wavelength: 8–14 µm) or sham treatment at 1, 25, 49, 73 and 97 h post-exercise to the exercised muscles. Maximum voluntary isometric contraction (MVC) torque, muscle soreness, plasma creatine kinase activity, and proprioception assessed by position sense, joint reaction angle, and force match were measured before, and 0.5, 24, 48, 72, 96 and 120 h post-exercise. The outcome measures showed significant changes (P < 0.05) at 0.5-hour post-exercise (before treatment) similarly (P > 0.05) between the conditions in both studies. However, changes in all measures at 24–120 h post-exercise were smaller (P < 0.05) for the FIR than sham condition in both studies. For example, MVC torque returned to the baseline by 72 h post-exercise for the FIR condition in both studies, but was still 19 ± 6% (Study 1) or 17 ± 12% (Study 2) lower than the baseline at 120 h post-exercise for the sham condition. These results suggested that the FIR lamp therapy was effective for accelerating recovery from muscle damage.

Dipole Cooperativity and Polarization Frustration Determine the Secondary Structure Distribution of Short Alanine Peptides in Water.

The physical driving forces for secondary structure preferences of hydrated alanine peptide are investigated with B3LYP-D3(BJ) and the adaptive force matching (AFM) method. The AFM fit to the DFT surface, ALA2022, provides excellent agreement with the nuclear magnetic resonance scalar coupling constants from experiments. In turn, the model is used to gain insight into the physical driving forces behind secondary structure preferences of hydrated peptides. DFT calculations with and without the Conductor-like Screening Model (COSMO) show that the α helix is stabilized by solvent polarization due to dipole cooperativity. The two adjacent amide groups in β strand form a near-planar trapezoid that is not much larger than the size of water molecules. When the finite size of a water molecule is considered, the stabilization from solvent polarization for such a trapezoid is frustrated. Water molecules cannot find orientations to properly stabilize all four polar regions close to each other with such an awkward arrangement. This leads to quite substantial reduction in polarization stabilization. Although the polyproline II (PP-II) conformation is very similar to the β strand, the small twist in the backbone angles allowed much improved polarization stabilization. The improved polarization, when combined with favorable intrapeptide interactions, leads to the PP-II to be lowest in free energy. Other factors, such as the entropic TΔS and the ϕ, ψ coupling terms, are also studied but are found to play only a minor role. The insight shown in this work helps to better understand the structure of globular and intrinsic disordered proteins and facilitate future force field development.

Post-contraction potentiation can react inversely to post-activation potentiation depending on the test contraction force

The surface electromyographic (EMG) activity of the biceps brachii during weak elbow flexion reportedly increases immediately after strong elbow flexion, even during the exertion of a given force. This phenomenon is called post-contraction potentiation (EMG–PCP). However, the effects of test contraction intensity (TCI) on EMG–PCP remain unclear. This study evaluated PCP levels at various TCI values. Sixteen healthy participants were asked to perform a force matching task (2%, 10%, or 20% of the maximum voluntary contraction [MVC]) before (Test 1) and after (Test 2) a conditioning contraction (50% of MVC). With a 2% TCI, the EMG amplitude was higher in Test 2 than in Test 1. With a 20% TCI, the EMG amplitude was lower in Test 2 than in Test 1. Furthermore, EMG spectral analyses showed that the α- and β-band power ratios in Test 2 were enhanced by 2% TCI compared with Test 1. These findings suggest that TCI is crucial in determining the EMG–force relationship immediately after a brief intensive contraction.

Bottom-Up Informed and Iteratively Optimized Coarse-Grained Non-Markovian Water Models with Accurate Dynamics.

Molecular dynamics (MD) simulations based on coarse-grained (CG) particle models of molecular liquids generally predict accelerated dynamics and misrepresent the time scales for molecular vibrations and diffusive motions. The parametrization of Generalized Langevin Equation (GLE) thermostats based on the microscopic dynamics of the fine-grained model provides a promising route to address this issue, in conjunction with the conservative interactions of the CG model obtained with standard coarse graining methods, such as iterative Boltzmann inversion, force matching, or relative entropy minimization. We report the application of a recently introduced bottom-up dynamic coarse graining method, based on the Mori-Zwanzig formalism, which provides accurate estimates of isotropic GLE memory kernels for several CG models of liquid water. We demonstrate that, with an additional iterative optimization of the memory kernels (IOMK) for the CG water models based on a practical iterative optimization technique, the velocity autocorrelation function of liquid water can be represented very accurately within a few iterations. By considering the distinct Van Hove function, we demonstrate that, with the presented methods, an accurate representation of structural relaxation can be achieved. We consider several distinct CG potentials to study how the choice of the CG potential affects the performance of bottom-up informed and iteratively optimized models.

Dynamic Mechanism and Energy Evolution of the Waterwheel Chaotic Rotation

In order to reveal the mechanism of water wheel chaotic rotation, the Mechanical Mechanism and energy conversion of water wheel chaotic rotation are studied by the method of moment analysis. The mathematical model of the Malkus water wheel rotation is transformed into Kolmogorov system. Based on the different coupling modes of inertia moment, internal moment, dissipation moment and external moment, the main influencing factors and internal mechanical mechanism of the Malkus water wheel chaotic rotation are analyzed and discussed by using the method of theoretical analysis and numerical simulation. The conversion among Hamiltonian energy, kinetic energy and potential energy is investigated. The relationship between the energies and the Rayleigh number is discussed. The main factors affecting chaotic rotation are internal energy, kinetic energy and Hamiltonian energy. Through analysis and simulation, it is found that the lack of torque mode can not make the system generate chaos, but the full torque mode can make the system produce chaos, at the same time, the system can produce chaos only when the dissipation and external force match, at this time the water wheel is in a chaotic rotating state. The Casimir function is introduced to analyze the system dynamics. The bound of chaotic attractor is obtained by the Casimir function. The Casimir function reflects the energy conversion and the distance between the orbit and the equilibria. These relationships are illustrated by numerical simulations.

COCONUT, a Novel Fast-converging MHD Model for Solar Corona Simulations. III. Impact of the Preprocessing of the Magnetic Map on the Modeling of the Solar Cycle Activity and Comparison with Observations

We developed a novel global coronal COCONUT (Coolfluid Corona Unstructured) model based on the COOLFluiD code. The steady-state model is predetermined by magnetograms set as boundary conditions, while inside the numerical domain the corona is described by MHD equations. This set of equations is solved with the use of an implicit solver on unstructured grids. Here we present numerically obtained results for two extremes of the solar activity cycle represented by CR 2161 and CR 2219 for solar maximum and minimum, respectively. We discuss the impact of reconstruction level on representative solar corona solutions and thus also the impact of small magnetic structures on the overall structure of the solar wind. Moreover, both cases correspond to particular solar eclipses, namely those in 2015 March and 2019 July, to allow us the direct comparison of simulations with observed coronal features. We use a validation scheme proposed by Wagner et al. (from less to more sophisticated methods, i.e., visual classification, feature matching, streamer direction and width, brute force matching, topology classification). The detailed comparison with observations reveals that our model recreates relevant features such as the position, direction, and shape of the streamers (by comparison with white-light images) and the coronal holes (by comparison with extreme ultraviolet images) for both cases of minimum and maximum solar activity. We conclude that an unprecedented combination of accuracy, computational speed and robustness even in the case of maximum activity is accomplished at this stage, with possible further improvements in a foreseeable perspective.

Deep coarse-grained potentials via relative entropy minimization.

Neural network (NN) potentials are a natural choice for coarse-grained (CG) models. Their many-body capacity allows highly accurate approximations of the potential of mean force, promising CG simulations of unprecedented accuracy. CG NN potentials trained bottom-up via force matching (FM), however, suffer from finite data effects: They rely on prior potentials for physically sound predictions outside the training data domain, and the corresponding free energy surface is sensitive to errors in the transition regions. The standard alternative to FM for classical potentials is relative entropy (RE) minimization, which has not yet been applied to NN potentials. In this work, we demonstrate, for benchmark problems of liquid water and alanine dipeptide, that RE training is more data efficient, due to accessing the CG distribution during training, resulting in improved free energy surfaces and reduced sensitivity to prior potentials. In addition, RE learns to correct time integration errors, allowing larger time steps in CG molecular dynamics simulation, while maintaining accuracy. Thus, our findings support the use of training objectives beyond FM, as a promising direction for improving CG NN potential's accuracy and reliability.

The role of left temporo-parietal and inferior frontal cortex in comprehending syntactically complex sentences: A brain stimulation study

Background and objectivesSyntactic competence relies on a left-lateralized network converging on hubs in inferior-frontal and posterior-temporal cortices. We address the question whether anodal transcranial direct current stimulation (a-tDCS) over these hubs can modulate comprehension of sentences, whose syntactic complexity systematically varied along the factors embedding depths and canonicity. Semantic content and length of the sentences were kept identical and forced choice picture matching was required after the full sentence had been presented. MethodsWe used a single-blind, within-subject, sham-controlled design, applying a-tDCS targeting left posterior tempo-parietal (TP) and left inferior frontal cortex (FC). Stimulation sites were determined by individual neuro-navigation. 20 participants were included of whom 19 entered the analysis. Results were analysed using (generalized) mixed models. In a pilot-experiment in another group of 20 participants we validated the manipulation of syntactic complexity by the two factors embedding depth and argument-order. ResultsReaction times increased and accuracy decreased with higher embedding depth and non-canonical argument order in both experiments. Notably a-tDCS over TP enhanced sentence-to-picture matching, while FC-stimulation showed no consistent effect. Moreover, the analysis disclosed a session effect, indicating improvements of task performance especially regarding speed. ConclusionsWe conclude that the posterior ‘hub’ of the neuronal network affording syntactic analysis represents a ‘bottleneck’, likely due to working-memory capacity and the challenges of mapping semantic to syntactic information allowing for role assignment. While this does not challenge the role of left inferior-frontal cortex for syntax processing and novel-grammar learning, the application of highly established syntactic rules during sentence comprehension may be considered optimized, thus not augmentable by a-tDCS in the uncompromised network. Significance statementAnodal transcranial direct current stimulation (a-tDCS) over left temporo-parietal cortex enhances comprehension of complex sentences in uncompromised young speakers. Since a-tDCS over left frontal cortex did not elicit any change, the ‘bottleneck’ for the understanding of complex sentences seems to be the posterior, temporo-parietal rather than the anterior inferior-frontal ‘hub’ of language processing. Regarding the attested role of inferior-frontal cortex in syntax processing, we suggest that its function is optimized in competent young speakers, preventing further enhancement by (facilitatory) tDCS. Results shed light on the functional anatomy of syntax processing during sentence comprehension; moreover, they open perspectives for research in the lesioned language network of people with syntactic deficits due to aphasia.

A Deformation Control Method in Thin-Walled Parts Machining Based on Force and Stiffness Matching Via Cutter Orientation Optimization

Abstract In the milling process, significant machining errors may occur due to the low stiffness of thin-walled parts. To reduce the cutting force-induced deformation in milling thin-walled parts such as blades, a cutter orientation optimization algorithm based on stiffness matching is proposed. The concept of maximum stiffness direction is put forward according to the phenomenon that different deformations are produced when applying forces with the same magnitude but in different directions. The stiffness of the in-process workpiece is obtained using the stiffness updating method. The cutter orientation optimization algorithm is presented to match the force with the maximum stiffness direction. The best cutter orientation is obtained by adopting the quantum particle swarms optimization algorithm at the key cutter location points, and then the cutter orientations of all cutter location points are obtained by the quaternion interpolation algorithm. The proposed deformation control method is verified on thin-walled blade milling experiments, and the experimental results show that the machining deformation of the blade with the optimized cutter orientation is reduced by about 36.51%, indicating that the proposed method can effectively reduce the machining deformation of the thin-walled parts.

Video Sequence Image Matching Algorithm Based on Adaptive Gamma Correction

Aiming at the low matching accuracy and poor robustness in video sequence image matching, a video sequence image matching algorithm based on Adaptive Gamma Correction is proposed in the paper. Firstly, Adaptive Gamma Correction is used to enhance the contrast of video sequence images. Then feature extraction and description are realized by the ORB algorithm. The RANSAC algorithm is optimized in matching by improving the interior point ratio after Brute Force Match. The experimental results show that the algorithm proposed improves the correct matching rate by 19.51%, 12.53%, and 4.87% respectively compared with the SIFT, ORB, and ORB+RANSAC algorithms without increasing the running time. Meanwhile, the algorithm in this paper has good robustness in video sequence image matching.

Differential changes in somatosensory evoked potentials and motor performance: pursuit movement task versus force matching tracking task.

Force modulation relies on accurate proprioception, and force-matching tasks alter corticocerebellar connectivity. Corticocerebellar (N24) and corticomotor pathways are impacted following the acquisition of a motor tracing task (MTT), measured using both somatosensory evoked potentials (SEPs) and transcranial magnetic stimulation. This study compared changes in early SEP peak amplitudes and motor performance following a force-matching tracking task (FMTT) to an MTT. Thirty (18 females) right-handed participants, aged 21.4 ± 2.76, were electrically stimulated over the right-median nerve at 2.47 Hz and 4.98 Hz (averaged 1,000 sweeps/rate) to elicit SEPs, recorded via a 64-channel electroencephalography cap, before, and after task acquisition using the right abductor pollicis brevis muscle. Retention was measured 24 h later. Significant time-by-group interactions occurred for the N20 SEP: 6.3% decrease post-FMTT versus 5.5% increase post-MTT (P = 0.013); P25 SEP: 4.0% decrease post-FMTT versus 10.3% increase post-MTT (P = 0.006); and N18 SEP: 113.4% increase post-FMTT versus 4.4% decrease post-MTT (P = 0.006). N18 and N30 showed significant effect of time (both P < 0.001). Motor performance: significant time-by-group interactions-postacquisition: FMTT improved 15.3% versus 24.3% for MTT (P = 0.025), retention: FMTT improved 17.4% and MTT by 30.1% (P = 0.004). Task-dependent differences occurred in SEP peaks associated with cortical somatosensory processing (N20 and P25), and cerebellar input (N18), with similar changes in sensorimotor integration (N30), with differential improvements in motor performance, indicating important differences in cerebellar and sensory processing for tasks reliant on proprioception.NEW & NOTEWORTHY This study demonstrates neurophysiological differences in cerebellar and somatosensory cortex pathways when learning a motor task requiring visuomotor tracking versus a task that requires force-matching modulation, in healthy individuals. The clear neurophysiological differences in early somatosensory evoked potentials associated with cortical somatosensory processing, cerebellar input, and sensorimotor integration between these two tasks demonstrate some of the neural correlates of force modulation and validate the force-matching task for use in future work.

Biceps Brachii Kasi İçin Maksimal ve Sabit Yük Altinda Submaksimal Kasilmalara Göre Elektromiyografik Normalizasyon Yöntemlerinin Güvenilirliği ve Korelasyonu

Normalization of surface electromyography (sEMG) signal amplitude is considered as a necessary operation to enable comparable data on different muscles, individuals, and sessions. Previous studies usually suggested using the maximal contraction normalization procedure. However, that procedure might not always be possible or the best method in some sEMG studies. The purpose of this study is therefore twofold. The first is to investigate reliability of two different constant load normalization procedures (with and without feedback) at different constant-force submaximal contractions. The second is to investigate correlation of normalization factors obtained from maximal voluntary and standardized submaximal tasks. 18 young healthy participants took part in the study. Subjects performed three muscle contraction tasks, namely, (i) maximal voluntary contraction (MVC) task: isometric maximal contraction of biceps brachii muscle, (ii) force matching task (FM): matching 2.5 kg, 5.0 kg, 7.5 kg and 10.0 kg force with visual feedback, and (iii) load holding (LH) task: holding 2.5 kg, 5.0 kg, 7.5 kg and 10.0 kg weights without visual feedback. sEMG amplitude normalization factors were examined for three tasks. The results of the study suggested that the reliability of sEMG amplitude normalization factors from FM and LH tasks for four target forces or loads were high (intraclass correlation (ICC): 0.863-0.958) to very high (ICC: 0.970-0.995). Due to some limitations of the MVC maximal contraction normalization procedure, normalization to the maximal might not always be possible or the best method for some sEMG studies. In such cases, submaximal isometric load holding tasks could be an alternative to the MVC task for biceps brachii muscle.

Chemical Pressure-Derived Assembly Principles for Dodecagonal Quasicrystal Approximants and Other Complex Frank-Kasper Phases.

The structures of complex intermetallic compounds can often be interpreted in terms of assemblies of units from simpler parent phases. For example, dodecagonal quasicrystals appear, when viewed down their high-symmetry axes, as plane-filling arrangements of square and triangular tiles corresponding to the Cr3Si and Al3Zr4 structure types, respectively. The atomic arrangements and cell-dimensions at the (100) faces of the cells of these structures provide a close geometrical match, which underlies not only dodecagonal quasicrystals and their approximants but also the much more common σ-phase structure. In this article, we show that such intergrowth of parent structures can arise from more than just geometrical coincidences but can be driven by a complementary matching of atomic packing forces. DFT-chemical pressure (CP) analysis on elemental versions of the Cr3Si and Al3Zr4 types reveal that in both cases arrays of positive interatomic pressures inhibit the formation of optimal contacts elsewhere in the structures. When they are lined up at the potential Cr3Si/Al3Zr4 interfaces, however, positive pressures from the two structures interdigitate rather than coincide, providing the opportunity for the relaxation of strained interatomic contacts. That such relief is afforded by the interfaces is confirmed by CP analysis of the σ-phase (FeCr-type) structure. Building on this scheme, we introduce the CPinterface function to represent how the CP features of atoms within a structure impact planes or other surfaces that could serve as interfaces between different structures. Using this function, we then explore how the favorability of interfaces between Cr3Si- and Al3Zr4-type units is tuned by partial elemental substitution with Si, as well as their potential matches with Laves phase units. The emerging picture provides an account for features of the quasicrystal approximants Mn7VSi2 and Mn81.5Si18.5, as well as a framework for approaching intermetallic intergrowth structures more broadly.