Optimal Material Design Research Articles

Energy Optimization Design of Limestone Hybrid Concrete in Consideration of Stress Levels and Carbonation Resistance

This research describes a genetic algorithm-based process for the optimization design of sustainable concrete with limestone powder. The objective of the optimization design was set as the embodied energy. The restraints of the optimization design consist of strength, workability, and carbonation resistance along with stress. The result of the research is shown as follows: (1) for low-strength concrete, carbonation dominates the mixture design of limestone hybrid concrete. Furthermore, the levels of stress and stress types modify the carbonation and optimization mixtures. The influence of tensile stress on optimization mixtures was much more apparent than compressive stress. (2) For concrete with high strength, strength dominates the mixture design of limestone hybrid concrete. (3) The optimization mixtures with low carbon footprints overlapped with those with low embodied energy. In addition, the new knowledge of the research is shown as follows: (1) find the decisive factor of concrete mixture design, (2) show a material design method considering structural stress, and (3) validate for various aims of optimal material design. In summary, the proposed model can be regarded as a common approach for the design of concrete mixture in consideration of strength, workability, carbonation resistance, and structural stress.

Interphase in Polymer Nanocomposites.

The lightweight and high-strength functional nanocomposites are important in many practical applications. Natural biomaterials with excellent mechanical properties provide inspiration for improving the performance of composite materials. Previous studies have usually focused on the bionic design of the material’s microstructure, sometimes overlooking the importance of the interphase in the nanocomposite system. In this Perspective, we will focus on the construction and control of the interphase in confined space and the connection between the interphase and the macroscopic properties of the materials. We shall survey the current understanding of the critical size of the interphase and discuss the general rules of interphase formation. We hope to raise awareness of the interphase concept and encourage more experimental and simulation studies on this subject, with the aim of an optimal design and controllable preparation of polymer nanocomposite materials.

Development of a Multi-Criteria Design Optimization Methodology for Automotive Plastics Parts.

The plastic industry is undergoing drastic changes, due to the customer sustainability perception of plastics, and the eruption of new processes (such 3D printing) and materials (such as renewably sourced resins). To enable a fast transition to high-quality, sustainable plastic applications, a specific methodology could be a key competitive advantage. This novel methodology is focused on improving the objectivity and efficiency of plastic production and the design review process. It is applicable to discrete optimization events in any product lifecycle milestone, from concept design to serial production stages. The methodology includes a natural way to capture plastic-related knowledge and trends, oriented towards building a dynamic “interaction matrix”, with a list of potential optimizations and their positive or negative impacts in a comprehensive set of multi-criteria evaluations. With an innovative approach, the matrix allows the possibility to incorporate a business strategy, which could be different at every lifecycle stage. The business strategy is translated from the common “verbal” definition into a quantitative set of “Target and Restrictions”, making it possible to detect and prioritize the best potential design optimization changes according to the strategy. This methodology helps to model and compare design alternatives, verify impacts in every evaluation criteria, and make robust and objective information-based decisions. The application of the methodology in real cases of plastic material design optimization in the automotive industry has provided remarkable results, accelerating the detection of improvement methods aligned with the strategy and maximizing the improvement in product competitiveness and sustainability. In comparison with the simultaneous application of existing mono-criteria optimization methodologies (such as “Design to Cost” or “Eco Design”) and subjective expert-based reviews, the novel methodology has a reduced workload and risks, confirming its potential for future application and further development in other polymer-based products, such as consumer goods or packaging.

Optimal control and design of magnetic field-responsive smart polymer composites

This paper presents a novel in-silico framework for the simultaneous optimal control and design of complex magnetic responsive polymer composite materials. State-of-the-art optimisation techniques are used in conjunction with the latest developments in the numerical solution of hard-magnetic soft materials undergoing large (potentially extreme) deformations, in order to address the challenging task of designing shape-morphing two-dimensional composite magnetic sheets. This paper introduces the following key novelties: (i) an optimisation-driven method for the simultaneous optimal control and design of the externally applied magnetic flux density as well as the remnant magnetisation of hard particles within the elastomer matrix, (ii) the well-posedness character of the optimisation problem is established by proving existence of solutions for both the underlying state equation and the control problem itself, (iii) a gradient-based optimisation algorithm is proposed for the numerical approximation of the problem, where explicit expressions of the continuous gradients are obtained by using the formal Lagrangian method. Furthermore, a series of numerical examples are presented in order to demonstrate the capability of the proposal as an alternative to intuition or experimentally-based approaches, representing an optimisation-driven method that facilitates the design of smart materials yielding complex magnetically induced shape morphing configurations.

Aggregation of nanoparticles and their effect on mechanical properties of carbon nanotube networks

Nanoparticles (NPs) are widely used to tune the mechanical and physical properties of carbon nanotube (CNT) networks in many practical applications. However, the distribution of NPs in CNT networks and their effects on microstructural evolutions and mechanical properties remain elusive. We employed the coarse-grained molecular dynamics (CGMD) simulations to systematically investigate these issues. First, we found that compared to ambient temperature and the frequency of cyclic loads, the relative cohesion energy of NPs and strain amplitude of cyclic loads are more important factors for controlling the aggregation of NPs; it was also revealed that NPs with larger relative cohesion energy and in larger-strain cyclic loads would aggregate more severely in CNT networks. Second, we observed that the Young's modulus and the tensile strength of the material can be increased by up to ∼3.2 and ∼2.0 times, respectively, at the critical volume fraction of NPs (∼21.6%). Finally, the underlying mechanisms by which NPs strengthen the inter-tube joints and constrain the bundling of CNTs are unveiled. These results should be useful for the optimal design of CNT-based advanced materials.

Evaluating Halogen-Bond Strength as a Function of Molecular Structure Using Nuclear Magnetic Resonance Spectroscopy and Computational Analysis.

Halogen bonding (XB) is a highly directional, non-covalent intermolecular interaction between a molecule (XB donor) presenting a halogen with an electron-deficient region or sigma hole (σ-hole) and an electron-rich or Lewis-base molecule (XB acceptor). A systematic, experimental, and theoretical study of solution-phase XB strength as a function of the molecular structure for both XB donor and acceptor molecules is presented. The impact of specific structural features is assessed using 19F and 1H nuclear magnetic resonance (NMR) titrations to determine association constants, density functional theory calculations for interaction energies and bond lengths, as well as 19F-1H HOESY NMR measurements of intermolecular cross-relaxation between the interacting XB donor-acceptor adducts. For XB donor molecules (perfluoro-halogenated benzenes), results indicate the critical importance of iodine coupled with electron-withdrawing entities. Prominent structural components of XB acceptor molecules include a central atom working in conjunction with a Lewis-base atom to present high electron density directed at the σ-hole (e.g., tributylphosphine oxide). Additionally, larger surrounding aliphatic R groups (e.g., butyl and octyl) were found to significantly stabilize strong XB, particularly in solvents that promote the interaction. With a more thorough understanding of structure-optimized XB, one can envision harnessing XB interactions more strategically for specific design of optimal materials and chemical applications.

A Modeling-Based Design to Engineering Protein Hydrogels with Random Copolymers.

Protein enzymes have shown great potential in numerous technological applications. However, the design of supporting materials is needed to preserve protein functionality outside their native environment. Direct enzyme-polymer self-assembly offers a promising alternative to immobilize proteins in an aqueous solution, achieving higher control of their stability and enzymatic activity in industrial applications. Herein, we propose a modeling-based design to engineering hydrogels of cytochrome P450 and of PETase with styrene/2-vinylpyridine (2VP) random copolymers. By tuning the copolymer fraction of polar groups and of charged groups via quaternization of 2VP for coassembly with cytochrome P450 and via sulfonation of styrene for coassembly with PETase, we provide quantitative guidelines to select either a protein-polymer hydrogel structure or a single-protein encapsulation. The results highlight that, regardless of the protein surface domains, the presence of polar interactions and hydration effects promote the formation of a more elongated enzyme-polymer complex, suggesting a membrane-like coassembly. On the other hand, the effectiveness of a single-protein encapsulation is reached by decreasing the fraction of polar groups and by increasing the charge fraction up to 15%. Our computational analysis demonstrates that the enzyme-polymer assemblies are first promoted by the hydrophobic interactions which lead the protein nonpolar residues to achieve the maximum coverage and to play the role of the most robust contact points. The mechanisms of coassembly are unveiled in the light of both protein and polymer physical-chemistry, providing bioconjugate phase diagrams for the optimal material design.

Experimental Study on Performance of Cement Stabilized Macadam Modified with Composite Agent

In this paper, three composite agents (i.e. emulsified asphalt, EA; styrene butadiene rubber, SBR; rubber powder, RP) were employed to modify the cement stabilized macadam (CSM) for the optimal design of semi-rigid base materials. The feasibility of utilizing EA/SBR/RP composites in the cement stabilized macadam is investigated from the perspectives of the modification mechanism and durability performance. To investigate the effects of different modifiers on the modification mechanism of the cement stabilized macadam, the unconfined compressive strength (UCS), indirect tensile strength (ITS), and compressive resilience modulus (CRM) of the modified samples with the variations in EA/SBR/RP composites groups were tested. Moreover, the drying shrinkage test and temperature shrinkage tests are performed to reveal the effectiveness of EA/SBR/RP composites on durability performance of cement stabilized macadam. The results show that the UCS, ITS, and CRM of the samples decrease with the increasing of EA/SBR/RP composites during 28 days. The average drying shrinkage coefficient (DSC) increases with the increasing of EA/SBR/RP composites. Considering all the above experimental results, the recommended dosage of the composite agent is 2% EA, 0.75% SBR, and 0.6% RP.

Optimal design of geopolymer grouting material for semi-flexible pavement based on response surface methodology

Composite grouting material (CGM) is an important part of constructing the semi-flexible pavement (SFP). The usage of CGM can improve pavement durability and rutting resistance in heavy-duty traffic. Owing to the environmental protection and performance requirements for grouting in loose sediments, the geopolymer grouting material (GPGM) as a new type of CGM is designed by a combination of powder materials, alkali and activator. The response surface method (RSM) is used to study the influence of three independent constituents (powder quality ratio, sodium oxide content, and water-binder ratio) as well as their interactions on four response variables (fluidity, 7 d dry-shrinkage ratio, 7 d compressive strength, and 28 d compressive strength) of GPGM. Furthermore, three types of additives, including water reducer, shrinkage reducing admixture and polymer latex, are taken into account to design the expected responses of GPGM by using the orthogonal test design method (OTDM). Finally, the micro detection experiments are built to compare the micro characteristics of GPGM blended with and without additives. The results show that the optimal mix proportion of GPGM can be obtained by RSM and OTDM. The micro performance tests and analysis can well explain the mechanism of inner constituents in GPGM.

Multi-objective optimization for materials design with improved NSGA-II

Artificial intelligence and data science have accelerated the research and development into new materials. However, in a new materials design, it is more important to determine what the next possible “action” is (which is occasionally recommended to be one or more experimental points), than just the property predictions. This reason, multiple objective optimization, using a non-dominated sorting genetic algorithm (NSGA), for example, can be applied. However, a traditional NSGA mainly focuses on convergence and the diversity of the solutions, while neglecting the property preference expected by material scientists. Therefore, based on a Pareto optimal solution and NSGA-II algorithm, we propose an improved NSGA-II algorithm, called NSGA-II with preference (NSGA-IIP). At the main idea here, when the NSGA-IIP algorithm calculates the crowding distance, the cosine similarity is introduced to make the population of the next generation gather toward the direction of preference. For NSGA-IIP, it can adjust the solution set direction according to the expected property preferences. Moreover, we propose four indicators, i.e., the generational distance, inverted generational distance, mean cosine similarity, and points in sector to evaluate the optimization algorithm in terms of the convergence, solution diversity, and consistency regarding the preference. Finally, we apply this method to the materials design of a thermal barrier ceramic coating and compare it with the previous method. The results show that our proposed NSGA-IIP achieves better practicability and time performance for a new material design.

Polymer-Based Carriers in Dental Local Healing-Review and Future Challenges.

Polymers in drug formulation technology and the engineering of biomaterials for the treatment of oral diseases constitute a group of excipients that often possess additional properties in addition to their primary function, i.e., biological activity, sensitivity to stimuli, mucoadhesive properties, improved penetration of the active pharmaceutical ingredient (API) across biological barriers, and effects on wound healing or gingival and bone tissue regeneration. Through the use of multifunctional polymers, it has become possible to design carriers and materials tailored to the specific conditions and site of application, to deliver the active substance directly to the affected tissue, including intra-periodontal pocket delivery, and to release the active substance in a timed manner, allowing for the improvement of the form of application and further development of therapeutic strategies. The scope of this review is polymeric drug carriers and materials developed from selected multifunctional groups of natural, semi-synthetic, and synthetic polymers for topical therapeutic applications. Moreover, the characteristics of the topical application and the needs for the properties of carriers for topical administration of an active substance in the treatment of oral diseases are presented to more understand the difficulties associated with the design of optimal active substance carriers and materials for the treatment of lesions located in the oral cavity.

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems.Graphic .

The regulating effect of trace elements Si, Zn and Sr on mineralization of gelatin-hydroxyapatite electrospun fiber

Biomineralization approaches have been increasingly adopted to synthesizing advanced materials with superior properties. Nevertheless, the potential influence of inorganic trace elements on the mineralization process of collagen has been rarely reported, despite of the significant progress achieved on exploiting the critical roles of organic polymers in regulating the collagen mineralization. To this aim, the potential roles of Si, Zn and Sr in regulating the mineralization of gelatin-hydroxyapatite (HA) composite fibers have been examined in this study. The results indicated that the incorporation of trace elements not only promoted the biomineralization of gelatin, but also led to drastic change in the mineralization behavior. In particular, the gelatin-SiHA sample showed uniform mineralization predominantly inside the fibers, with nucleation and growth directions along the c-axis of the gelatin fibers. On the contrary, the gelatin-HA sample showed nucleation outside the fibers and spherical mineral crystals on top of fibers, typical structure for heterogeneous nucleation. As the mineralization process proceeded, the gelatin-ZnHA and gelatin-SrHA samples evolved into having similar structure as the gelatin-SiHA sample, despite of showing totally different mineralization behaviors at early time. Overall, the incorporation of trace elements seemed to lower the nucleation barriers, led to a more homogeneous mineralization mode within the fiber region and formation of mineralized structures closer to those in natural bone. Moreover, mineralized samples with trace elements demonstrated improved adhesion and cytoskeleton organization of osteoblastic cells. Such finding would provide important insight for understanding the mineralization process and the optimal design of advanced biological materials.

Design of All-Small-Molecule Organic Solar Cells Approaching 14% Efficiency via Isometric Terminal Alkyl Chain Engineering

Morphology is crucial to determining the photovoltaic performance of organic solar cells (OSCs). However, manipulating morphology involving only small-molecule donors and acceptors is extremely challenging. Herein, a simple terminal alkyl chain engineering process is introduced to fine-tune the morphology towards high-performance all-small-molecule (ASM) OSCs. We successfully chose a chlorinated two-dimension benzo[1,2-b:4,5-b′]dithiophene (BDT) central unit and two isomeric alkyl cyanoacetate as the end-capped moieties to conveniently synthesize two isomeric small-molecule donors, namely, BT-RO-Cl and BT-REH-Cl, each bearing linear n-octyl (O) as the terminal alkyl chain and another branched 2-ethylhexyl (EH) as the terminal alkyl chain. The terminal alkyl chain engineering process provided BT-RO-Cl with 13.35% efficiency and BT-REH-Cl with 13.90% efficiency ASM OSCs, both with Y6 as the electron acceptor. The successful performance resulted from uniform phase separation and the favorable combination of face-on and edge-on molecular stacking of blended small-molecule donors and acceptors, which formed a fluent 3D transport channel and thus delivered high and balanced carrier mobilities. These findings demonstrate that alkyl chain engineering can finely control the morphology of ASM OSCs, and provides an alternative for the optimal design of small-molecule materials towards high-performance ASM OSCs.

Material Design for Optimal Postbuckling Behaviour of Composite Shells.

Lightweight thin-walled structures are crucial for many engineering applications. Advanced manufacturing methods are enabling the realization of composite materials with spatially varying material properties. Variable angle tow fibre composites are a representative example, but also nanocomposites are opening new interesting possibilities. Taking advantage of these tunable materials requires the development of computational design methods. The failure of such structures is often dominated by buckling and can be very sensitive to material configuration and geometrical imperfections. This work is a review of the recent computational developments concerning the optimisation of the response of composite thin-walled structures prone to buckling, showing how baseline products with unstable behaviour can be transformed in stable ones operating safely in the post-buckling range. Four main aspects are discussed: mechanical and discrete models for composite shells, material parametrization and objective function definition, solution methods for tracing the load-displacement path and assessing the imperfection sensitivity, structural optimisation algorithms. A numerical example of optimal material design for a curved panel is also illustrated.

A fluorinated polymer sponge with superhydrophobicity for high-performance biomechanical energy harvesting

Human body contains various biomechanical energy, which emerges as a pervasive and sustainable energy resource for wearable electronics in the era of Internet of Things. We have developed a fluorinated polymer sponge based triboelectric nanogenerator (FPS-TENG) that provides stable electrical output over a wide range of ambient humidity. The humidity resistance due to excellent hydrophobic property of the fluorinated polymer sponge can overcome the adverse effects of moisture. The FPS-TENG also exhibits high durability even after enduring heavy abrasion. The output voltage of the FPS-TENG is three times higher than that of the pristine polymer film (PPF) based TENG. When assembled with hydrophobic copper (HC) contact electrodes, the FPS-TENG retains almost 90% electrical output over 20–85% relative humidity. Moreover, super durability is achieved by quasi-bulk-phase functionalization. After 1 mm-thickness abrasion of the fluorinated polymer sponge, the output voltage is degraded by only 10%. Under the optimal operating conditions, the FPS-TENG delivers a maximum power density of 0.89 W m −2 at a load resistance of 10 MΩ. The fluorination enhanced triboelectrification and the surface superhydrophobicity induced humidity-stability make the FPS-TENG a sustainable power source for the wearable bioelectronics in the era of Internet of Things. • Moisture-resistant triboelectric nanogenerator was developed. • Fluorination treatment effectively improves hydrophobicity. • Quasi-bulk-phase functionalization enables super durability. • Parametric experimental results yield optimal material design.

Investigation of cracking behaviors in divertor armor-blocks under cyclic loading

Optimal design of materials and configurations is necessary to assure intended functions of divertor module against nuclear fusion plasma. Relevant activities performed not only diverse numerical analyses of armor-blocks and structures but also material property tests of specimens and limited experiments of mock-ups under harsh environments. As recent studies reported remarkable cracks in the tungsten-armored multiple-block subjected to cyclic loading, this research is intended to investigate cracking behaviors and to establish a promising numerical approach for engineering application. First of all, three sets of traction-separation law(TSL) parameters for a tungsten material were assumed based on reference data under a severe heat flux of 20 MW/m2. Extended finite element analyses were carried out mainly for the mock-up that consists of five blocks to determine a proper set of TSL parameters by comparing with experimental observation. Subsequently, parametric analyses were conducted to examine further realistic situations by changing the number of blocks and joining restraints. As results of analyses, crack propagation directions and amounts as well as initiation locations were predicted in the simulated blocks. Different cracking behaviors were also evaluated in relation to the number of applied cycles followed by a discussion of key findings from the thermal fatigue and failure assessment standpoint.

A static/dynamic micromechanical model of graphene-reinforced polymer matrix nanocomposites with consideration of the nanoscale interphase

As a kind of potential excellent materials, polymer-based nanocomposites with nanoreinforcements have become increasingly attractive in recent years, especially the latest graphene reinforced polymer matrix nanocomposites in virtue of the distinctive extremely-large aspect ratio of graphene nanoplatelets (GNPs). In this paper, we propose a static/dynamic micromechanical model of graphene-reinforced polymer nanocomposites, with consideration of the nanoscale interfaces and random orientations of GNPs, to effectively predict their static and dynamic mechanical behavior. The nanoscale interfaces of GNPs are introduced into the micromechanical model as the third phase to reflect their key role in the shear-load transfer between graphene and the matrix. The elastic modulus of graphene used in the model has been corrected as an effective modulus, based on a micromechanical statistics analysis of randomly-distributed orientations of GNPs. The dynamic model of the nanocomposites is established on the basis of the static one, in which the rate effect is introduced through the matrix using an improved Maxwell element method. Finally, the proposed static and dynamic models are applied in GNP/Epoxy nanocomposites to obtain the reasonable predictions of their viscoelastic behaviors, and have been well validated by experimental data. So, this work should be able to provide a micromechanical theoretical basis to the optimal material design of graphene reinforced polymer nanocomposites for better performance in engineering applications.

Internal polarization process revelation of electrochemical impedance spectroscopy of proton exchange membrane fuel cell by an impedance dimension model and distribution of relaxation times

• A 2D physics-based impedance model is built to study impedance spectroscopy. • Polarization processes are identified by the distribution of relaxation times. • An independent impedance analysis by configuring system dynamics is utilized. • An inductive loop at low-frequency is observed in simulated impedance spectroscopy. • Inductive loop strongly depends on membrane water gradient and net diffusion flux. Electrochemical impedance spectroscopy (EIS) is a widespread non-invasive technology applied in proton exchange membrane (PEM) fuel cell characterization and diagnosis. In an experimental impedance plot, multi-arc nature displays or some arcs may merge. To fully reveal the internal polarization process inside the fuel cell, a two-dimension impedance model involving dominant transient behaviors such as electrochemical reaction, reactant transfer, and membrane water transfer is used for impedance spectroscopy calculation. An independent impedance analysis methodology by configuring system dynamics is utilized to demonstrate the physical nature of different frequency features. Meanwhile, a model-free approach to the distribution of relaxation times (DRT) helps probe the characteristics of different time constants in the impedance spectroscopy. A systematic dynamic configuration and model parameter independence analysis supports the assignment that polarization processes in the impedance spectroscopy from ultra-high frequency to ultra-low frequency correspond to anode chemical reaction, proton transfer inside the ionomer of the cathode, charge transfer attributed oxygen reduction reaction, oxygen transfer in the cathode, and dissolved water transfer. In detail, the results indicate that membrane water content affects the conductivity of the polymer, in turn determining proton transfer and charge transfer loss. Besides, oxygen molar concentration along the channel strongly influences whole mass transfer loss, followed by concentration in the gas diffusion layer. The inductive loop caused by membrane hydration is mainly determined by the gradient and net diffusion flux of the dissolved water across the membrane. These works provide a deep insight into impedance behaviors and help material optimization and controller design.

Tuning Thermal Conductivity in Si Nanowires with Patterned StructuresSupported by the National Natural Science Foundation of China (Grant No. 11875047).

Tuning the thermal conductivity of silicon nanowires (Si-NWs) is essential for realization of future thermoelectric devices. The corresponding management of thermal transport is strongly related to the scattering of phonons, which are the primary heat carriers in Si-NWs. Using the molecular dynamics method, we find that the scattering of phonons from internal body defects is stronger than that from surface structures in the low-porosity range. Based on our simulations, we propose the concept of an exponential decay in thermal conductivity with porosity, specifically in the low-porosity range. In contrast, the thermal conductivity of Si-NWs with a higher porosity approaches the amorphous limit, and is insensitive to specific phonon scattering processes. Our findings contribute to a better understanding of the tuning of thermal conductivity in Si-NWs by means of patterned nanostructures, and may provide valuable insights into the optimal design of one-dimensional thermoelectric materials.