Measuring Lattice Strain in Three Dimensions through Electron Microscopy.

The three-dimensional (3D) atomic structure of nanomaterials, including strain, is crucial to understand their properties. Here, we investigate lattice strain in Au nanodecahedra using electron tomography. Although different electron tomography techniques enabled 3D characterizations of nanostructures at the atomic level, a reliable determination of lattice strain is not straightforward. We therefore propose a novel model-based approach from which atomic coordinates are measured. Our findings demonstrate the importance of investigating lattice strain in 3D.

Mechanical Performance Comparison of Sandwich Panels with Graded Lattice and Honeycomb Cores.

The design of graded and multifunctional lattice cores is driven by the increasing demand for high-performance components in lightweight engineering. This trend benefits from significant achievements in additive manufacturing, where the lattice core and the face sheets are fabricated simultaneously in a single print job. This work systematically compares the mechanical performance of sandwich panels comprising various graded lattice cores subjected to concentrated loads. In addition to graded lattice cores, uniform lattices and conventional honeycomb cores are analyzed. To obtain an optimized graded lattice core, a fully stressed design method is applied. Stresses and displacements are determined using a linear elastic analytical model that allows grading the core properties in a layerwise manner through the core thickness. The analysis indicates the superior performance of graded lattice cores compared to homogeneous lattice cores. However, conventional honeycombs outperform graded lattice cores in terms of load-to-weight ratio and stiffness-to-weight ratio. This study provides valuable insights for the design of lattice core sandwich panels and the advantages of several design approaches.

Effect of Architected Structural Members on the Viscoelastic Response of 3D Printed Simple Cubic Lattice Structures.

Three-dimensional printed polymeric lattice structures have recently gained interests in several engineering applications owing to their excellent properties such as low-density, energy absorption, strength-to-weight ratio, and damping performance. Three-dimensional (3D) lattice structure properties are governed by the topology of the microstructure and the base material that can be tailored to meet the application requirement. In this study, the effect of architected structural member geometry and base material on the viscoelastic response of 3D printed lattice structure has been investigated. The simple cubic lattice structures based on plate-, truss-, and shell-type structural members were used to describe the topology of the cellular solid. The proposed lattice structures were fabricated with two materials, i.e., PLA and ABS using the material extrusion (MEX) process. The quasi-static compression response of lattice structures was investigated, and mechanical properties were obtained. Then, the creep, relaxation and cyclic viscoelastic response of the lattice structure were characterized. Both material and topologies were observed to affect the mechanical properties and time-dependent behavior of lattice structure. Plate-based lattices were found to possess highest stiffness, while the highest viscoelastic behavior belongs to shell-based lattices. Among the studied lattice structures, we found that the plate-lattice is the best candidate to use as a creep-resistant LS and shell-based lattice is ideal for damping applications under quasi-static loading conditions. The proposed analysis approach is a step forward toward understanding the viscoelastic tolerance design of lattice structures.

Protein Folding Prediction in a Cubic Lattice in Hydrophobic-Polar Model.

The tertiary structure of the proteins determines their functions. Therefore, the predicting of protein's tertiary structure, based on the primary amino acid sequence from long time, is the most important and challenging subject in biochemistry, molecular biology, and biophysics. One of the most popular protein structure prediction methods, called Hydrophobic-Polar (HP) model, is based on the observation that in polar environment hydrophobic amino acids are in the core of the molecule-in contact between them and more polar amino acids are in contact with the polar environment. In this study, we present a new mixed integer programming formulation, exact algorithm, and two heuristic algorithms to solve the protein folding problem stated as a combinatorial optimization problem in a simple cubic lattice. The results from computational runs on a set of benchmarks are favorably compared to known algorithms for solving the 3D lattice HP model as genetic algorithms, ant colony optimization algorithm, and Monte Carlo algorithm.

Hybrid method to solve HP model on 3D lattice and to probe protein stability upon amino acid mutations.

BACKGROUND: Predicting protein structure from amino acid sequence is a prominent problem in computational biology. The long range interactions (or non-local interactions) are known as the main source of complexity for protein folding and dynamics and play the dominant role in the compact architecture. Some simple but exact model, such as HP model, captures the pain point for this difficult problem and has important implications to understand the mapping between protein sequence and structure. RESULTS: In this paper, we formulate the biological problem into optimization model to study the hydrophobic-hydrophilic model on 3D square lattice. This is a combinatorial optimization problem and known as NP-hard. Particle swarm optimization is utilized as the heuristic framework to solve the hard problem. To avoid premature in computation, we incorporated the Tabu search strategy. In addition, a pulling strategy was designed to accelerate the convergence of algorithm based on the characteristic of native protein structure. Together a novel hybrid method combining particle swarm optimization, Tabu strategy, and pulling strategy can fold the amino acid sequences on 3D square lattice efficiently. Promising results are reported in several examples by comparing with existing methods. This allows us to use this tool to study the protein stability upon amino acid mutation on 3D lattice. In particular, we evaluate the effect of single amino acid mutation and double amino acids mutation via 3D HP lattice model and some useful insights are derived. CONCLUSION: We propose a novel hybrid method to combine several heuristic strategies to study HP model on 3D lattice. The results indicate that our hybrid method can predict protein structure more accurately and efficiently. Furthermore, it serves as a useful tools to probe the protein stability on 3D lattice and provides some biological insights.

3D printed lattices as an activation and expansion platform for T cell therapy.

One of the most significant hurdles to the affordable, accessible delivery of cell therapy is the cost and difficulty of expanding cells to clinically relevant numbers. Immunotherapy to prevent autoimmune disease, tolerate organ transplants or target cancer critically relies on the expansion of specialized T cell populations. We have designed 3D-printed cell culture lattices with highly organized micron-scale architectures, functionalized via plasma polymerization to bind monoclonal antibodies that trigger cell proliferation. This 3D technology platform facilitate the expansion of therapeutic human T cell subsets, including regulatory, effector, and cytotoxic T cells while maintaining the correct phenotype. Lentiviral gene delivery to T cells is enhanced in the presence of the lattices. Incorporation of the lattice format into existing cell culture vessels such as the G-Rex system is feasible. This cell expansion platform is user-friendly and expedites cell recovery and scale-up, making it ideal for translating T cell therapies from bench to bedside.

Glial scar size, inhibitor concentration, and growth of regenerating axons after spinal cord transection.

A mathematical model has been formulated in accordance with cell chemotaxis and relevant experimental data. A three-dimensional lattice Boltzmann method was used for numerical simulation. The present study observed the effects of glial scar size and inhibitor concentration on regenerative axonal growth following spinal cord transection. The simulation test comprised two parts: (1) when release rates of growth inhibitor and promoter were constant, the effects of glial scar size on axonal growth rate were analyzed, and concentrations of inhibitor and promoters located at the moving growth cones were recorded. (2) When the glial scar size was constant, the effects of inhibitor and promoter release rates on axonal growth rate were analyzed, and inhibitor and promoter concentrations at the moving growth cones were recorded. Results demonstrated that (1) a larger glial scar and a higher release rate of inhibitor resulted in a reduced axonal growth rate. (2) The axonal growth rate depended on the ratio of inhibitor to promoter concentrations at the growth cones. When the average ratio was < 1.5, regenerating axons were able to grow and successfully contact target cells.