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At least 235 records · Page 13

SUMC reconfigurable micro-assembler

The development of a reconfigurable micro-assembler to provide the micro-programmer the capability to specify micro-instructions in concise, meaningful terms is discussed. The implementation plan for the development of the micro-assembler was predicted on the existing capabilities of the SUMC Reconfigurable Assembler. Utilizing the reconfigurable assembler as a base, new directives and existing directive modifications were implemented to provide the micro-assembly as a new capability of the reconfigurable assembler. The micro-assembler language allows the specification of all micro-instruction control field settings in one concise assembler source statement. The language appears very similar to a conventional machine instruction assembler language. The machine instruction assembler language has the characteristic of one operation specification per statement whereas, the micro-instruction assembler language allows multiple operations to be designated per statement.

Edwards, A. J.↗

Backward assembly planning with DFA analysis

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies is presented. The planning system analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc., that must occur during the assembly. Additionally, the planning handles nonreversible, as well as reversible, assembly tasks through backward assembly planning. In order to decrease the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Lee, Sukhan↗

Backward assembly planning with DFA analysis

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies, and analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans is presented. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc. that must occur during the assembly, and handles nonreversible as well as reversible assembly tasks through backward assembly planning. In order to increase the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Lee, Sukhan↗

Highly Efficient Single-Pot Scarless Golden Gate Assembly

We report that Golden Gate assembly is one of the most widely used DNA assembly methods due to its robustness and modularity. However, despite its popularity, the need for BsaI-free parts, the introduction of scars between junctions, as well as the lack of a comprehensive study on the linkers hinders its more widespread use. Here, we first developed a novel sequencing scheme to test the efficiency and specificity of 96 linkers of 4-bp length and experimentally verified these linkers and their effects on Golden Gate assembly efficiency and specificity. We then used this sequencing data to generate 200 distinct linker sets that can be used by the community to perform efficient Golden Gate assemblies of different sizes and complexity. We also present a single-pot scarless Golden Gate assembly and BsaI removal scheme and its accompanying assembly design software to perform point mutations and Golden Gate assembly. Finally, this assembly scheme enables scarless assembly without compromising efficiency by choosing optimized linkers near assembly junctions.

59 BASIC BIOLOGICAL SCIENCES↗

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.

59 BASIC BIOLOGICAL SCIENCES↗

Automated Multi-Robot Assembly of Compliance Optimized Structures

Autonomous assembly of large structures is one of the fundamental challenges on the way towards NASA’s objectives of deep space exploration. In this work, we propose an algorithmic framework to optimize the assembly process of a prescribed target structure by constraining the assembly effort as well as maintaining structural soundness throughout the process. This framework uses structural topology optimization with assembly effort metrics to generate checkpoints for robotic traversal algorithms. Assembly effort is quantified by the Wasserstein metric between consecutive structural configurations during the assembly process. The robotic assembly task is split into two subtasks, where we first optimize for a set of key frames, then perform reconfiguration between consecutive frames. Key frames are optimized by adopting topology optimization techniques to reduce assembly effort and maintain structural integrity during the assembly process, while reconfiguration between key frames is performed using a path planning algorithm with a minimum weight maximum matching approach on a bipartite graph. We employ a Crystalline robot model in which each structural element is capable of locomotion through the structure and locking into place with neighboring elements after reaching its destination. An example assembly of a two-dimensional cantilever beam under volume constraints and structural compliance considerations is presented to demonstrate the approach. Finally, we conclude by discussing possible future extensions to this work, including adoption of better metrics, extension to three-dimensional large-scale problems, and exacting finer control of structural integrity during the path-planning phase.

robotic assembly↗

Impact of Nanoparticle Size and Surface Chemistry on Peptoid Self-Assembly

Self-assembled organic nanomaterials can be generated by bottom-up assembly pathways where the structure is controlled by the organic sequence and altered using pH, temperature, and solvation. In contrast, self-assembled structures based on inorganic nanoparticles typically rely on physical packing and drying effects to achieve uniform superlattices. By combining these two chemistries to access inorganic–organic nanostructures, we aim to understand the key factors that govern the assembly pathway and structural outcomes in hybrid systems. In this work, we outline two assembly regimes between quantum dots (QDs) and reversibly binding peptoids. These regimes can be accessed by changing the solubility and size of the hybrid (peptoid-QD) monomer unit. The hybrid monomers are prepared via ligand exchange and assembled, and the resulting assemblies are studied using ex-situ transmission electron microscopy as a function of assembly time. In aqueous conditions, QDs were found to stabilize certain morphologies of peptoid intermediates and generate a final product consisting of multilayers of small peptoid sheets linked by QDs. The QDs were also seen to facilitate or inhibit assembly in organic solvents based on the relative hydrophobicity of the surface ligands, which ultimately dictated the solubility of the hybrid monomer unit. Increasing the size of the QDs led to large hybrid sheets with regions of highly ordered square-packed QDs. A second, smaller QD species can also be integrated to create binary hybrid lattices. Furthermore, these results create a set of design principles for controlling the structure and structural evolution of hybrid peptoid-QD assemblies and contribute to the predictive synthesis of complex hybrid matter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantification of Changes in Fill Tube Curvature During Target Assembly

National Ignition Facility (NIF) targets used for inertial confinement fusion (ICF) experiments are precision-engineered assemblies composed of more than 100 components carefully and precisely assembled with accuracies no larger than a few micrometers in most cases. When individual components deviate from these strict specifications during the assembly process, they can induce target failure. An integral component essential to ICF targets is the capsule-fill-tube assembly. This assembly involves bonding the capsule to a fused silica tube less than 5 μm in thickness, through which the tritium and deuterium (T 2 + D 2 ) fuel mixture is injected into the capsule prior to the NIF shot. The filling tube is bonded to a larger fused silica capillary, about 130 μm in outer diameter, which is coated with a polymeric layer on the order of a 10-μm thickness or less. Only tubes exhibiting a deflection equivalent to less than 1% of their total length from a perfectly straight line are suitable for assembly. Slight curvatures on the order of 1 mm over 10 cm can induce unwanted stresses, potentially causing capsule misalignment and resulting in clogging or leaks during the filling process. Despite manually qualitatively sorting each tube for straightness prior assembly, it has been found that the treatments the tubes undergo once attached to the capsule can alter their curvature. Filling tubes that initially satisfy straightness tolerances can undergo geometric deformation, resulting in curvature deviations exceeding 1% of their total length and thus failing to meet target assembly requirements. Here, in this study, we propose a metric to assess the degree of curvature of the filling tubes and to gauge their changes in curvature caused by the standard thermal processing methods employed in target assembly. In addition, we suggest alternatives to mitigate tube curvature, ensuring they conform to specifications following assembly in the final targets.

Materials science↗

Persistent memory as an effective alternative to random access memory in metagenome assembly

Abstract Background The assembly of metagenomes decomposes members of complex microbe communities and allows the characterization of these genomes without laborious cultivation or single-cell metagenomics. Metagenome assembly is a process that is memory intensive and time consuming. Multi-terabyte sequences can become too large to be assembled on a single computer node, and there is no reliable method to predict the memory requirement due to data-specific memory consumption pattern. Currently, out-of-memory (OOM) is one of the most prevalent factors that causes metagenome assembly failures. Results In this study, we explored the possibility of using Persistent Memory (PMem) as a less expensive substitute for dynamic random access memory (DRAM) to reduce OOM and increase the scalability of metagenome assemblers. We evaluated the execution time and memory usage of three popular metagenome assemblers (MetaSPAdes, MEGAHIT, and MetaHipMer2) in datasets up to one terabase. We found that PMem can enable metagenome assemblers on terabyte-sized datasets by partially or fully substituting DRAM. Depending on the configured DRAM/PMEM ratio, running metagenome assemblies with PMem can achieve a similar speed as DRAM, while in the worst case it showed a roughly two-fold slowdown. In addition, different assemblers displayed distinct memory/speed trade-offs in the same hardware/software environment. Conclusions We demonstrated that PMem is capable of expanding the capacity of DRAM to allow larger metagenome assembly with a potential tradeoff in speed. Because PMem can be used directly without any application-specific code modification, these findings are likely to be generalized to other memory-intensive bioinformatics applications.

59 BASIC BIOLOGICAL SCIENCES↗

Preserving Structurally Labile Peptide Nanosheets After Molecular Functionalization of the Self-Assembling Peptides

A significant challenge in creating supramolecular materials is that conjugating molecular functionalities to building blocks often results in dissociation or undesired morphological transformation of their assemblies. Here we present a facile strategy to preserve structurally labile peptide assemblies after molecular modification of the self-assembling peptides. Sheet-forming peptides are designed to afford a staggered alignment with the segments bearing chemical modification sites protruding from the sheet surfaces. The staggered assembly allows for simultaneous separation of attached molecules from each other and from the underlying assembly motifs. Strikingly, using PEGs as the external molecules, PEG 400 - and PEG 700 -peptide conjugates directly self-associate into nanosheets with the PEG chains localized on the sheet surfaces. In contrast, the sheet formation based on in-register lateral packing of peptides does not recur upon the peptide PEGylation. This strategy allows for fabrication of densely modified assemblies with a variety of molecules, as demonstrated using biotin (hydrophobic molecule), c(RGDfK) (cyclic pentapeptide), and nucleic acid aptamer (negatively charged ssDNA). The staggered co-assembly also enables extended tunability of the amount/density of surface molecules, as exemplified by screening ligand-appended assemblies for cell targeting. In conclusion, this study paves the way for functionalization of historically challenging fragile assemblies while maintaining their overall morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data from Highly Efficient Single-Pot Scarless Golden Gate Assembly

Golden Gate assembly is one of the most widely used DNA assembly methods due to its robustness and modularity. However, despite its popularity, the need for BsaI-free parts, the introduction of scars between junctions, as well as the lack of a comprehensive study on the linkers hinders its more widespread use. Here, we first developed a novel sequencing scheme to test the efficiency and specificity of 96 linkers of 4-bp length and experimentally verified these linkers and their effects on Golden Gate assembly efficiency and specificity. We then used this sequencing data to generate 200 distinct linker sets that can be used by the community to perform efficient Golden Gate assemblies of different sizes and complexity. We also present a single-pot scarless Golden Gate assembly and BsaI removal scheme and its accompanying assembly design software to perform point mutations and Golden Gate assembly. This assembly scheme enables scarless assembly without compromising efficiency by choosing optimized linkers near assembly junctions.

Conversion↗

Assembly planning based on subassembly extraction

A method is presented for the automatic determination of assembly partial orders from a liaison graph representation of an assembly through the extraction of preferred subassemblies. In particular, the authors show how to select a set of tentative subassemblies by decomposing a liaison graph into a set of subgraphs based on feasibility and difficulty of disassembly, how to evaluate each of the tentative subassemblies in terms of assembly cost using the subassembly selection indices, and how to construct a hierarchical partial order graph (HPOG) as an assembly plan. The method provides an approach to assembly planning by identifying spatial parallelism in assembly as a means of constructing temporal relationships among assembly operations and solves the problem of finding a cost-effective assembly plan in a flexible environment. A case study of the assembly planning of a mechanical assembly is presented.

Lee, Sukhan↗

In Space Assembled Telescope (ISAT) Study Preliminary Findings

“When is it advantageous to assemble telescopes in space rather than deploying them from launch vehicle fairings”? This question forms the crux of the objectives of a NASA study we have been conducting in collaboration with colleagues from different NASA centers, industry and academia. In this study, we have engaged a broad cross section of experts from the various fields of optics engineering, that is, telescope design and instrument design, structure and thermal engineering, robotics, launch system engineering, orbital mechanics, integration and testing, astrophysics, and NASA programmatics among others. Initial efforts began with a quick review of the current state of art of the component technologies that contribute towards an in-space assembled telescope. Then, leveraging the collective expertise of the diverse group of experts, we formulated a reference telescope design and attempted to develop a baseline approach to modularize the telescope into components amenable for robotic assembly. The group identified different trades associated with modularization and also developed a set of criteria to discern between the different options as revealed by the trades. Based on the modularization of the telescope, we will assess the impact of various launch vehicles, orbits for assembly and operation, robotic systems and operational approaches, and other related variables. From this, a concept to assemble the reference telescope in space from modular components will be developed. Based on this concept, and definition of the modules, we will develop a mission lifecycle plan for an assembled telescope over different phases of preliminary design, detailed design, assembly-test-and-integration, and in space operations. The mission lifecycle plan will be used to evaluate cost and risk implications of in-space assembly toward answering our fundamental question of the advantages, if any, of assembling a telescope in space as compared to self-deployment. In this paper, we summarize the objectives of the study, a review of the status of the underlying component technologies, a description of the methodology, including three different multi-day technical interchange meetings (TIMs), summary of findings from the TIMs and other related activities. In addition, a detailed description of the various factors that impact in-space assembly, their interplay and criteria for discerning among them, a preliminary description of the life cycle plan, including the test and integration plan, and initial observations on cost and risk implications will be included in the paper.

Mukherjee, Rudranarayan↗

Lyotropic Liquid Crystal Mediated Assembly of Donor Polymers Enhances Efficiency and Stability of Blade-Coated Organic Solar Cells

Conjugated polymers can undergo complex, concentration-dependent self-assembly during solution processing, yet little is known about its impact on film morphology and device performance of organic solar cells. Herein, lyotropic liquid crystal (LLC) mediated assembly across multiple conjugated polymers is reported, which generally gives rise to improved device performance of blade-coated non-fullerene bulk heterojunction solar cells. Using D18 as a model system, the formation mechanism of LLC is unveiled employing solution X-ray scattering and microscopic imaging tools: D18 first aggregates into semicrystalline nanofibers, then assemble into achiral nematic LLC which goes through symmetry breaking to yield a chiral twist-bent LLC. The assembly pathway is driven by increasing solution concentration – a common driving force during evaporative assembly relevant to scalable manufacturing. This assembly pathway can be largely modulated by coating regimes to give 1) lyotropic liquid crystalline assembly in the evaporation regime and 2) random fiber aggregation pathway in the Landau–Levich regime. The chiral liquid crystalline assembly pathway resulted in films with crystallinity 2.63 times that of films from the random fiber aggregation pathway, significantly enhancing the T80 lifetime by 50-fold. The generality of LLC-mediated assembly and enhanced device performance is further validated using polythiophene and quinoxaline-based donor polymers.

14 SOLAR ENERGY↗

Efficient analysis of small-angle scattering curves for large biomolecular assemblies using Monte Carlo methods

Structure elucidation from small-angle scattering curves of large biomolecular assemblies is notoriously challenging. This is because the simulation of high-resolution features in the structure of large macromolecular assemblies, such as de novo protein assemblies, is computationally demanding when it needs to cover a broad range of length scales. Conventional methods, such as the numerical approximation to the Debye equation or the use of spherical harmonics, do not scale well as the size of the assembly increases, which limits their application to small structures (e.g. individual proteins). This work explores the effectiveness of a Monte Carlo method to simulate and fit scattering curves for large biomolecular assemblies spanning over ranges covering atomic and molecular detail (e.g. spacing and orientation of proteins in an assembly) as well as large-scale (hundreds of nanometres) features. Owing to its speed and scalability, it can be combined with a fitting algorithm to extract structural features from experimental small-angle scattering curves in biomolecular assemblies that are otherwise intractable for interpretation. This work first demonstrates the effectiveness of the tool using experimental small-angle X-ray scattering (SAXS) data from tile-like proteins that assemble into 1D tube-like macromolecular structures. Here, the diameter distribution of tubes is extracted from SAXS fits, and this is quantitatively compared with distributions from electron microscopy. SAXS data are also obtained from 2D sheet-like protein assemblies, and the proposed method is used to quantify structural features such as the separation distance between protein building blocks and the flexing of the sheet. An open-source implementation of the methodology is provided for use in a broad range of biological systems involving multi-scale scattering analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ecological Processes Shaping Bulk Soil and Rhizosphere Microbiome Assembly in a Long-Term Amazon Forest-to-Agriculture Conversion

Forest-to-agriculture conversion has been identified as a major threat to soil biodiversity and soil processes resilience, although the consequences of long-term land use change to microbial community assembly and ecological processes have been often neglected. In this paper, we combined metagenomic approach with a large environmental dataset, to (i) identify the microbial assembly patterns and, (ii) to evaluate the ecological processes governing microbial assembly, in bulk soil and soybean rhizosphere, along a long-term forest-to-agriculture conversion chronosequence, in Eastern Amazon. We hypothesized that (i) microbial communities in bulk soil and rhizosphere have different assembly patterns and (ii) the weight of the four ecological processes governing assembly differs between bulk soil and rhizosphere and along the chronosequence in the same fraction. Community assembly in bulk soil fitted most the zero-sum multinomial (ZSM) neutral-based model, regardless of time. Low to intermediate dispersal was observed. Decreasing influence of abiotic factors was counterbalanced by increasing influence of biotic factors, as the chronosequence advanced. Undominated ecological processes of dispersal limitation and variable selection governing community assembly were observed in this soil fraction. For soybean rhizosphere, community assembly fitted most the lognormal niche-based model in all chronosequence areas. High dispersal and an increasing influence of abiotic factors coupled with a decreasing influence of biotic factors were found along the chronosequence. Thus, we found a dominant role of dispersal process governing microbial assembly with a secondary effect of homogeneous selection process, mainly driven by decreasing aluminum and increased cations saturation in soil solution, due to long-term no-till cropping. Together, our results indicate that long-term no-till lead community abundances in bulk soil to be in a transient and conditional state, while for soybean rhizosphere, community abundances reach a periodic and permanent distribution state. Dominant dispersal process in rhizosphere, coupled with homogeneous selection, brings evidences that soybean root system selects microbial taxa via trade-offs in order to keep functional resilience of soil processes.

59 BASIC BIOLOGICAL SCIENCES↗

Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides

Self-assembling peptides containing aromatic groups are an attractive target for bioelectronic materials design because of their ease of manufacture, biocompatibility, aqueous solubility, and chemical tunability. Microscopic understanding of the properties that control assembly is a prerequisite for rational design. In this work, we study the assembly of a family of DXXX-Π–XXXD oligopeptides possessing a π-conjugated core flanked by Asp-terminated tetrapeptide wings that display pH-triggered assembly into supramolecular aggregates. We develop a coarse-grained patchy particle model to conduct molecular dynamics simulations of the assembly of ten thousand oligopeptides over hundreds of nanometers and hundreds of microseconds. We study the effects of core and side chain interaction strength and side chain steric volume upon the morphology and kinetics of assembly. By characterizing the rate and fractal dimension of hierarchical nanoaggregate growth, we identify parameter regimes that favor rapid assembly of linear aggregates and map these regimes to sequence-defined candidate peptides for experimental synthesis and testing. Here, this work establishes new understanding of assembly on previously unexplored time and length scales and presents an efficient and extensible protocol for computational screening and prediction of promising peptide chemistries to assemble nanostructures with desirable optoelectronic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Rigidity on Molecular Self-Assembly

Rigid, cage-like molecules, like diamondoids, show unique self-assembly behavior, such as templating 1-D nanomaterial assembly via pathways that are typically blocked for such bulky substituents. We investigate molecular forces between diamondoids to explore why molecules with high structural rigidity exhibit these novel assembly pathways. The rigid nature of diamondoids significantly lowers configurational entropy, and we hypothesize that this influences molecular interaction forces. To test this concept, we calculated the distance-dependent impact of entropy on assembly using molecular dynamics simulations. To isolate pairwise entropic and enthalpic contributions to assembly, we considered pairs of molecules in a thermal bath, fixed at set intermolecular separations but otherwise allowed to freely move. By comparing diamondoids to linear alkanes, we draw out the impact of rigidity on the entropy and enthalpy of pairwise interactions. We find that linear alkanes actually exhibit stronger van der Waals interactions than diamondoids at contact, because the bulky structure of diamondoids induces larger net atomic separations. Yet, we also find that diamondoids pay lower entropic penalties when assembling into contact pairs. Thus, the cage-like shape of diamondoids introduces an enthalpic penalty at contact, but the penalty is counterbalanced by entropic effects. Investigating the distance dependence of entropic forces provides a mechanism to explore how rigidity influences molecular assembly. Our results show that low entropic penalties paid by diamondoids can explain the effectiveness of diamondoids in templating nanomaterial assembly. Hence, tuning molecular rigidity can be an effective strategy for controlling the assembly of functional materials, such as biomimetic surfaces and nanoscale materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗