Bottom-up Design Strategy Research Articles

Computational investigation of the effects of polymer grafting on the effective interaction between silica nanoparticles in water.

Understanding and control of the effective interaction between nanoscale building blocks (colloids or nanoparticles) dispersed in a solvent is an important prerequisite for the development of bottom-up design strategies for soft functional materials. Here, we have employed all-atom molecular dynamics simulations to investigate the impact of polymer grafting on the solvent-mediated effective interaction between the silica nanoparticles (Si-NPs) in water, and in turn, on its bulk structural and thermodynamic properties. We found that the nature of the short grafting polymers [characterized by their interaction with water (hydrophobicity or hydrophilicity) and molecular weight] has a profound effect on the range and strength of the effective interaction between the Si-NPs. The hydrophobic polymer [such as polyethylene (PE)]-grafting of Si-NP gives rise to a more attractive interaction between the Si-NPs compared to the hydrophilic polymer [such as polyethylene glycol (PEG)] and non-grafted cases. This study further provides fundamental insights into the molecular origin of the observed behavior of the effective pair interactions between the grafted Si-NPs. For PE-grafted Si-NPs, the confined water (water inside the cavity formed by a pair of Si-NPs) undergoes a partial dewetting transition on approaching below a critical inter-particle separation leading to a stronger attractive interaction. Furthermore, we report that the effective attraction between the PE-grafted Si-NPs can be reliably controlled by changing the grafting PE density. We have also investigated the bulk structural and thermodynamic behavior of the coarse-grained Si-NP system where the particles interact via effective interaction in the absence of water. We believe that the insights gained from this work are important prerequisites for formulating rational bottom-up design strategies for functional materials where nano- (or, colloidal) particles are the building blocks.

Reconfigurable matrix multiplier with on-site reinforcement learning.

Matrix multiplication is a fundamental building block for modern information processing and artificial intelligence algorithms. Photonics-based matrix multipliers have recently attracted much attention due to their advantages of low energy and ultrafast speed. Conventionally, achieving matrix multiplication relies on bulky Fourier optical components, and the functionalities are unchangeable once the design is determined. Furthermore, the bottom-up design strategy cannot easily be generalized into concrete and practical guidelines. Here, we introduce a reconfigurable matrix multiplier driven by on-site reinforcement learning. The constituent transmissive metasurfaces incorporating varactor diodes serve as tunable dielectrics based on the effective medium theory. We validate the viability of tunable dielectrics and demonstrate the performance of matrix customization. This work represents a new avenue in realizing reconfigurable photonic matrix multipliers for on-site applications.

Construction of Co3O4/CeO2 heterostructure nanoflowers facilitates deployment of oxygen defects to enhance the oxygen evolution kinetics

The bottom-up design strategy can more rationally optimize the composition and structure of the materials to impart excellent oxygen evolution reaction (OER) performance. Heterostructures can modulate electronic behavior through interface construction to optimize materials properties for superior OER performance. In this paper, we created abundant Co3O4/CeO2 phase interfaces to tune the grain size, the electronic configuration of cobalt sites, and the content of oxygen defects in Co3O4, which increases the number of active sites, enhances the electronic conductivity of the material, and optimized the adsorption energy for reaction intermediates. Moreover, the assembly of nanograins into nanoflowers with a three-dimensional hierarchical pore structure can provide more effective active sites, abundant pores and channels for mass transport, and discrete cavities for in-depth reactions of intermediates. The construction of Co3O4/CeO2 heterostructure nanoflowers (CoCe HNFs) contributes to the excellent OER performance of the catalyst.

Microfluidic switches driven by mechanically guided multistable buckling

Reconfigurable microfluidic devices are of growing interest in microfluidic chemical analysis and separation system, since their channel network topology can be adjusted conveniently, in a dynamic and reversible manner. Such reconfigurability is important for a variety of engineering applications. Compared with the existing reconfiguration methods, mechanically-controlled reconfiguration approach is promising, because of the applicability to diverse materials, without potential negative effects to the electromagnetic devices during operation. In this work, we introduce a reconfiguration strategy that exploits multistable structure to control the flow in microchannels. Here, the configuration of a cross-shaped device is reversibly altered by the loading/releasing sequence of the elastomer platform beneath, thereby changing the open/close status of the channels inside the device. The cross-sectional geometry of the channel is systematically studied to reveal the underlying physics. Quantitative experimental and FEA results provide design guidelines of the microfluidic device. Through a bottom-up design strategy, a single reconfigurable switch device can be repeated to form a switch device array, capable of controlling multiple channels. A demonstration of a 3x1 switch array illustrates the utility of these ideas.

Computing With Networks of Chemical Oscillators and its Application for Schizophrenia Diagnosis.

Chemical reactions are responsible for information processing in living organisms, yet biomimetic computers are still at the early stage of development. The bottom-up design strategy commonly used to construct semiconductor information processing devices is not efficient for chemical computers because the lifetime of chemical logic gates is usually limited to hours. It has been demonstrated that chemical media can efficiently perform a specific function like labyrinth search or image processing if the medium operates in parallel. However, the number of parallel algorithms for chemical computers is very limited. Here we discuss top-down design of such algorithms for a network of chemical oscillators that are coupled by the exchange of reaction activators. The output information is extracted from the number of excitations observed on a selected oscillator. In our model of a computing network, we assume that there is an external factor that can suppress oscillations. This factor can be applied to control the nodes and introduce input information for processing by a network. We consider the relationship between the number of oscillation nodes and the network accuracy. Our analysis is based on computer simulations for a network of oscillators described by the Oregonator model of a chemical oscillator. As the example problem that can be solved with an oscillator network, we consider schizophrenia diagnosis on the basis of EEG signals recorded using electrodes located at the patient’s scalp. We demonstrated that a network formed of interacting chemical oscillators can process recorded signals and help to diagnose a patient. The parameters of considered networks were optimized using an evolutionary algorithm to achieve the best results on a small training dataset of EEG signals recorded from 45 ill and 39 healthy patients. For the optimized networks, we obtained over 82% accuracy of schizophrenia detection on the training dataset. The diagnostic accuracy can be increased to almost 87% if the majority rule is applied to answers of three networks with different number of nodes.

A bottom-up design strategy for controllable self-assembly based on the isotropic double-well potential.

Controllable self-assembly of particles or atoms is still challenging in the synthesis of materials with desirable properties that are highly relevant to the microscopic structures determined by the interparticle interactions. To gain insight into how the interactions affect the self-assembly, we designed various kinds of isotropic double-well potentials and simulated the motion of the particles. By controlling the depth and location of the potential wells and the height of the barriers, we studied their effects on the aggregation structures and the related microscopic kinetic processes. We identified five aggregation patterns at different temperatures and eight kinds of crystals, including Frank-Kasper phases, and observed the expansion or contraction of crystals. We found that the system usually stays in a sparse configuration at very low or very high temperatures. The particles typically assemble into a loosely packed cluster at medium temperatures and then deplete into a tightly packed state with a specific pattern. These phenomena can be explained from the perspective of energy. In contrast, very few structures could be obtained for the system guided by a single-well potential under the same simulation conditions. Thus, the interparticle interactions driven by the double-well potential greatly enrich the possible packing morphology of the system. The information obtained from this work helps us to understand how to achieve a specific self-assembled architecture through a reasonable selection of materials.

Online Newspaper Clustering in Aceh using the Agglomerative Hierarchical Clustering Method

The rapid progress in the field of information technology, especially the internet, has given birth to a lot of information. The ease of publishing an article on a website causes an explosion of news pages which will certainly confuse readers. The diversity and the increasing number of news articles make it increasingly difficult for internet users to find news and large piles of news data on online newspaper sites in Aceh. The grouping of text documents is needed to classify news in online newspapers in Aceh based on the content contained in news articles. In this study, the process of grouping online news in Aceh was tried using the Agglomerative Hierarchical Clustering method. News is grouped with a Bottom-Up design strategy that starts with placing each object as a cluster then combined into a larger cluster based on the similarity of keywords in each news, then the cluster results are compared and put into each news category. The research design was carried out in a structured manner using data flow diagrams in forming the research framework. The study was conducted by taking online news text data on 10 online news websites in Aceh from July 2016 to March 2017 with 1000 randomly generated documents. The process of crawling news data is done using a php script which will only take text files from the news on the website. News grouping is done based on religion, politics, law, sports, tourism, education, culture, economy and technology. The results of the grouping performance of the Agglomerative Hierarchical Clustering method in this study have an average accuracy of 89.84%.

Biosynthesis of Diverse Type II Polyketide Core Structures in Streptomyces coelicolor M1152.

Synthetic biology-based approaches have been employed to generate advanced natural product (NP) pathway intermediates to overcome obstacles in NP drug discovery and production. Type II polyketides (PK-IIs) comprise a major subclass of NPs that provide attractive structures for antimicrobial and anticancer drug development. Herein, we have assembled five biosynthetic pathways using a generalized operon design strategy in Streptomyces coelicolor M1152 to allow comparative analysis of metabolite production in an improved heterologous host. The work resulted in production of four distinct PK-II core structures, namely benzoisochromanequinone, angucycline, tetracenomycin, and pentangular compounds, which serve as precursors to diverse pharmaceutically important NPs. Our bottom-up design strategy provided evidence that the biosynthetic pathway of BE-7585A proceeds via an angucycline core structure, instead of rearrangement of an anthracycline aglycone, and led to the discovery of a novel 26-carbon pentangular polyketide. The synthetic biology platform presented here provides an opportunity for further controlled production of diverse PK-IIs in a heterologous host.

Design of one-dimensional organic semiconductors with high intrinsic electron mobilities: lessons from computation

A bottom-up design strategy for one-dimensional organic semiconductors with high intrinsic electron mobilities is proposed.

Geometrically reconfigurable 3D mesostructures and electromagnetic devices through a rational bottom-up design strategy.

Microelectronic devices with reconfigurable three-dimensional (3D) microarchitecture that can be repetitively switched among different geometrical and/or working states have promising applications in widespread areas. Traditional approaches usually rely on stimulated deformations of active materials under external electric/magnetic fields, which could potentially introduce parasitic side effects and lower device performances. Development of a rational strategy that allows access to high-performance 3D microdevices with multiple stable geometric configurations remains challenging. We introduce a mechanically guided scheme to build geometrically reconfigurable 3D mesostructures through a bottom-up design strategy based on a class of elementary reconfigurable structures with the simplest ribbon geometries. Quantitative mechanics modeling of the structural reconfigurability allows for the development of phase diagrams and design maps. Demonstrations of ~30 reconfigurable mesostructures with diverse geometric topologies and characteristic dimensions illustrate the versatile applicability. The multimode nature enables customized distinct beamforming and discrete beam scanning using a single antenna capable of on-demand reconfiguration.

Inverse modeling for fast design optimization of small-size rat-race couplers incorporating compact cells

In the paper, a framework for computationally-efficient design optimization of compact rat-race couplers (RRCs) is discussed. A class of hybrid RRCs with variable operating conditions is investigated, whose size reduction is obtained by replacing ordinary transmission lines with compact microstrip resonant cells (CMRCs). Our approach employs a bottom-up design strategy leading to the development of compact RRCs through rapid design optimization of its building blocks and a subsequent fine tuning to account for parasitic cross-coupling effects. The fundamental component of the proposed method is an inverse CMRC surrogate model, covering a wide range of cell electrical parameters, and enabling a convenient adjustment of coupler bandwidth. Having the surrogate model established, it is possible to produce close-to-optimum CMRC dimensions at a negligible computational cost. The subsequent correction step requires only up to two electromagnetic simulations of the CMRC. The proposed method is demonstrated by designing an RRC for several operational bandwidths. Experimental results are also provided.

Design of a synthetic yeast genome.

We describe complete design of a synthetic eukaryotic genome, Sc2.0, a highly modified Saccharomyces cerevisiae genome reduced in size by nearly 8%, with 1.1 megabases of the synthetic genome deleted, inserted, or altered. Sc2.0 chromosome design was implemented with BioStudio, an open-source framework developed for eukaryotic genome design, which coordinates design modifications from nucleotide to genome scales and enforces version control to systematically track edits. To achieve complete Sc2.0 genome synthesis, individual synthetic chromosomes built by Sc2.0 Consortium teams around the world will be consolidated into a single strain by "endoreduplication intercross." Chemically synthesized genomes like Sc2.0 are fully customizable and allow experimentalists to ask otherwise intractable questions about chromosome structure, function, and evolution with a bottom-up design strategy.

How New Advancements Enable a Position Change in the Science of Magnesium Batteries

Driven by the need to access higher energy densities beyond those offered by Li-ion batteries, rechargeable Mg batteries have been receiving increased interests. Although Mg metal is not competitive with Li metal on both specific capacity (2205 mAh g-1 vs. 3862 mAh g-1 for lithium) and redox potential levels (-2.3 V compared to -3.0 V for Li vs. NHE), it was found to be non-dendritic. In addition, Mg metal has a high volumetric capacity (3833 vs. 2046 mAh cm-3 for Li), and offers an opportunity for battery cost reductions owing its abundance in the earth crust (5th most abundant element). However, several technical challenges that hamper realizing practical rechargeable Mg batteries are currently present. For example, the absence of robust and practical high voltage/high capacity cathodes currently limits the energy density which could be harnessed using these systems.[1] Another major hurdle is caused by the type of electrolytes currently used in Mg batteries. At its very core, is the limitation induced by the incompatibility of Mg metal with simple ionic salts and non-ethereal solvents. This has limited the working electrolytes options to a handful of complex halogen systems which are corrosive. We have been pioneering the development of a new family of electrolytes based on a novel bottom-up design strategy to create highly performing simple type highly compatible Mg salts. Herein, we will explain our design concepts that guided the development of a new paradigm using boron-hydrogen salts and resulted in demonstrating the only ionic simple-type salts known to date that are highly compatible with Mg metal.[2,3] References [1] a) R. Mohtadi, F. Mizuno Beilstein J. Nanotechnol. 2014, 5, 1291–1311, b) H. D. Yoo, I. Shterenberg, Y. Gofer, G. Gershinsky, N. Pour, D. Aurbach, Energy Environ. Sci. 2013, 6, 2265-2279. [2] a) R. Mohtadi, M. Matsui, T. S. Arthur, S.-J. Hwang, Angew. Chem. Int. Ed. 2012, 51, 9780 –9783; b) T. J. Carter, R. Mohtadi, T. S. Arthur, F. Mizuno, R. Zhang, S. Shirai, J. W. Kampf, Angew. Chem. Int. Ed. 2014, 53, 3173-3177, c) O. Tutusaus, R. Mohtadi, ChemElectroChem. 2014DOI: 10.1002/celc.201402207; [3] O. Tutusaus, R. Mohtadi, T. Arthur. F. Mizuno, Angew. Chem. Int. Ed. 2015, DOI: 10.1002/anie.201412202R3.

Patchy from the bottom up

The realization of a self-assembled kagome lattice from colloids with attractive hydrophobic patches offers a simple but powerful example of the bottom-up design strategy.

Improving system performance through an integrated design approach

Product designers typically use existing concept solutions in their day-to-day business and development generally takes place via incremental improvements leaving little room for innovation. This study aims to improve system performance by an integrated design approach. The approach encompasses three phases: technology assimilation, technology insertion and technology integration, following a sequence of modular, top-down and bottom-up design strategies. The goal is to find opportunities to integrate structure and functionality early in the conceptual stage to increase production efficiency and reduce cost. This paper describes the integrated design approach; also, practical results are presented where the developed approach was successfully applied.

Mixed-Signal Architectures for High-Efficiency and Low-Distortion Digital Audio Processing and Power Amplification

The paper addresses the algorithmic and architectural design of digital input power audio amplifiers. A modelling platform, based on a meet-in-the-middle approach between top-down and bottom-up design strategies, allows a fast but still accurate exploration of the mixed-signal design space. Different amplifier architectures are configured and compared to find optimal trade-offs among different cost-functions: low distortion, high efficiency, low circuit complexity and low sensitivity to parameter changes. A novel amplifier architecture is derived; its prototype implements digital processing IP macrocells (oversampler, interpolating filter, PWM cross-point deriver, noise shaper, multilevel PWM modulator, dead time compensator) on a single low-complexity FPGA while off-chip components are used only for the power output stage (LC filter and power MOS bridge); no heatsink is required. The resulting digital input amplifier features a power efficiency higher than 90% and a total harmonic distortion down to 0.13% at power levels of tens of Watts. Discussions towards the full-silicon integration of the mixed-signal amplifier in embedded devices, using BCD technology and targeting power levels of few Watts, are also reported.

Security from the bottom-up

This paper explores the push toward more bottom-up design strategies for the creation of web applications, a push which has produced a strengthening of code auditing, training, and education. Par...

Modelling an ongoing design process utilizing top-down and bottom-up design strategies

The product design process plays a central role in ensuring that new products are realized with improved quality, in a short lead-time and with costs kept to a minimum. It is identified that making decisions dynamically on how the design process should proceed is not trivial. A computational environment that aids dynamic decision making on the design process would be useful in ensuring successful design of new products. A key component of analysing and making decisions on the progression of the design process is a model that captures an ongoing design process. In this paper, an approach to modelling an ongoing design process is proposed based on the use of design nodes. The approach allows an ongoing design process to be modelled that facilitates dynamic decision making on how the design process should progress and accounts for the state of the design problem. The approach allows top-down and bottom-up design strategies to be modelled.

Cross-Layer Design for Power Efficiency and QoS Provisioning in Multi-Hop Wireless Networks

In recent years, it has become common consensus that independent consideration of communication layers often turns out to be inadequate in terms of providing the desired quality of service (QoS) and power efficiency in wireless networks. The need for a synergistic, cross-layer design framework has already been identified. In that respect, our work constitutes an important step towards a better understanding of the cross-layer paradigm by simultaneously targeting both the power efficiency and the end-to-end QoS in multi-hop wireless networks. More specifically, we address the joint problem of power control and scheduling with the objective of minimizing the total transmit power subject to the end-to-end bandwidth guarantees and the bit error rate constraints of each communication session. After identifying the inherent difficulty of the problem, we propose two classes of heuristic algorithms that rely on graph theory principles as well as on derived metrics such as effective interference. The first heuristic follows a top-down design strategy by solving the schedule feasibility problem as the initial step and then targeting the total power efficiency. On the other hand, the second heuristic follows a bottom-up approach that schedules one wireless link at a time by greedily filling up the available time slots. The simulation results reveal valuable insights about the performance of each strategy. The top-down design strategy turns out to address power efficiency issues better, whereas the bottom-up design strategy with a properly selected cost function for link scheduling shows better performance in finding a feasible solution, namely one that satisfies both the QoS and the transmit power constraints. Our results also illustrate the impact of routing decisions on the feasibility and the power efficiency of multi-hop wireless networks through employing different routing criteria in the experiments