Empirical Design Rules Research Articles

Engineering Anisotropy into Organized Nanoscale Matter.

Programming the organization of discrete building blocks into periodic and quasi-periodic arrays is challenging. Methods for organizing materials are particularly important at the nanoscale, where the time required for organization processes is practically manageable in experiments, and the resulting structures are of interest for applications spanning catalysis, optics, and plasmonics. While the assembly of isotropic nanoscale objects has been extensively studied and described by empirical design rules, recent synthetic advances have allowed anisotropy to be programmed into macroscopic assemblies made from nanoscale building blocks, opening new opportunities to engineer periodic materials and even quasicrystals with unnatural properties. In this review, we define guidelines for leveraging anisotropy of individual building blocks to direct the organization of nanoscale matter. First, the nature and spatial distribution of local interactions are considered and three design rules that guide particle organization are derived. Subsequently, recent examples from the literature are examined in the context of these design rules. Within the discussion of each rule, we delineate the examples according to the dimensionality (0D-3D) of the building blocks. Finally, we use geometric considerations to propose a general inverse design-based construction strategy that will enable the engineering of colloidal crystals with unprecedented structural control.

Deeper insights into flame retardancy of polymers by interpretable, quantifiable, yet accurate machine-learning model

Fire-safety polymer materials are essential in modern society such as electronics, aerospace, new energy. The quantification and prediction of flame retardancy, determined by the chemical composition and the burning process, has always been a bottleneck challenge. Previous empirical design rules and the existing models show large deviations for predicting flame retardancy and are often unexplainable. Here, this study proposes an interpretable model that can quantify the groups contribution of flame-retardancy and predict the flame retardance of intrinsically flame-retardant polymers. The machine learning model simultaneously considers the group structures and their flame-retardant mechanism in both the gas phase and condensed phase, achieving high prediction accuracy (89.8% for the training set and 83.8% for the testing set). It also quantifies the contribution values of various flame-retardant groups (halogen-containing structures, phosphorus-containing structures, phosphorus-nitrogen-containing structures, aromatic ring-containing structures, etc.) in both phases for the first time. The running script that integrates the model has also been open-sourced, providing an emerging strategy for transitioning flame-retardant research from empirical methods to scientific design.

Semi-supervised learning method incorporating structural optimization for shear-wall structure design using small and long-tailed datasets

Intelligent structural design based on machine learning represents a novel structural design paradigm and has received extensive attention in recent years. However, the performance of the machine learning models is heavily dependent on the quality and quantity of training data, as the underlying approaches are inherently data-driven. Well-recognized data issues ‒ particularly data insufficiencies and long-tailed data distributions ‒ have become critical impediments in this research area. To address these data issues, this study formulates a schematic structural design task as a semi-supervised learning problem. Specifically, a semi-supervised learning method using small, long-tailed datasets is proposed in which a structural optimization method is incorporated into a self-training framework. As a practical application of the proposed method, a shear-wall layout optimization procedure is devised, based on a two-stage evaluation strategy and the previously established empirical design rules. Results of the numerical experiments indicate that the proposed method can improve the design performance on the tail data by 11.6 % and reduce the performance difference between the head and tail data by 21.3 %, compared to the conventional supervised learning method. A typical case study shows that the shear-wall layout created by the proposed method can satisfactorily resemble that by design engineers whilst meeting key code-specified requirements.

On the model complexity of the air handling unit to investigate the energy efficiency of indoor swimming pool facilities

Building performance simulation is a powerful tool applied both in research and for building design including heating, ventilation, and air-conditioning systems. Several research studies have used this tool to investigate the potential of energy savings measures for swimming facilities. However, in these facilities the technical complexity is a considerable challenge in modelling since many complex phenomena occur in the various sub-systems. The building industry traditionally plans and design these complex buildings by heuristic rules of thumb, and these empirical design rules may lead to significant differences between real and predicted performance. Therefore, it's important to develop simplified models with acceptable accuracy for simulation-based design of swimming facilities. The scientific literature introduces different simplifications for the air handling unit modelling, but the impact of these simplifications is hardly analyzed. Therefore, the paper investigates the model complexity of the air handling unit in a Norwegian swimming facility by comparing a novel simplified model and a detailed model which serves as a digital replica of a real unit. The simplified decoupled model is found to have an acceptable accuracy for early-stage design, bearing in mind the overall uncertainty at this design stage. However, when carrying out a detailed investigation of a swimming facility, the detailed model should be applied, since this complex heuristic rule-based model, is taking into account phenomena like thermal-coupling effects between the swimming pool and the air handling unit and the control errors of the real internal controller. In conclusion, the paper derives useful guidelines for building performance simulation design of air handling unit, which is the main energy-intensive component in indoor swimming pool facilities.

Deep Mutational Scanning of an Oxygen-Independent Fluorescent Protein CreiLOV for Comprehensive Profiling of Mutational and Epistatic Effects.

Oxygen-independent, flavin mononucleotide-based fluorescent proteins (FbFPs) are promising alternatives to green fluorescent protein in anaerobic contexts. Deep mutational scanning performs systematic profiling of protein sequence-function relationships but has not been applied to FbFPs. Focusing on CreiLOV from Chlamydomonas reinhardtii, we created and analyzed two comprehensive mutant collections: (1) single-residue, site-saturation mutagenesis libraries covering all 118 residues; and (2) a full combinatorial metagenesis library among 20 mutations at 15 residues, where mutation and residue selection was based on single-site mutagenesis results. Notably, the second type of library is indispensable to study higher-order epistasis but underrepresented in the literature. Using optimized FACS-seq assays, 2,185 (>92.5%) out of 2,360 possible single-site mutants and 165,428 (>89.7%) out of 184,320 possible combinatorial mutants were reliably assigned with fitness values. We constructed statistical and machine-learning models to analyze the CreiLOV data set, enabling accurate fitness prediction of higher-order mutants using lower-order mutagenesis data. In addition, we successfully isolated CreiLOV variants with improved fluorescence quantum yield and thermostability. This work provides new empirical data and design rules to engineer combinatorial protein variants.

Fine Tuning the Pore Surface in Zirconium Metal–Organic Frameworks for Selective Ethane/Ethylene Separation

Ethylene is an important chemical feedstock for production of polymers and high-value organic chemicals, and yet its conventional purification process is plagued with high consumption of energy. Metal–organic frameworks (MOFs) provide a suitable adsorption platform for selective ethane/ethylene separation thanks to their structural diversity, tunable pore characteristics, designable pore sizes, and high pore volumes. Although there are empirical design rules like avoiding open metal sites and creating nonpolar pore surfaces for development of adsorptive MOFs, it is still challenging to design robust MOFs that can realize direct ethane-selective separation. Herein, we systematically designed and synthesized three Zr-MOFs based on the assembly of angular ligands and 12-connected Zr6 clusters that feature the pcu network structure. By changing the size and flexibility of the substituent on the angular ligand, we were able to prevent interpenetration and identified NPF-802, which exhibits good C2H6/C2H4 separation performance that is attributed to the bulky and inert tert-butyl groups of its carbazole ligand. This work provides insights for design of ligands of MOFs with suitable pore environments to address important and challenging gas separations.

A genome-scale CRISPR interference guide library enables comprehensive phenotypic profiling in yeast

BackgroundCRISPR/Cas9-mediated transcriptional interference (CRISPRi) enables programmable gene knock-down, yielding loss-of-function phenotypes for nearly any gene. Effective, inducible CRISPRi has been demonstrated in budding yeast, and genome-scale guide libraries enable systematic, genome-wide genetic analysis.ResultsWe present a comprehensive yeast CRISPRi library, based on empirical design rules, containing 10 distinct guides for most genes. Competitive growth after pooled transformation revealed strong fitness defects for most essential genes, verifying that the library provides comprehensive genome coverage. We used the relative growth defects caused by different guides targeting essential genes to further refine yeast CRISPRi design rules. In order to obtain more accurate and robust guide abundance measurements in pooled screens, we link guides with random nucleotide barcodes and carry out linear amplification by in vitro transcription.ConclusionsTaken together, we demonstrate a broadly useful platform for comprehensive, high-precision CRISPRi screening in yeast.

Materials genome project: Mining the ionic conductivity in oxide perovskites

We present in this work a strategy for predicting new oxide perovskites with the potential for achieving high ionic conductivity for applications as a solid oxide fuel cell (SOFC). We employ a throughout multivariate technique based the principal component analysis (PCA) and the partial least square methods (PLS) in order to identify empirical design rules (activation and migration energies) for stable ionic conductors. Among the 892 tested hypothetical oxide perovskites, which yet to be experimentally synthetized, ~150 compounds may exhibit an interesting potential as ionic conductors. These results may serve as a map for the design of perovskite-related solid electrolytes.

Nondestructive Prediction of the Buckling Load of Imperfect Shells

From soda cans to space rockets, thin-walled cylindrical shells are abundant, offering exceptional load carrying capacity at relatively low weight. However, the actual load at which any shell buckles and collapses is very sensitive to imperceptible defects and cannot be predicted, which challenges the of such structures. Consequently, probabilistic descriptions in terms of empirical design rules are used and designing reliable structures requires the use of conservative strength estimates. We introduce a nonlinear description where finite-amplitude perturbations trigger buckling. Drawing from the analogy between imperfect shells which buckle and imperfect pipe flow which becomes turbulent, we experimentally show that lateral probing of cylindrical shells reveals their strength nondestructively. A new ridge-tracking method is applied to commercial cylinders with a hole showing that when the location where buckling nucleates is known we can accurately predict the buckling load of each individual shell, within ±5%. Our study provides a new promising framework to understand shell buckling, and more generally, imperfection-sensitive instabilities.

Design Rules for Environmentally Friendly Medium Voltage Load Break Switches

Today's medium voltage distribution grids are often designed in a ring-structure with ring main units at their nodes. As these grids are mainly placed in urban areas, the space is limited and compact and reliable SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> filled switchgear is commonly used. However, SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> is the most potent greenhouse gas known and industry as well as decision makers are looking for possible replacements. In the course of substituting SF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sub> in ring main units, the load break switch is the critical component. In the switch, the gas has to serve as both, insulating and quenching medium. This work investigates the influence of the design of a polymeric nozzle on the thermal interruption capability and dielectric recovery of a medium voltage load break switch. The experiments are performed in a nitrogen/carbon dioxide atmosphere with nozzles made from polytetrafluorethylene. The main influencing factor on the interruption capability is the applied blowing pressure. Additionally, the nozzle throat length as well as the throat diameter show significant impacts on the interruption capability. From the experimental findings, empirical design rules are derived to estimate the thermal interruption capability of arbitrary nozzle designs for a fixed contact diameter.

Reconfigurable T-junction DNA Origami.

DNA self-assembly allows the construction of nanometre-scale structures and devices. Structures with thousands of unique components are routinely assembled in good yield. Experimental progress has been rapid, based largely on empirical design rules. Herein, we demonstrate a DNA origami technique designed as a model system with which to explore the mechanism of assembly. The origami fold is controlled through single-stranded loops embedded in a double-stranded DNA template and is programmed by a set of double-stranded linkers that specify pairwise interactions between loop sequences. Assembly is via T-junctions formed by hybridization of single-stranded overhangs on the linkers with the loops. The sequence of loops on the template and the set of interaction rules embodied in the linkers can be reconfigured with ease. We show that a set of just two interaction rules can be used to assemble simple T-junction origami motifs and that assembly can be performed at room temperature.

Reconfigurable T‐junction DNA Origami

AbstractDNA self‐assembly allows the construction of nanometre‐scale structures and devices. Structures with thousands of unique components are routinely assembled in good yield. Experimental progress has been rapid, based largely on empirical design rules. Herein, we demonstrate a DNA origami technique designed as a model system with which to explore the mechanism of assembly. The origami fold is controlled through single‐stranded loops embedded in a double‐stranded DNA template and is programmed by a set of double‐stranded linkers that specify pairwise interactions between loop sequences. Assembly is via T‐junctions formed by hybridization of single‐stranded overhangs on the linkers with the loops. The sequence of loops on the template and the set of interaction rules embodied in the linkers can be reconfigured with ease. We show that a set of just two interaction rules can be used to assemble simple T‐junction origami motifs and that assembly can be performed at room temperature.

Establishing empirical design rules of nucleic acid templates for the synthesis of silver nanoclusters with tunable photoluminescence and functionalities towards targeted bioimaging applications.

DNA-templated silver nanoclusters (AgNCs) are an emerging class of ultrasmall (<2 nm) fluorophores with increasing popularity for bioimaging due to their facile synthesis and tunable emission color. However, design rules correlating different nucleotide sequences with the photoemission properties of AgNCs are still largely unknown, preventing the rational design of DNA templates to fine-tune the emission color, brightness and functionalities of AgNCs for any targeted applications. Herein, we report a systematic investigation to understand the empirical influences of the four basic DNA nucleotides on AgNC synthesis and their effects on photoluminescence properties. After establishing the importance of nucleotide–Ag+ binding and AgNC encapsulation within DNA tetraplex structures, we then determined the unique attributes of each individual nucleobase using different combinations of systematically varied DNA templates. Using the empirical design rules established herein, we were able to predict the photoluminescence behaviours of AgNCs templated by complex aptamer sequences with specific binding affinity to human cancer cells, and to deliberately control their emission color by rational modifications of the DNA template sequences for targeted bioimaging. Our empirical findings from this systematic experimentation can contribute towards the rational design of DNA sequences to customise the photoluminescence properties and biofunctionalities of DNA-protected AgNCs towards multicolour targeted bioimaging applications.

A New Electrolyte Formulation for Securing High Temperature Cycling and Storage Performances of Na‐Ion Batteries

AbstractThe Na‐ion battery is recognized as a possible alternative to the Li‐ion battery for applications where power and cost override energy density performance. However, the increasing instability of their electrolyte with temperature is still problematic. Thus, a central question remains how to design Na‐based electrolytes. Here, the discovery of a Na‐based electrolyte formulation is reported which enlists four additives (vinylene carbonate, succinonitrile, 1,3‐propane sultone, and sodium difluoro(oxalate)borate) in proper quantities that synergistically combine their positive attributes to enable a stable solid electrolyte interphase at both negative and positive electrodes surface at 55 °C. Moreover, the role of each additive that consists in producing specific NaF coatings, thin elastomers, sulfate‐based deposits, and so on via combined impedance and X‐ray photoelectron spectroscopy is rationalized. It is demonstrated that empirical electrolyte design rules previously established for Li‐ion technology together with theoretical guidance is vital in the quest for better Na‐based electrolytes that can be extended to other chemistries. Overall, this finding, which is implemented to 18 650 cells, widens the route to the rapid development of the Na‐ion technology based on Na3V2(PO4)2F3/C chemistry.

Glass Transition Phenomenon for Conjugated Polymers

AbstractConjugated polymers are emerging as promising building blocks for a broad range of modern applications including skin‐like electronics, wearable optoelectronics, and sensory technologies. In the past three decades, the optical and electronic properties of conjugated polymers have been extensively studied, while their thermomechanical properties, especially the glass transition phenomenon which fundamentally represents the polymer chain dynamics, have received much less attention. Currently, there is a lack of design rules that underpin the glass transition temperature of these semirigid conjugated polymers, putting a constraint on the rational polymer design for flexible stretchable devices and stable polymer glass that is needed for the devices’ long‐term morphology stability. In this review article, the glass transition phenomenon for polymers, glass transition theories, and characterization techniques are first discussed. Then previous studies on the glass transition phenomenon of conjugated polymers are reviewed and a few empirical design rules are proposed to fine‐tune the glass transition temperature for conjugated polymers. The review paper is finished with perspectives on future directions on studying the glass transition phenomena of conjugated polymers. The goal of this perspective is to draw attention to challenges and opportunities of controlling, predicting, and designing polymeric semiconductors, specifically to accommodate their end use.

Código Modelo 2020: Un proyecto fib para el avance del hormigón estructural

El Código Modelo es uno de los documentos más importantes producidos por fib. Desde su primera edición en 1970, se han publicado ediciones en 1978, 1990 y, recientemente, en 2010. Todos estos documentos han influido en la producción de códigos nacionales y regionales. Los Códigos Modelo de 1978 y 1990 han tenido una gran influencia en las diferentes versiones del Eurocódigo 2. El Código Modelo de 2010 sirve de guía de manera similar al trabajo preparatorio de CEN para las nuevas ediciones de los Eurocódigos. Los Códigos Modelo siempre han sido una referencia importante para investigadores, diseñadores y constructores. La nueva edición del Código Modelo que se publicará en 2020 pretende abordar, al mismo nivel, las estructuras nuevas y existentes y presentar modelos más generales y más racionales, eliminando cualquier rastro de reglas de diseño empírico previas. Será un Código Modelo operativo y orientado a las necesidades prácticas. Este documento muestra el contenido del nuevo Modelo de Código 2020 y el trabajo en curso para su preparación.

Stress field solution for strip loaded reinforced concrete blocks

This paper aims at contributing to a better understanding of the physical-mechanical behaviour of partially loaded areas in reinforced concrete. Following a review of the current state of the art on this topic, which includes a description of the mechanical behaviour and existing predictive models, a remarkable knowledge gap in this standard problem is revealed. A new stress field solution for reinforced concrete blocks under strip loading is developed herein which is based on the lower-bound theorem of limit analysis and adopts a modified Coulomb failure criterion for concrete. Contrary to existing empirical design rules, the new mechanical model consistently accounts for the behaviour of concrete under multiaxial compression as well as the favourable effect of transverse reinforcement. While a comparison of the ultimate loads predicted using the new stress field solution shows a good correlation with the available test data, further experiments are required particularly for the validation of the predicted higher resistances of heavily confined areas as compared to existing design rules.

Optimization and performance of bifacial solar modules: A global perspective

With the rapidly growing interest in bifacial photovoltaics (PV), a worldwide map of their potential performance can help assess and accelerate the global deployment of this emerging technology. However, the existing literature only highlights optimized bifacial PV for a few geographic locations or develops worldwide performance maps for very specific configurations, such as the vertical installation. It is still difficult to translate these location- and configuration-specific conclusions to a general optimized performance of this technology. In this paper, we present a global study and optimization of bifacial solar modules using a rigorous and comprehensive modeling framework. Our results demonstrate that with a low albedo of 0.25, the bifacial gain of ground-mounted bifacial modules is less than 10% worldwide. However, increasing the albedo to 0.5 and elevating modules 1 m above the ground can boost the bifacial gain to 30%. Moreover, we derive a set of empirical design rules, which optimize bifacial solar modules across the world and provide the groundwork for rapid assessment of the location-specific performance. We find that ground-mounted, vertical, east-west-facing bifacial modules will outperform their south-north-facing, optimally tilted counterparts by up to 15% below the latitude of 30°, for an albedo of 0.5. The relative energy output is reversed in latitudes above 30°. A detailed and systematic comparison with data from Asia, Africa, Europe, and North America validates the model presented in this paper.

Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

Small interfering RNAs (siRNAs) may induce to targeted gene knockdown, and the gene silencing effectiveness relies on the efficacy of the siRNA. Therefore, the task of this paper is to construct an effective siRNA prediction method. In our work, we try to describe siRNA from both quantitative and qualitative aspects. For quantitative analyses, we form four groups of effective features, including nucleotide frequencies, thermodynamic stability profile, thermodynamic of siRNA-mRNA interaction, and mRNA related features, as a new mixed representation, in which thermodynamic of siRNA-mRNA interaction is introduced to siRNA efficacy prediction for the first time to our best knowledge. And then an F-score based feature selection is employed to investigate the contribution of each feature and remove the weak relevant features. Meanwhile, we encode the siRNA sequence and existed empirical design rules as a qualitative siRNA representation. These two kinds of siRNA representations are combined to predict siRNA efficacy by supported Vector Regression (SVR) at score level. The experimental results indicate that our method may select the features with powerful discriminative ability and make the two kinds of siRNA representations work at full capacity. The prediction results also demonstrate that our method can outperform other popular siRNA efficacy prediction algorithms.

Computational discovery of stableM2AXphases

The family of layered ${M}_{n+1}A{X}_{n}$ compounds provides a large class of materials with applications ranging from magnets to high-temperature coatings to nuclear cladding. In this work, we employ a density-functional-theory-based discovery approach to identify a large number of thermodynamically stable ${M}_{n+1}A{X}_{n}$ compounds, where $n=1$, $M=\text{Sc}$, Ti, V, Cr, Zr, Nb, Mo, Hf, Ta; $A=\text{Al}$, Si, P, S, Ga, Ge, As, Cd, In, Sn, Tl, Pb; and $X=\text{C}$, N. We calculate the formation energy for 216 pure ${M}_{2}AX$ compounds and 10 314 solid solutions, ${(M{M}^{\ensuremath{'}})}_{2}(A{A}^{\ensuremath{'}})(X{X}^{\ensuremath{'}})$, relative to their competing phases. We find that the 49 experimentally known ${M}_{2}AX$ phases exhibit formation energies of less than 30 meV/atom. Among the 10 530 compositions considered, 3140 exhibit formation energies below 30 meV/atom, most of which have yet to be experimentally synthesized. A significant subset of 301 compositions exhibits strong exothermic stability in excess of 100 meV/atom, indicating favorable synthesis conditions. We identify empirical design rules for stable ${M}_{2}AX$ compounds. Among the metastable ${M}_{2}AX$ compounds are two Cr-based compounds with ferromagnetic ordering and expected Curie temperatures around 75 K. These results can serve as a map for the experimental design and synthesis of different ${M}_{2}AX$ compounds.