Optimising the design of building blocks for self-assembly of discrete clusters

Self-assembly is the spontaneous organisation of matter into an ordered state. Significant progress has been made in the fabrication of synthetic components for self-assembly, opening up routes to building blocks for the production of functional materials and nanomachines. The information required to assemble a target structure can be encoded into the building blocks. For assembly of an equilibrium state, the target must be thermodynamically stable and the pathway must avoid kinetic traps. The design of building blocks must address both these requirements. In this work a generic model is introduced which, through an explicit representation of interactions, is able to express many approaches to self-assembly. The model consists of hard cubic particles, whose faces are patterned with attractive patches. A hybrid, dynamical Monte Carlo protocol is developed to simulate self-assembly of such inhomogeneous systems efficiently, accounting for both internal rearrangements and relative diffusion rates of aggregates. Using this single model, different self-assembly strategies are assessed, ranging from simple approaches with only one type of building block, to more complex strategies using multiple components and hierarchical paths. The important case of fully addressable targets, where all components of the structure are unique and have a specific location, is then examined in more detail. Firstly, a new metric is introduced to quantify the problem of competition between partly assembled fragments, which is a prominent source of kinetic traps in addressable clusters. Principles are established for minimising this problem. Secondly, a scheme for globally optimising the interactions amongst a set of particles is developed to maximise the performance of building blocks of a given complexity. This also makes it possible to determine the level of complexity required for a given target to assemble reliably. The computational tools and general principles established in this work should be applicable in a wide range of self-assembly problems

Assessing Simulations of Imperial Dynamics and Conflict in the Ancient World

The development of models to capture large-scale dynamics in human history is one of the core contributions of cliodynamics. Most often, these models are assessed by their predictive capability on some macro-scale and aggregated measure and compared to manually curated historical data. In this report, we consider the model from Turchin et al. (2013), where the evaluation is done on the prediction of "imperial density": the relative frequency with which a geographical area belonged to large-scale polities over a certain time window. We implement the model and release both code and data for reproducibility. We then assess its behaviour against three historical data sets: the relative size of simulated polities vs historical ones; the spatial correlation of simulated imperial density with historical population density; the spatial correlation of simulated conflict vs historical conflict. At the global level, we show good agreement with population density ($R^2 < 0.75$), and some agreement with historical conflict in Europe ($R^2 < 0.42$). The model instead fails to reproduce the historical shape of individual polities. Finally, we tweak the model to behave greedily by having polities preferentially attacking weaker neighbours. Results significantly degrade, suggesting that random attacks are a key trait of the original model. We conclude by proposing a way forward by matching the probabilistic imperial strength from simulations to inferred networked communities from real settlement data

Optimising Minimal Building Blocks for Addressable Self-Assembly

Addressable structures are characterised by the set of unique components from which they are built and by the specific location that each component occupies. For an addressable structure to self-assemble, its constituent building blocks must be encoded with sufficient information to define their positions with respect to each other and to enable them to navigate to those positions. DNA, with its vast scope for encoding specific interactions, has been successfully used to synthesise addressable systems of several hundred components. In this work we examine the complementary question of the minimal requirements for building blocks to undergo addressable self-assembly driven by a controlled temperature quench. Our testbed is an idealised model of cubic particles patterned with attractive interactions. We introduce a scheme for optimising the interactions using a variant of basin-hopping and a negative design principle. The designed building blocks are tested dynamically in simple target structures to establish how their complexity affects the limits of reliable self-assembly

SATRE: Standardised Architecture for Trusted Research Environments

The SATRE DARE UK-funded Driver Project was challenged to create a trusted research environment (TRE) architecture supporting the research community's need to have suitable data analytics and research environments for working with sensitive data. The project developed an inclusive and transparent way of working to ensure that what was created was representative of the TRE community in the UK. We have created, for the first time, an open specification for TRE operators by which to evaluate themselves against a set of capabilities. It is a thorough specification, perhaps definition, for TREs informed not only by the experience of the project team who have been running a TRE and supporting sensitive data projects for a combined 15 years but also the expansive knowledge of the wider UK research community. The public has also been involved throughout the development of the specification to ensure their voices are heard and reflected in the specification. The specification has been informed through one survey completed by 105 individuals representing approximately 60 organisations, 14 Collaboration Cafés with up to 75 participants, 26 individuals contributing directly, 44 issues raised and six public engagement sessions online and in-person. Despite the breadth and diversity of the individuals included, we have been able to create a single specification encompassing four architectural principles, four pillars, 29 capabilities and 160 statements. The 75 mandatory statements are what is considered the minimum required to be a SATRE-compliant TRE. Now, with a stable version 1.0 release, the specification is ready for use by the UK TRE community. We are and will continue to work with all organisations to evaluate themselves against the specification and also identify what works and what doesn't, which will be captured in future versions of the specification. The specification has been developed with the long-term in mind and can be a basis for a common understanding between operators, data controllers, accreditors, researchers, industry and government organisations for how TREs can federate and interoperate better.This work was funded by UK Research &amp; Innovation [Grant Number MC_PC_23008] as part of Phase 1 of the DARE UK (Data and Analytics Research Environments UK) programme, delivered in partnership with Health Data Research UK (HDR UK) and Administrative Data Research UK (ADR UK)

Design strategies for self-assembly of discrete targets

Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper, we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture the thermodynamic, dynamic, and steric challenges typically faced by self-assembly processes, including competition between multiple partially completed structures. Self-assembly pathways are extracted from the simulation trajectories by a fully extendable scheme for identifying structural fragments, which are then assembled into history diagrams for successfully completed target structures. For the simple target, a one-component assembly scheme is most efficient and robust overall, but hierarchical and addressable strategies can have an advantage under some conditions if high yield is a priority

Controlling Fragment Competition on Pathways to Addressable Self-Assembly

Addressable self-assembly is the formation of a target structure from a set of unique molecular or colloidal building-blocks, each of which occupies a defined location in the target. The requirement that each type of building-block appears exactly once in each copy of the target introduces severe restrictions on the combinations of particles and on the pathways that lead to successful self-assembly. These restrictions can limit the efficiency of self-assembly and the final yield of the product. In particular, partially formed fragments may compete with each other if their compositions overlap, since they cannot be combined. Here, we introduce a "completability" algorithm to quantify competition between self-assembling fragments and use it to deduce general principles for suppressing the effects of fragment incompatibility in the self-assembly of small addressable clusters. Competition originates from loops in the bonding network of the target structure, but loops may be needed to provide structural rigidity and thermodynamic stability. An optimal compromise can be achieved by careful choice of bonding networks and by promoting semi-hierarchical pathways that rule out competition between early fragments. These concepts are illustrated in simulations of self-assembly in two contrasting addressable targets of 20 unique components each

Abstract ATE Data Collection – A comprehensive requirements proposal to maximize ROI of test

ATE customers are increasingly viewing a tester that does not facilitate easy and consistent access to the test data as a barrier to their profitability. The data is needed towards various ends like, Statistical Post Processin