Structural Framework Research Articles

Mixed ligand iso-reticular MOFs as integrated photo-catalytic adsorbents for the removal of bromo-phenol blue: Kinetics, thermodynamics and mechanistic study

The designing of mixed linker MOFs with identical framework structures and different chemical components provides opportunities for enhancing their inborn adsorption and photo-degradation performances. Herein, we synthesized zinc, copper, manganese, and cobalt-based iso-reticular MOFs via the solvothermal method using 2,5-furan dicarboxylic acid and 1,2-bis(4-pridyl) ethylene as green ligands. The synthesized MOFs were applied for the adsorption-assisted photo-catalytic decontamination of bromophenol blue (BPB) from wastewater without using any co-catalyst under visible light irradiation. Note-worthily, Cu-MOF (BUT-206-Cu) exhibits high adsorption capacity (299 mg/g) and removal efficiency (97 %), mainly owing to the high surface area (280 m2/g), opened porous structure, additional defective sites, efficient energy transfer, and excellent stability in aqueous, and acidic environments resulting from the strong co-ordination environment of the copper cations. The impact of key factors, including initial pH and concentration of the dye solution, on the adsorption and degradation efficiency of BUT-206-Cu was investigated. Moreover, trapping experiments and EPR results revealed that OH• and h+ were the main active species in the photocatalytic degradation of BPB. Adsorption and degradation kinetics of BPB were observed to obey pseudo-second-order and pseudo-first order models, respectively. The thermodynamics study revealed that the adsorption of BPB fitted the Langmuir model, and values of the ΔGads, ΔHads, and ΔSads revealed that the adsorption process is spontaneous, physical, and exothermic and leads to increased randomness in the system. BUT-206-Cu exhibited excellent reusability for up to five cycles, indicating its potential as an environmentally friendly integrated photocatalytic adsorbent for removing BPB from wastewater.

Model-free aperiodic tracking for discrete-time systems using hierarchical reinforcement learning

In the operation of practical systems, it is often a challenging task to deal with limited knowledge of the system dynamics, therefore, it is needed to obtain a framework for the simultaneous learning and control of dynamic systems, able to cope with uncertain dynamics. This paper proposes a model-free aperiodic tracking control method based on MAXQ hierarchical reinforcement learning for unknown dynamics in discrete-time systems. Firstly, a MAXQ hierarchical framework is developed for aperiodic tracking control that decomposes the task into pre-control and accurate control subtasks. The former achieves sub-optimal tracking which prompts the implementation of accurate control. The latter implements aperiodic tracking based on the pre-control result to reduce resource occupation. The structure of the MAXQ framework simplifies the complexity of the tracking task, and the incorporation of pre-control accelerates the learning process in the formal control stage. Secondly, considering the disparities between the control inputs and the control update instants, pre-control is decomposed to learn the triggering strategy and control policy, respectively. Meanwhile, the control policy learns optimal control inputs by minimizing the cost function. Similarly, the triggering strategy and control policy are also separately learned in accurate control. In contrast to traditional aperiodic triggering mechanisms, in accurate control stage, the triggering strategy is developed based on the cumulative error of the pre-control result, thus avoiding the influence of accidental factors and the cumulative effects of errors, enhancing system robustness. Thirdly, the proposed tracking control is derived by using only the input, output, and reference signal data from the system, without relying on system dynamics. It is applicable to both linear and nonlinear systems, demonstrating strong generalizability. Finally, simulation examples are provided to validate the effectiveness and superiority of the proposed method.

Demographic obstacles to European growth

The growth rates of the four largest European economies – France, Germany, Italy, and the United Kingdom – have slowed in recent decades. The persistence of the slowdown suggests that a low-frequency structural change is at work. Longer life expectancy and declining fertility have led to gradually ageing populations. These demographic trends contribute to economic growth directly through aggregate savings and labor supply decisions and indirectly through distortionary taxes needed to fund pension systems. We provide a structural framework to quantify the demographic contributions to historical and future growth rates. Several reforms have been suggested to increase late-life labor supply and, through that, output growth. Our structural framework also gives a welfare measure to evaluate these proposed reforms. The welfare implications are heterogeneous across age, wealth, and income. Welfare heterogeneity offers some insights into the political economy of pension reforms and the opposition to their implementation despite the projected increase in aggregate output growth.

A CAD-oriented parallel-computing design framework for shape and topology optimization of arbitrary structures using parametric level set

Recently, the high-resolution topology optimization to promote engineering applicability has gained much more attentions. However, an accurate and highly-efficient design framework for implementing shape and topology optimization of engineering structures with integration of CAD model is still in demand. In the current work, the critical intention is to develop a CAD-oriented parallel-computing design framework for arbitrary structures, where the Parametric Level Set Method (PLSM) is employed for shape and topology optimization. Firstly, an implicit identification model is constructed for generating a signed distance field using the vertex and normal information from the ‘STL’ file of engineering structures. The signed distance field is combined with the compactly supported radial basis functions (CSRBFs) to solve the initial level set function with a parametrization. This method is applied to present all domains, including design domains, Neumann boundary domains, Dirichlet boundary domains, and non-design domains. Secondly, the CPU parallel strategy is considered for allocating partitions of structural stiffness matrix in finite element analysis to different CPU cores for the parallel-computing to save computation costs. Thirdly, a parallel-computing design formulation is developed for performing shape and topology optimization of arbitrary structures, in which the partitioned terms of all design variables and stiffness matrix are concurrently computed on each CPU core. Finally, several classic benchmarks and the critical engineering structure of Virtual Reality (VR) glass part with extremely complex geometries, are discussed to demonstrate the effectiveness and efficiency of the proposed design framework.

A universal machine learning framework to automatically identify high‐performance covalent organic framework membranes for CH4/H2 separation

AbstractA universal machine learning framework is proposed to predict and classify membrane performance efficiently and accurately, achieved by combining classical density functional theory and string method. Through application of this framework, we conducted high‐throughput computations under industrial conditions, utilizing an extensive database containing nearly 70,000 covalent organic framework (COF) structures for CH4/H2 separation. The best‐performing COF identified surpasses the materials reported in the previously documented MOF and COF databases, exhibiting an impressive adsorption selectivity for CH4/H2 exceeding 82 and a membrane selectivity reaching as high as 248. More impressively, some of the best candidates identified from this framework have been verified through previous experimental works. Furthermore, the automated machine learning framework and its corresponding scoring system not only enable rapid identification of promising membrane materials from a vast material space but also contribute to a comprehensive understanding of the governing mechanisms that determine separation performance.

Natural Peroxides from Plants: Historical Discovery, Biosynthesis, and Biological Activities.

Naturally occurring peroxides received great interest and attention from scientific research groups worldwide due to their structural diversity, versatile biological activities, and pharmaceutical properties. In the present review, we describe the historical discovery of natural peroxides from plants systematically and update the researchers with recently explored ones justifying their structural caterogrization and biological/pharmaceutical properties intensively. Till the end of 2023, 192 peroxy natural products from plants were documented herein for the first time implying most categories of natural scaffolds (e. g. terpenes, polyketides, phenolics and alkaloids). Numerically, the reported plants' peroxides have been classified into seventy-four hydro-peroxides, hundred seven endo-peroxides and eleven acyl-peroxides. Endo-peroxides (cyclic alkyl peroxides) are an important group due to their high variety of structural frameworks, and we have further divided them into "four-, five-, six and seven"-membered rings. Biosynthetically, a shedding light on the intricate mechanisms behind the formation of plant-derived peroxides are addressed as well.

Crustal extension and necking at central Campos rifted margin: The Marlim Detachment System

Detachment faults play a crucial role in accommodating crustal thinning and controlling basin architecture in extensional tectonic settings. This study focuses on the characterization of extensional structures at the Necking Domain of the central Campos Rifted Margin, southeast Brazil. Based on seismic reflection and magnetic data we interpreted a system of long offset detachment faults, here named as the Marlim Detachment System. This system is characterized by three distinct large-displacement detachment faults which systematically root at subhorizontal intracrustal reflectors, interpreted as middle crust ductile shear zones, indicating a depth-dependent accommodation of extensional strain. The detachment fault systems resulted in highly tilted upper crustal blocks, which lead to intense erosion of the footwall and the pre-salt sequences eastward. The large horizontal displacement of the hanging wall blocks by most of the detachment faults created deep and wide half-grabens resulting in thick syn-rift sedimentary wedges. The basement structural framework seems to reflect a northward strike-rotation from NE-to NS-direction of the fault systems. That rotation promoted the segmentation of the Marlim Detachment System and points out an oblique-slip extensional kinematics during rifting. We propose that the observed tectonic style at the Necking Domain of central Campos is the result of its interaction with the Vitória-Colatina Transfer Zone to the north and the Araruama Transfer Zone to the south, configuring the Marlim area as a structurally transition zone. The tectonostratigraphic analysis suggests a migration of the deformation from continent to ocean from Hauterivian to Aptian, and a polyphase and/or tardi-tectonic deformation of the Necking Domain in the central Campos Rifted Margin.

Phosphomolybdates for Dual-Mode Photoelectrochemical Sensing toward Trace Chromium(VI) and Tetracycline.

Highly sensitive photoelectrochemical (PEC) sensors for trace carcinogens, such as heavy metal chromium(VI) [Cr(VI)] and antibiotic tetracycline (TC) are crucial. Herein, by integration of photoactive and redox phosphomolybdates with conjugated organic components, types of dual-mode PEC sensors were synthesized for sensing trace Cr(VI) and TC pollutants, with formulas of (H2bimb)2[Co2(bimb)1.5][Co(H2O)4][Co(P4Mo6O31H6)2]·6H2O (1), (H2bib)2[Co(H2O)3][Co2(H2O)5][Co(P4Mo6O31H6)2]·9H2O (2), and (H2bib)6[Co(Hbib)2(H2O)5][Co(P4Mo6O31H7)2]2·15H2O (3), where bimb represents 1,4-bis(1-imidazolyl)benzene and bib is 4,4'-bis(imidazolyl)bibphenyl. Hybrid 1 consisted of a three-dimensional framework structure constructed by Co{P4Mo6}2 clusters and one-dimensional (1D) {Co-bimb} chains, hybrid 2 exhibited 1D Co ion-bridged Co{P4Mo6}2 chains hydrogen-bonding with [H2bib]2+ cations, and hybrid 3 showed a discrete hybrid structure built upon a Co{P4Mo6}2 cluster modified by the {Co-bib} unit. Hybrids 1-3 displayed wide spectral absorption and excellent electrochemical redox properties, enabling dual-mode PEC responses to Cr(VI) reduction and TC oxidation. For Cr(VI) detection, hybrids 1-3 exhibited high sensitivities of 364.40, 225.72, and 124.29 μA·μM-1 as well as "nM" level detection limits (LODs) of 4.9, 10.0, and 11.0 nM, respectively. For TC detection, the sensitivities of hybrids 1-3 were 494.72, 308.78, and 174.03 μA·μM-1 and the LODs were 5.2, 6.1, and 12.9 nM, respectively. This research offers significant insights into designing efficient PEC sensors for the detection of environmental pollutants.

Possible metal oxide cathode materials for Al-ion batteries: A first principle study

This study investigates various Aluminum (Al) -ion oxide cathode materials, considering their structural properties/stability, cell voltage, band gap analysis, and electrical/ion-diffusion rate-capability. The studied materials are AlMn2O4, AlMoO3, AlTiO2, AlV2O5, AlLiCo2O4, and AlCo2O4. The calculations are conducted using Density Functional Theory (DFT) methods, specifically Generalized Gradient Approximation (GGA) and GGA + U. We employ various noble approaches and techniques to assess the properties of the materials. The findings reveal structural stability after deintercalation of Al ion for all the considered structures. AlMn2O4 exhibits the highest stability due to its strong structural framework, while TiO2 is suspected for this property. Voltage estimation suggests higher possible voltages for AlCo2O4 and AlLiCo2O4 materials, despite not being experimentally examined. Calculated intrinsic-like and extrinsic-like band gaps demonstrate the highest conduction for AlCo2O4. Evaluation of rate-capability recognizes the highest electrical/ion-diffusion rate-capability for AlCo2O4 and AlLiCo2O4. Finally, this study introduces two new superior electrode materials for Al-ion batteries (AIBs), i.e. AlLiCo2O4 and AlCo2O4, with promising properties for future AIBs.

Probabilistic resilience assessment framework of structures considering the combined functionality-recovery-duration uncertainty

In the current stage, the risk-guided performance-based earthquake engineering (PBEE) has become the main direction in the earthquake community. As an important part of risk, seismic resilience indicators have been increasingly emphasized and elevated to new levels in recent years. Seismic resilience refers to the capacity of social entities to reduce disaster risks and to facilitate recovery efforts with the least social disruption in possible. Currently, the calculations of resilience indicators are commonly based on the deterministic approach. In fact, resilience indicators are also random variables, and the corresponding recovery time, recovery function or residual function in resilience calculation may vary within a range for different intensity levels and limit states. Therefore, characterizing resilience indicators through probabilistic models or confidence intervals can be a more practically valuable and meaningful strategy for future research. In this paper, a probabilistic resilience assessment framework of structures is proposed, and a sinusoidal-based continuous recovery function characterized by different limit states and recovery modes is given. The combined uncertainties of functionality, recovery and duration are incorporated into the framework, and an application example via the reinforced concrete frame is given to implement the framework. Besides, the sensitive analysis of different variables to the resilience assessment result is performed, and the comparison between the deterministic and probabilistic analysis is further discussed. In general, the framework consists of three parts, i.e., (1) Generating samples, fragility and damage states; (2) Calculating total stochastic recovery functions for resilience analyses; and (3) Performing probabilistic seismic resilience analyses. If deterministic analysis is used, the resilience index is only a value, while if probabilistic analysis is used, the resilience index will be a variable with a corresponding probability and distribution range. Compared with other variables, the amplitude and wavelength have a stronger influence in the result of resilience index. This is because these two parameters are function-dependent and will directly affect the envelope curve in the resilience calculation. Although the changes in coefficient of variation (COV) will affect the curve results, the macro characteristics are consistent when comparing different target resilience index. Moreover, as the intensity rises, there is a statistical decrease in both the average residual functionality and resilience indicators, along with a statistical increase in the average recovery durations. The annual exceeding probability decreases as the target resilience level increases, while the life-cycle exceeding probability increases when the target resilience level decreases for the same year. In a sense, the integrated probabilistic resilience framework realizes the decoupling of resilience indicators for different performance groups and limit states, and provides a reference for the further stochastic resilience assessment from a probabilistic perspective.

Crystal structure of an antibody specifically recognizing 3,4-methyl enedioxy methamphetamine through the epoxide moiety

3,4-methylenedioxymethamphetamine (MDMA) or publicly known as “ecstasy” is a drug abuse substance. Since antibodies that detect MDMA typically also recognize its chemical analogue, methamphetamine (METH), we identified antibodies specifically recognizing MDMA, but not METH, named 1bB11 and 1bF12, using phage display. The crystal structure of 1bB11 in complex with MDMA was determined at 3.2 Å resolution. Key interactions were found between the epoxide moiety of MDMA and S34 and Y36 of the light chain. Additional interaction with E33 of the heavy chain contributes to anchoring MDMA. Mutagenesis-based biochemical analysis confirmed the importance of these residues in MDMA binding. Comparing the structure of 1bB11 to a scFv6H4, which binds both METH and MDMA, revealed opposite binding orientations. Taken together, our data provides a structural framework for selective binding to MDMA by the 1bB11 antibody, paving a way to develop a highly specific antibody for diagnosis.

Applying the "SOTEC" framework of sociotechnical risk analysis to the development of an autonomous robot swarm for a public cloakroom.

The past decade has seen efforts to develop new forms of autonomous systems with varying applications in different domains, from underwater search and rescue to clinical diagnosis. All of these applications require risk analyses, but such analyses often focus on technical sources of risk without acknowledging its wider systemic and organizational dimensions. In this article, we illustrate this deficit and a way of redressing it by offering a more systematic analysis of the sociotechnical sources of risk in an autonomous system. To this end, the article explores the development, deployment, and operation of an autonomous robot swarm for use in a public cloakroom in light of Macrae's structural, organizational, technological, epistemic, and cultural framework of sociotechnical risk. We argue that this framework provides a useful tool for capturing the complex "nontechnical" dimensions of risk in this domain that might otherwise be overlooked in the more conventional risk analyses that inform regulation and policymaking.

Gravity and magnetism of southern Africa in relation to Craton structures and belts

The general tectonic structural architecture of southern Africa is an ensemble comprised of Kalahari Craton, a vast range of mosaics of the best-preserved geological Belts, and exposed crustal blocks. In the region, demarcation of geological boundaries, tracing of magnetic and gravitational bodies, and detrending lineaments are essential to understanding the structural limits. The study presents the prevalent gravitational and magnetic investigation of major geological Belts, enhancing edges of Cratons, and evaluation of surface invariants to improve the geological understanding and evaluate the correlation of structures with the general structural tectonic framework. The utilized filter methods in the gravity maps are the Directional derivatives along x, y, and z-directions, the Modulus tensor, the Total horizontal derivative, and the Tilt angle techniques.The phase-based filters used in the magnetic section include the Total horizontal derivative, Analytical signal, Tilt angle method, Tilt of total horizontal derivative, Theta method, Horizontal tilt angle method, Enhanced tilt filter, and Enhanced total derivative of the tilt angle. The Directional derivatives of the gravity field and the Modulus of the gravity gradient tensor demarcate the boundaries of geological structures. The Total horizontal derivative method gives an immediate and easy-to-read image of the linear structures and fault systems. The signal cluster on the Analytical signal and Tilt angle maps delineate the boundaries of causative geological sources. The Theta map is comparable with the enhanced total derivative of the tilt angle. The Tilt of the total horizontal derivative, Theta map, and Enhanced tilt filter accentuate the traces of magnetic bodies, including the Cratons. The study finds regional lineaments surrounding the Cratons and concentrated along the geological Belts. The approach of using joint elegant filters is effective and increases the certainty of the interpretation.

The Structural Framework and Opening Appearance of the VP1-Pocket of Enteroviruses Correlated with Viral Thermostability.

Enteroviruses (EVs and RVs) are prevalent worldwide and cause various diseases in humans, of which the VP1-pocket is a target of antivirals, with a lipid molecule as a pocket factor to stabilize the virion. However, the characterization of the structure of the VP1-pocket in EVs is poor. Here, we compared the published capsid crystals of EVs and RVs and proposed a structural framework for the VP1-pocket: Frame 1-4, which is located at the CD loop, GH loop, and C-terminus, presenting with an outward opening appearance or not. The non-outward viral strains-CVB3, Echo 11, RV-A81, and RV-B70-are more thermally stable, with a breakpoint temperature (B.T.) of 51~62 °C for genome releasing, which is 4~10 °C higher than its outward temperature of 41~47 °C, and infectivity preservation when treated at 50 °C for 3 min. Its outward versus non-outward opening is correlated significantly with the B.T. for genome release (r = -0.90; p = 0.0004) and infectivity (r = -0.82, p = 0.0039). The energy of Frames 1, 2, and 4, including Van der Waals attractive and repulsive interactions and hydrogen bonds, showed significant correlations with the B.T. (r = -0.67, 0.75, and -0.8; p = 0.034, 0.013, and 0.006, respectively). These characters of the VP1-pocket could be predictors for virion thermostability and aid in the development of vaccines or antivirals.

Mechanisms of near-wellbore fracture growth considering the presence of cement sheath microcracks and their implications on wellbore stability

Placement of intended perforations is usually extensive enough into the reservoir to minimize any near wellbore influence on the expected fracture growth. However, some unplanned fractures do not necessarily originate from the intended shot holes. A sufficient volume of published work exists on the processes of crack growth from the near wellbore regions such as from the cement sheath or from fractures observed on the formation wall surrounding the wellbore. A robust quantification of wellbore stability issues should not detach such fracture development, which can potentially result into issues such as cement sheath damage and unnecessary formation damage in the near-wellbore regions. Such fractures may become fluid injection points during stimulation related wellbore pressurization, leading to pronounced development. In such scenarios, fracture development may become a nuisance if it jeopardises the intended structural support and zonal isolation integrity of the cement sheath around the wellbore, leading to wellbore failure, and a potential abandonment. The pressure transmission across this structural seal affects the zonal isolation integrity and its intended structural support leading to wellbore instability. Understanding crack growth behaviour in such cement-rock structural framework is still illusional yet it poses the wellbore to a risky state of instability. Our study provides insight into mechanical and elastic behavior of a tightly bonded cement-rock framework with presence of initial cracks. It also provides insight into how the acting far-field stresses, applied wellbore pressures, crack length, and orientation angle influence the crack growth morphologies including planar fractures, curved and cyclic fractures. The study is important not only for a proper selection of the cement slurry but also for the definition of allowable pressures during the wellbore lifespan. Inappropriately selected parameters might lead to the loss of wellbore integrity to a point as early as the start of a well’s life.

Hydrophobic and porous Fe-Pdb coordination framework structure supported Pt-Fe nanoparticles catalyst for enhanced chemoselective hydrogenation of cinnamaldehyde

The selective hydrogenation of cinnamaldehyde to cinnamyl alcohol has remained a ponding challenge due to competitive hydrogenation reactions between CC and CO groups. In this work, a hydrophobic and porous Fe and 3,3′-(pyridine-3,5-diyl)-dibenzoic acid coordination framework structure (Fe-Pdb(CFs)) was employed to support Pt-Fe nanoparticles and synthesize a high-performance Pt-Fe/Fe-Pdb(CFs) heterogeneous catalyst. The reactivity activity could be greatly improved by introducing electrophilic sites and enhancing the enrichment effect of Fe-Pdb(CFs) material. Thus, the optimal cinnamaldehyde conversion reached approximately 88.9%, with a better selectivity of 85.8% towards cinnamyl alcohol at 60°C.

Highly sensitive electrochemiluminescence sensing platform based on copper nanoclusters synthesized via a DNA nanoribbon template for the detection of cancer cells

Herein, we presented a simple ultra-sensitive "on-off-on" electrochemiluminescence (ECL) biosensor that uses copper nanoclusters (CuNCs) synthesized via a DNA nanoribbon (DNR) template (DNR-CuNCs) as a sensing platform coupled with target-cycle amplification for the sensitive and rapid detection of cancer cells that overexpress proteins. DNR templated DNR-CuNCs, a well-ordered ECL emitter, was integrated into the nucleic acid framework structure to self-assembly, which enhanced the ECL intensity benefit from reduced band gap and accelerated electron transfer reaction of CuNCs. Additionally, an optimized exonuclease III (Exo III)-assisted cycle amplification method was introduced to efficiently convert trace target biomarkers into a substantial output of DNA, significantly improving target conversion efficiency and boosting the ECL signal. Consequently, MUC1 proteins were sensitively detected by the ECL biosensor throughout a broad concentration range, from 1 fg·mL−1 to 1 ng·mL−1, with a low limit of detection (LOD) of 0.061 fg·mL−1, and successfully detected MUC1-overexpressing cancer cells (using MCF-7 cancer cells as a model), accurately identifying MCF-7 cells in the concentration range of 10–100,000 cells·mL−1 with a LOD of 5 cells·mL−1. This research, for the first time, introduced a DNR-CuNCs ECL biosensor for the highly sensitive detection of living cells and their associated surface proteins. The detection of biomarker proteins and specific cells is greatly promising by applying this simple, sensitive, and specific strategy.

A Hydrogen-Bonded Organic Framework Based on Triphenylamine for Photocatalytic Silane Hydroxylation.

Employing hydrogen-bonded organic frameworks (HOFs) as mild photocatalysts for organic conversions is still considerably challenging. In this work, we synthesized a hydrogen-bonded organic framework (HOF-16) and achieved the photocatalytic oxidation of silanes to generate silanols. Considering the constraints imposed by the framework structure, a significant improvement in the efficacy of singlet oxygen (1O2) generation is observed. HOF-16 exhibits remarkable photocatalytic performance when it comes to silane hydroxylation, displaying high efficiency, low catalyst loading, and good recyclability. This research highlights the immense potential of HOFs in the realm of organic photocatalysis.

Recognition and order of multiple sidechains by metal-organic framework enhances the separation of hexane isomers.

Porous materials perform molecular sorting, separation and transformation by interaction between their framework structures and the substrates. Proteins also interact with molecules to effect chemical transformations, but rely on the precise sequence of the amino acid building units along a common polypeptide backbone to maximise their performance. Design strategies that positionally order sidechains over a defined porous framework to diversify the internal surface chemistry would enhance control of substrate processing. Here we show that different sidechains can be ordered over a metal-organic framework through recognition of their distinct chemistries during synthesis. The sidechains are recognised because each one forces the common building unit that defines the backbone of the framework into a different conformation in order to form the extended structure. The resulting sidechain ordering affords hexane isomer separation performance superior to that of the same framework decorated only with sidechains of a single kind. The separated molecules adopt distinct arrangements within the resulting modified pore geometry, reflecting their strongly differentiated environments precisely created by the ordered sidechains. The development of frameworks that recognise andorder multiple sidechain functionality by conformational control offers tailoring of the internal surfaces within families of porous materials to direct interactions at the molecular level.

Using a Structured Research Framework to Improve Mentoring Capacity in a Biophysics Research Lab

ABSTRACT Undergraduate research experiences (UREs) cultivate workforce skills, such as critical thinking, project management, and scientific communication. Many UREs in biophysical research have constraints related to limited resources, often resulting in smaller student cohorts, barriers for students entering a research environment, and fewer mentorship opportunities for graduate students. In response to those limitations, we have created a structured URE model that uses an asynchronous training style paired with direct-tiered mentoring delivered by peers, graduate students, and faculty. The adaptive undergraduate research training and experience (AURTE) framework was piloted as part of the Brown Experiential Learning program, a computational biophysics research lab. The program previously demonstrated substantial increases and improvements in the number of students served and skills developed. Here, we discuss the long-term effectiveness of the framework, impacts on graduate and undergraduate students, and efficacy in teaching research skills and computational-based biophysical methods. The longitudinal impact of our structured URE on student outcomes was analyzed by using student exit surveys, interviews, assessments, and 5 years of feedback from alumni. Results indicate high levels of student retention in research compared with university-wide metrics. Also, student feedback emphasizes how tiered mentoring enhanced research skill retention, while allowing graduate mentors to develop mentorship and workforce skills to expedite research. Responses from alumni affirm that workforce-ready skills (communicating science, data management, and scientific writing) acquired in the program persisted and were used in postgraduate careers. The framework reinforces the importance of establishing, iterating, and evaluating a structured URE framework to foster student success in biophysical research, while promoting mentorship skill training for graduate students. Future work will explore the adaptability of the framework in wet lab environments and probe the potential of AURTE in broader educational contexts.