Future Design Research Articles

Ultra-Narrowband Circularly Polarized Luminescence from Multiple 1,4-Azaborine-Embedded Helical Nanographenes.

In this manuscript we present a strategy to achieve ultranarrowband circularly polarized luminescence (CPL) from multiple 1,4-azaborine-embedded helical nanographenes. The impact of number and position of boron and nitrogen atoms in the rigid core of the molecule on optical properties─including absorption and emission maxima, photoluminescence quantum yield, Stokes shift, excited singlet-triplet energy gap and full width at half-maximum (fwhm) for CPL and fluorescence─was investigated. The molecules reported here exhibits ultranarrowband fluorescence (fwhm 16-17.5 nm in toluene) and CPL (fwhm 18-19 nm in toluene). To the best of our knowledge, this is among the narrowest CPL for any organic molecule reported to date. Quantum chemical calculations, including computed CPL spectra involving vibronic contributions, provide valuable insights for future molecular design aimed at achieving narrowband CPL.

Architectural organization and in situ fusion protein structure of lymphocytic choriomeningitis virus.

The impact of COVID-19 on public health has highlighted the importance of understanding zoonotic pathogens. Lymphocytic choriomeningitis virus (LCMV) is a rodent-borne human pathogen that causes hemorrhagic fever. Herein, we describe the in situ structure of LCMV proteins and their architectural organization on the viral envelope and around the nucleocapsid. The virion structure reveals the distribution of the surface glycoprotein complex (GPC) and the contact points between the viral envelope and the underlying matrix protein, as well as the association with the nucleocapsid. The morphology and sizes of virions, as well as the number of RNA polymerase L inside each virion vary greatly, highlighting the fast-changing nature of LCMV. A comparison between the in situ GPC trimeric structure and prior ectodomain structures identifies the transmembrane and endo domains of GPC and key interactions among its subunits. The work provides new insights into LCMV assembly and informs future structure-guided vaccine design.

Analysing the behaviour change techniques in an effective food literacy program to inform future program design.

Food literacy programs aim to improve food related skills and knowledge and are selected Governments as a strategy to address dietary intakes at a community level. The purpose of this research is to identify behaviour change techniques in a food literacy program, which were assessed by the achievement of participant goals related to food literacy and dietary behaviour changes. Consensus methods were applied to map behaviour change techniques to an adult food literacy program. A second phase investigation applied content analysis of participant process evaluation data (collected between 2016 and June 2021) to align target behaviours and behaviour change techniques. Chi-square and ANCOVA were used to assess the statistically significant demographic characteristics, food literacy, and dietary behaviour scores for participants who set goals and recorded changes. A total of 4697 program participants provided evaluation data from the 4-week food literacy program. Participants who set goals and made changes were statistically more likely to have higher food literacy factor scores (p < 0.001) and fruit serves (p = 0.004). Statistical analysis showed that participants were more likely to have set goals and recorded changes if they were female (p < 0.001), older (p < 0.001), higher education level (p < 0.001), had a higher socioeconomic status (p = 0.049), lived with children (p = 0.014), were born in Australia (p = 0.019), or did not identify as Indigenous (p < 0.001). The behaviour change technique mapping process identified nine techniques used weekly and a total of 22 techniques used over the entire 4 week program curriculum. This is the first Australian study to link the contribution of behaviour change techniques to food literacy and dietary behaviour change in an established effective food literacy program. Knowing the behaviour change techniques associated with effective programs will facilitate replication of effective interventions.

Influence of Pnictogen and Ligand Framework on the Lewis Acidity and Steric Environment in Pnictogen Pincer Complexes.

Pnictogen pincer complexes are a fascinating class of compounds due to their dynamic molecular and electronic structures, and valuable stoichiometric or catalytic reactivity. As recognition of their unique chemistry has grown, so too has the library of pincer ligands employed and pnictogen centres engaged to prepare them. Here we computationally study how the choice of pincer ligand framework and pnictogen influence the electronic and steric outcomes of the complexes obtained. The most relevant electronic parameter is the pnictogen-centred electrophilicity, which has been quantified by fluoride ion affinities and LUMO energies, while the most relevant steric parameter is the crowding around the central pnictogen, which has been quantified by the %Vbur values and visualized using steric maps. The resulting trends are analyzed with reference to binding pocket size, acceptor orbital type, electronic delocalization, π-donor strengths, and heteroatom incorporation. Thus, considering 16 ligand frameworks and 4 heavy pnictogen centres, this study provides a broad-spectrum view of stereo-electronic variation in pnictogen pincer complexes, which, together with a recent study on geometric variation in the same family, provides a substantial dataset to guide future molecular design and reactivity studies.

Feasibility of Emergency Department-Initiated HIV Pre-Exposure Prophylaxis

Introduction: Pre-exposure prophylaxis (PrEP) for HIV—using antiretroviral medication in non-infected individuals to prevent HIV—has immense potential to slow the spread of the virus. However, uptake has been insufficient, and stark racial disparities exist in both HIV acquisition and PrEP usage, making PrEP access a health equity issue. A promising venue to engage high-risk populations in PrEP care is the emergency department (ED); however, existing ED PrEP initiatives have been costly or have had limited success. We hypothesize that two strategies could overcome these barriers: prescribing PrEP during an ED visit and providing patients with an initial supply of PrEP medication in the ED. Here, we describe the results of a qualitative study exploring multidisciplinary emergency clinicians and HIV clinicians’ needs and views about the feasibility of such an initiative. Methods: We conducted 22 semi-structured interviews with multidisciplinary clinicians from an urban, safety-net medical center in the ED and the on-site HIV clinic that provides PrEP services.We performed thematic analysis to summarize challenges and potential solutions described by participants. Results: Participants’ responses fell into three thematic categories: operational challenges; patient-level considerations; and potential impacts. Operational challenges highlighted the difficulty of PrEP initiation in a busy ED and clinician support needs. Patient-level considerations included the complex psychosocial needs of ED patients who could benefit from PrEP. Finally, participants anticipated that an ED-based PrEP initiation program could positively impact both individual patients and public health. Conclusion: Interviews with emergency department and HIV clinic staff revealed important considerations and potential solutions for ED-initiated PrEP workflows. Clinicians in both specialties were enthusiastic about such an initiative, which could facilitate its success. This study lays the groundwork for the future design of an efficient and innovative workflow to leverage the ED as an essential entry point into HIV prevention services.

A Review of Seismic Optimization Design of Building Structures with Uniform Response

Earthquakes threaten human survival with powerful destructive power, and the performance of buildings in earthquakes is crucial. The seismic design of traditional building structures has the limitations of non-uniform response to displacement and acceleration, which can easily lead to partial damage to the building, unreasonable structure and difficulty in post-earthquake repair, which seriously affects the comfort and safety of the building. It is emphasized that improving the seismic safety of buildings is not only an inevitable requirement to ensure the safety of people's lives, but also to meet people's needs for continuous improvement of building comfort. The review shows that it is of great practical significance to study the seismic optimization design method of building structures with uniform response, which provides an important reference direction for the future design of building structures.

A Digital Engineering Analysis of an Additively Manufactured Turbine Vane

Abstract Additive manufacturing (AM) has transformed the ability to accelerate gas turbine component research and development at a fraction of the cost and time associated with conventional manufacturing. However, whereas prior works have assessed manufacturing variability in cast turbine airfoils, limited data are available to understand the impact of as-built deviations in AM turbine parts. As metal additive airfoils are becoming more prevalent in research turbine architectures, it is increasingly important to understand the effects of potential hardware deviations specific to additively manufactured parts. With this goal in mind, the current study utilizes a digital engineering approach to evaluate the aerodynamic impact of surface deviations on a high-pressure turbine vane design created for research purposes. RANS-based CFD studies derived from structured light scans of as-built turbine vanes are used to quantify performance relative to design intent geometries. Further computational analyses compare results from individual serialized parts with an average vane doublet geometry serving as a surrogate for the entire wheel. Particular emphasis in the study focuses on external surface defects caused by internal cooling features that are inherent through additive manufacturing and how these features can impact the vane performance. Ultimately, this study identifies specific regions of the vane that are subject to increased sensitivity, which benefits future designers intending to use AM as a tool for turbine research and development.

Non-Equal Contributions of Different Elements and Atomic Bonds to the Strength and Deformability of a Multicomponent Metallic Glass Zr47Cu46Al7

Multicomponent metallic glasses (MGs) are a fascinating class of advanced alloys known for their exceptional properties such as limit-approaching strength, high hardness and corrosion resistance, and near-net-shape castability. One important question regarding these materials that remains unanswered is how the different elements and atomic bonds within them control their strength and deformability. Here, we present a detailed visual and statistical analysis of the behaviors of various elements and atomic bonds in the Zr47Cu46Al7 (at%) MG during a uniaxial tensile test (in the z-direction) simulated using molecular dynamics. Specifically, we investigate the identities of atoms undergoing significant shear strain, and the averaged bond lengths, projected z-lengths, and z-angles (angles with respect to the z-direction) of all the atomic bonds as functions of increasing strain. We show that, prior to yielding, the Zr element and the intermediate (Zr-Zr, Cu-Al) and stronger (Zr-Al, Zr-Cu) bonds dominate the elastic deformation and strength, while the Cu and Al elements and the weaker Al-Al and Cu-Cu bonds contribute more to the highly localized shear transformation. The significant reconstruction, as signified by the cessation of bond-length increment and bond-angle decrement, of the intermediate and the stronger bonds triggers yielding of the material. After yielding, all the elements and bonds participate in the plastic deformation while the stronger bonds contribute more to the residual strength and the ultimate (fracture) strain. The results provide new insights into the atomic mechanisms underlying the mechanical behavior of multicomponent MGs, and may assist in the future design of MG compositions towards better combination of strength and deformability.

Comparing Static and Dynamic Vibration Cues in Wristband Haptic Feedback for Enhanced Driver Response in Automated Vehicles

Higher levels of driving automation make effective takeover requests critical. The wrist’s sensitivity to vibration makes wristband devices a potential carrier for sending these requests. However, the impacts of conveying takeover requests through directional vibrotactile patterns such as dynamic patterns (sequential stimuli occurring at different locations on the wrist) and static patterns (fixed stimuli at the same locations on the wrist) are unclear. Therefore, this study examined the effects of directional vibrotactile patterns on takeover performance among younger and older adults. Participants responded to four patterns (two dynamic, one static, and one baseline) in a simulated SAE Level 3 automated vehicle. Takeover performance was evaluated using reaction time and takeover time. The results show that the static and baseline patterns had shorter reaction and takeover times compared to the dynamic patterns. In addition, younger adults react faster to takeover requests compared to older adults. Findings provide important insights for the future design of human-machine interfaces via wristband devices for automated vehicles.

Critical comparison of potential machine learning methods for lightning thermal damage assessment of composite laminates

The present study assesses the potential of using machine learning (ML) methods to predict the extent of lightning thermal damage in fiber-reinforced composite laminates using three supervised machine learning (SML) algorithms: (1) linear regression (LR), (2) decision tree (DT)-based, and (3) MLP models. These models were based on the 10 most significant factors that influence the severity of lightning damage, including three current waveform parameters, four material configurations, and three orthogonal electrical conductivities of each composite. All models demonstrated good performance with coefficient of determination (R2) values between 0.84 ~ 0.96. The multilayer perceptron (MLP) regression model trained with the lightning matrix damage dataset showed the most promising results (R2 > 0.94). Additional hyperparameter optimization was performed to improve the prediction performance of the baseline MLP model. The hyperparameter optimization (Adam optimizer, tanh activation function, and three hidden layers with 234 neurons) slightly improved the performance of the baseline MLP model by ~0.02, but achieved faster convergence. This result suggests that the baseline MLP model trained with the lightning matrix damage dataset is sufficiently accurate and robust. This paper highlights that ML-informed regression models can serve as an efficient first pass-estimator of lightning matrix damage in composite laminates, potentially reducing the amount of extremely time-consuming and expensive laboratory-scale lightning tests or streamlining the development of complex lightning damage models for future design.

Binding mode of cyclic chemerin-9 peptide and chemerinS157 protein at CMKLR.

The chemokine-like receptor 1 (CMKLR1) is activated by the adipokine and chemoattractant protein chemerin. Cryo-EM structures of chemerin-9-CMKLR1-Gi have been published, where chemerin-9 is the nonapeptide of the C terminus of chemerinS157. Chemerin-9 is as active as the full-length protein in Ca2+-release but shows differences in equilibrium read-outs. An equally potent cyclic chemerin-9 variant (cC9) was reported previously. Now, we have built a computational model of CMKLR1 to investigate the binding mode of cC9 and chemerinS157 in comparison to chemerin-9. Differences were investigated using CMKLR1 variants. Double-mutant cycle analysis identified CMKLR1-F2.53 as the relevant position for Phe8-binding of cC9. Energy contribution revealed slight differences in Phe8-binding to CMKLR1-F2.53 and space for larger residues. This was confirmed as the chemerin-9 variant with 1-naphthyl-L-alanine at position 8 showed a 4-fold increased potency of 2 nM (pEC50=8.6±0.15). While chemerin-9 and cC9 share their interactions at the CMKLR1, chemerinS157 tolerates most mutations of CMKLR1 in the deep binding site. The computational model of chemerinS157 suggests a β-sheet interaction between the N-terminal CMKLR1-segment I25VVL28 and the β-sheet D108KVLGRLVH116 of ChemS157, which was confirmed experimentally. Our data expand the knowledge by identifying the binding mode of chemerinS157 and cC9 at CMKLR1 facilitating future structure-based drug design.

External Moderation of Reactor Core Neutrons for Optimized Production of Ultra-Cold Neutrons

The ultra-cold neutron (UCN) source being commissioned at North Carolina State University’s PULSTAR reactor is uniquely optimized for UCN production in the former graphite-filled thermal column outside of the reactor pool. The source utilizes a remote moderation design, which is particularly well suited to the PULSTAR reactor because of its high thermal and epithermal neutron leakage from the core face. This large non-equilibrium flux from the core is efficiently transported to the UCN source through the specially designed beam port in order to optimize UCN production at any given reactor power. The increased distance to the source from the core also greatly limits the heat load on the cryogenic system. A MCNP (Monte Carlo N-Particle) model of this system was developed and is in good agreement with gold foil activation measurements using a test configuration as well as with the real UCN source’s heavy water moderator. These results established a firm baseline for estimates of the cold neutron flux available for UCN production and prove that remote moderation in a thermal column port is a valuable option for future designs of cryogenic UCN sources.

Molecular Dynamics (MD) Simulations Provide Insights into the Activation Mechanisms of 5-HT2A Receptors

Recent breakthroughs in the determination of atomic resolution 3-D cryo-electron microscopy structures of membrane proteins present an unprecedented opportunity for drug discovery. Structure-based drug discovery utilizing in silico methods enables the study of dynamic connectivity of stable conformations induced by the drug in achieving its effect. With the ever-expanding computational power, simulations of this type reveal protein dynamics in the nano-, micro-, and even millisecond time scales. In the present study, aiming to characterize the protein dynamics of the 5HT2A receptor stimulated by ligands (agonist/antagonist), we performed 1 µs MD simulations on 5HT2A/DOI (agonist), 5HT2A/GSK215083 (antagonist), and 5HT2A (APO, no ligand) systems. The crystal structure of 5HT2A/zotepine (antagonist) (PDB: 6A94) was used to set up the simulation systems in a lipid bilayer environment. We found the monitoring of the ionic lock residue pair (R3.50-E6.30) of 5HT2A in MD simulations to be a good approximation of the effects of agonists (ionic lock breakage) or antagonists (ionic lock formation) on receptor activation. We further performed analyses of the MD trajectories, including Principal Component Analysis (PCA), hydrogen bond, salt bridge, and hydrophobic interaction network analyses, and correlation between residues to identify key elements of receptor activation. Our results suggest that in order to trigger receptor activation, DOI must interact with 5HT2A through residues V5.39, G5.42, S5.43, and S5.46 on TM5, inducing significant conformational changes in the backbone angles of G5.42 and S5.43. DOI also interacted with residues W6.48 (toggle switch) and F6.51 on TM6, causing major conformational shifts in the backbone angles of F6.44 and V6.45. These structural changes were transmitted to the intracellular ends of TM5, TM6, and ICL3, resulting in the breaking of the ionic lock and subsequent G protein activation. The studies could be helpful in future design of selective agonists/antagonists for various serotonin receptors (5HT1A, 5HT2A, 5HT2B, 5HT2C, and 5HT7) involved in detrimental disorders, such as addiction and schizophrenia.

Dual metal centers within a water-stable Co/Ni bimetallic metal-triazolate framework contribute to durable photocatalysis for water treatment.

Bimetallic metal-organic frameworks (MOFs) have been studied extensively in various fields, including photocatalytic and electrocatalytic applications. The enhanced catalytic activity is typically attributed to the synergistic effect of the two metals, often without further explanation. Here, we demonstrate a CoNi-bimetallic triazolate MOF with fixed metal occupancy within the MOF's secondary building unit. Due to the difference in electronegativity and so on, the charge redistribution between the two metal centers could be responsible for the enhanced photocatalytic activity. In addition, the metal(II)-triazolate MOFs we synthesized exhibit unique metal-N coordination and a strong bond between the metal center and triazole ring. Therefore, their crystal structure and high porosity are highly retained even after exposure to humid environments for several months or stirring in water for several days. Overall, the CoNi-bimetallic triazolate MOF combines the excellent water stability and high surface area of its two monometallic counterparts. It can be further tailored to yield the highest colloidal stability during photocatalytic water treatment. As a result, the dual metal centers within the bimetallic MOF, combined with boosted colloidal stability, demonstrate the highest reactive oxygen species generation and promising antibacterial performance compared to their Ni- or Co-based counterparts. These findings shed light on the future design of robust MOF-based photocatalysts, particularly bimetallic ones.

Enhancing Cognitive Fit: Exploring the Potential of Mixed Reality for Developing Mental Rotation Skills

Mixed Reality is a promising venue for spatial ability training, allowing participants to engage in problem-solving through gesture-based interactions with holographic objects. 3-D measurement of learning in Mixed Reality environments may result in a better cognitive fit than 2-D. This mixed-method study measures and enhances mental rotation ability and investigates user experience in Mixed Reality. To assess mental rotation ability, we adapted the Purdue Spatial Visualization Test:Rotation for Microsoft HoloLens 2, creating a measurement tool for our Mixed Reality-based training program, Holomental. Comparing 2-D and 3-D tests, we explored how stimulus dimensionality influences accuracy and cognitive load. Our findings indicate that Holomental enhances mental rotation performance, both in 2-D and 3-D. Cognitive load in the 3-D test was lower than in the 2-D test. Semi-structured interviews revealed participants’ appreciation for the representational and interactional affordances of the training environment. This study provides valuable insights into the effectiveness of 3-D spatial training, with implications and suggestions for future design considerations.

Hydromechanical properties of metachronal swimming in polychaetes

Free-swimming polychaetes are common in marine habitats and exhibit a unique form of swimming whereby a metachronal wave occurs simultaneously with a bending body wave. This body wave is unusual among swimming animals because it travels in the same direction as the animal’s swimming direction. However, we currently lack a mechanistic understanding of this unusual form of locomotion. In this study we use a combination of high-speed, high-resolution video and particle image velocimetry (PIV) to quantify kinematics and fluid dynamics for three species of swimming polychaetes, spanning two orders of magnitude in size. We find that in all species, flows generated by metachronal waves of parapodia dominate while typical flows associated with body bending is absent. However, the parapodia are less flexible than propulsive structures in other metachronal swimmers. This creates a localized, but substantial upstream flow during the recovery stroke. Using body bending, the recovery stroke can occur mostly beneath the bulk flow from the power strokes, resulting in minimal inference while the subsequent power stroke can benefit from the pressure field generated during recovery. These results may have implications for future vehicle designs that incorporate metachronal locomotion.

Lenvatinib Plus Ifosfamide and Etoposide in Children and Young Adults With Relapsed Osteosarcoma

The combination of ifosfamide and etoposide (IE) is commonly used to treat relapsed or refractory osteosarcoma; however, second-line treatment recommendations vary across guidelines. To evaluate whether the addition of lenvatinib to IE (LEN-IE) improves outcomes in children and young adults with relapsed or refractory osteosarcoma. The OLIE phase II, open-label, randomized clinical trial was conducted globally across Europe, Asia and the Pacific, and North America. From March 22, 2020, through November 11, 2021, the trial enrolled patients aged 2 to 25 years with high-grade osteosarcoma, measurable or evaluable disease per Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST 1.1), and 1 to 2 prior lines of systemic treatment. The data analyses were performed between March 22, 2020 (first patient in) and June 22, 2022 (data cutoff for the primary analysis), and September 29, 2023 (end of study final database lock). The OLIE trial assessed the efficacy and safety of lenvatinib (14 mg/m2 taken orally once daily) combined with up to 5 cycles of ifosfamide (3000 mg/m2 intravenously) and etoposide (100 mg/m2 intravenously) on days 1 to 3 of each cycle vs IE alone at the same doses. Patients randomized to IE could cross over to receive lenvatinib upon disease progression by independent imaging review. The primary end point was progression-free survival (PFS) per RECIST 1.1 by independent imaging review. The Kaplan-Meier method was used to estimate the PFS distribution, with a prespecified 1-sided significance threshold of .025 by stratified log-rank test. Secondary end points included PFS rate at 4 months and overall survival. Adverse events were summarized using descriptive statistics. A total of 81 patients were enrolled (median [IQR] age, 15.0 [12.0-18.0] years; 46 males [56.8%]), with 40 in the LEN-IE arm and 41 in the IE arm. Median PFS was 6.5 months (95% CI, 5.7-8.2 months) for the LEN-IE arm and 5.5 months (95% CI, 2.9-6.5 months) for the IE arm (hazard ratio [HR], 0.54; 95% CI, 0.27-1.08; 1-sided P = .04). The rate of PFS at 4 months was 76.3% (95% CI, 59.3%-86.9%) in the LEN-IE arm and 66.0% (95% CI, 47.7%-79.2%) in the IE arm. Median overall survival was 11.9 months (95% CI, 10.1 months to not estimable) with LEN-IE and 17.4 months (95% CI, 14.2 months to not estimable) with IE (HR, 1.28; 95% CI, 0.60-2.70; 1-sided nominal P = .75). Grade 3 or higher treatment-related adverse events occurred in 35 of 39 patients (89.7%) in the LEN-IE arm and 31 of 39 patients (79.5%) in the IE arm. Although LEN-IE did not meet prespecified statistical significance for improved PFS vs IE, this study demonstrates the importance of international collaboration and randomized clinical trials in patients with relapsed or refractory osteosarcoma and may inform future trial design. ClinicalTrials.gov Identifier: NCT04154189.

Multiple sclerosis subgroups: Data-driven clusters based on patient-reported outcomes and a large clinical sample.

While standard clinical assessments provide great value for people with multiple sclerosis (PwMS), they are limited in their ability to characterize patient perspectives and individual-level symptom heterogeneity. To identify PwMS subgroups based on patient-reported outcomes (PROs) of physical, cognitive, and emotional symptoms. We also sought to connect PRO-based subgroups with demographic variables, functional impairment, hypertension and smoking status, traditional qualitative multiple sclerosis (MS) symptom groupings, and neuroperformance measurements. Using a cross-sectional design, we applied latent profile analysis (LPA) to a large database of PROs; analytic sample N = 6619). We identified nine distinct MS subtypes based on PRO patterns. The subtypes were primarily categorized into low, moderate, and high mobility impairment clusters. Approximately 70% of participants were classified in a low mobility impairment group, 10% in a moderate mobility impairment group, and 20% in a high mobility impairment group. Within these subgroups, several unexpected patterns were observed, such as high mobility impairment clusters reporting low non-mobility impairment. The present study highlights an opportunity to advance precision medicine approaches in MS. Combining PROs with data-driven methodology allows for a cost-effective and personalized characterization of symptom presentations. that can inform clinical practice and future research designs.

Alzheimer's disease and other memory disorders in the age of AI: reflection and perspectives on the 120th anniversary of the birth of Dr. John von Neumann.

Two themes are coming to the forefront in this decade: Cognitive impairment of an aging population and the quantum leap in developing artificial intelligence (AI). Both can be described as growing exponentially and presenting serious challenges. Although many questions have been addressed about the dangers of AI, we want to go beyond the fearful aspects of this topic and focus on the possible contribution of AI to solve the problem of chronic disorders of the elderly leading to cognitive impairment, like Alzheimer's disease, Parkinson's disease, and Lewy body dementia. Our second goal is to look at the ways in which modern neuroscience can influence the future design of computers and the development of AI. We wish to honor the memory of Dr. John von Neumann, who came up with many breakthrough details of the first electronic computer. Remarkably, Dr. von Neumann dedicated his last book to the comparison of the human brain and the computer as it stood in those years of the mid-1950s. We will point out how his ideas are more relevant than ever in the age of supercomputers, AI and brain implants.

Toward Finding the Role of Surface Iron Ions in Enhancing Oxygen-Evolution Reaction.

The oxygen evolution reaction (OER) in alkaline media is crucial for energy conversion technologies, and Fe-based catalysts have garnered significant attention for their efficacy. In this study, we provide an investigation of Fe-based catalysts under OER conditions using some techniques. Our findings reveal minimal structural alterations in the bulk FeHxOy framework during OER, indicating that the bulk structure remains largely intact. Instead, the catalytic activity is primarily localized on the material's surface. This conclusion is corroborated by the measured low electrochemical surface area (ECSA) of FeHxOy, suggesting that its limited OER performance stems from a paucity of active sites rather than low intrinsic activity. The superior efficiency of Fe ions in conductive oxides or on conductive metal substrates (e.g., copper and gold) in OER is attributed to the increased availability of surface-active sites in these systems. To further elucidate this phenomenon, we investigated two additional systems: NiFe and VFe (hydr)oxides. For NiFe (hydr)oxides, we demonstrate that only surface Fe ions contribute actively to OER. In contrast, in VFe (hydr)oxides, the removal of vanadium resulted in a marked increase in ECSA and the generation of defect sites, significantly enhancing OER activity. These findings provide critical insights into the surface-specific role of Fe ions in catalytic activity and could inform future design strategies for more efficient OER catalysts by optimizing the availability and reactivity of surface-active Fe sites.