Sensitivity volume as figure-of-merit for maximizing data importance in electrical impedance tomography.

Objective.Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the periphery of a heterogeneous conductor are inverted to map its internal conductivity. The EIT method proposed here aims to improve computational speed and noise tolerance by introducing sensitivity volume as a figure-of-merit for comparing EIT measurement protocols.Approach.Each measurement is shown to correspond to a sensitivity vector in model space, such that the set of measurements, in turn, corresponds to a set of vectors that subtend a sensitivity volume in model space. A maximal sensitivity volume identifies the measurement protocol with the greatest sensitivity and greatest mutual orthogonality. A distinguishability criterion is generalized to quantify the increased noise tolerance of high sensitivity measurements.Main result.The sensitivity volume method allows the model space dimension to be minimized to match that of the data space, and the data importance to be increased within an expanded space of measurements defined by an increased number of contacts.Significance.The reduction in model space dimension is shown to increasecomputational efficiency, accelerating tomographic inversion by several orders of magnitude, while the enhanced sensitivitytolerates higher noiselevels up to several orders of magnitude larger than standard methods.

Implications and Optimization of Domain Structures in IV-VI High-Entropy Thermoelectric Materials.

High-entropy semiconductors are now an important class of materials widely investigated for thermoelectric applications. Understanding the impact of chemical and structural heterogeneity on transport properties in these compositionally complex systems is essential for thermoelectric design. In this work, we uncover the polar domain structures in the high-entropy PbGeSnSe1.5Te1.5 system and assess their impact on thermoelectric properties. We found that polar domains induced by crystal symmetry breaking give rise to well-structured alternating strain fields. These fields effectively disrupt phonon propagation and suppress the thermal conductivity. We demonstrate that the polar domain structures can be modulated by tuning crystal symmetry through entropy engineering in PbGeSnAgxSbxSe1.5+xTe1.5+x. Incremental increases in the entropy enhance the crystal symmetry of the system, which suppresses domain formation and loses its efficacy in suppressing phonon propagation. As a result, the room-temperature lattice thermal conductivity increases from κL = 0.63 Wm-1 K-1 (x = 0) to 0.79 Wm-1 K-1 (x = 0.10). In the meantime, the increase in crystal symmetry, however, leads to enhanced valley degeneracy and improves the weighted mobility from µw = 29.6 cm2 V-1 s-1 (x = 0) to 35.8 cm2 V-1 s-1 (x = 0.10). As such, optimal thermoelectric performance can be achieved through entropy engineering by balancing weighted mobility and lattice thermal conductivity. This work, for the first time, studies the impact of polar domain structures on thermoelectric properties, and the developed understanding of the intricate interplay between crystal symmetry, polar domains, and transport properties, along with the impact of entropy control, provides valuable insights into designing GeTe-based high-entropy thermoelectrics.

Electrically Controlled All-Antiferromagnetic Tunnel Junctions on Silicon with Large Room-Temperature Magnetoresistance.

Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and reading of information, which are also compatible with established silicon-based manufacturing. Recent experiments have shown tunneling magnetoresistance (TMR) readout in epitaxial AFM tunnel junctions. However, these TMR structures are not grown using a silicon-compatible deposition process, and controlling their AFM order required external magnetic fields. Here it is shown three-terminal AFM tunnel junctions based on the noncollinear antiferromagnet PtMn3 , sputter-deposited on silicon. The devices simultaneously exhibit electrical switching using electric currents, and electrical readout by a large room-temperature TMR effect. First-principles calculations explain the TMR in terms of the momentum-resolved spin-dependent tunneling conduction in tunnel junctions with noncollinear AFM electrodes.

Reformulating Reactivity Design for Data-Efficient Machine Learning.

Machine learning (ML) can deliver rapid and accurate reaction barrier predictions for use in rational reactivity design. However, model training requires large data sets of typically thousands or tens of thousands of barriers that are very expensive to obtain computationally or experimentally. Furthermore, bespoke data sets are required for each region of interest in reaction space as models typically struggle to generalize. We have therefore reformulated the ML barrier prediction problem toward a much more data-efficient process: finding a reaction from a prespecified set with a desired target value. Our reformulation enables the rapid selection of reactions with purpose-specific activation barriers, for example, in the design of reactivity and selectivity in synthesis, catalyst design, toxicology, and covalent drug discovery, requiring just tens of accurately measured barriers. Importantly, our reformulation does not require generalization beyond the domain of the data set at hand, and we show excellent results for the highly toxicologically and synthetically relevant data sets of aza-Michael addition and transition-metal-catalyzed dihydrogen activation, typically requiring less than 20 accurately measured density functional theory (DFT) barriers. Even for incomplete data sets of E2 and SN2 reactions, with high numbers of missing barriers (74% and 56% respectively), our chosen ML search method still requires significantly fewer data points than the hundreds or thousands needed for more conventional uses of ML to predict activation barriers. Finally, we include a case study in which we use our process to guide the optimization of the dihydrogen activation catalyst. Our approach was able to identify a reaction within 1 kcal mol-1 of the target barrier by only having to run 12 DFT reaction barrier calculations, which illustrates the usage and real-world applicability of this reformulation for systems of high synthetic importance.

Photoredox-HAT Catalysis for Primary Amine α-C-H Alkylation: Mechanistic Insight with Transient Absorption Spectroscopy.

The synergistic use of (organo)photoredox catalysts with hydrogen-atom transfer (HAT) cocatalysts has emerged as a powerful strategy for innate C(sp3)-H bond functionalization, particularly for C-H bonds α- to nitrogen. Azide ion (N3-) was recently identified as an effective HAT catalyst for the challenging α-C-H alkylation of unprotected, primary alkylamines, in combination with dicyanoarene photocatalysts such as 1,2,3,5-tetrakis(carbazol-9-yl)-4,6-dicyanobenzene (4CzIPN). Here, time-resolved transient absorption spectroscopy over sub-picosecond to microsecond timescales provides kinetic and mechanistic details of the photoredox catalytic cycle in acetonitrile solution. Direct observation of the electron transfer from N3- to photoexcited 4CzIPN reveals the participation of the S1 excited electronic state of the organic photocatalyst as an electron acceptor, but the N3• radical product of this reaction is not observed. Instead, both time-resolved infrared and UV-visible spectroscopic measurements implicate rapid association of N3• with N3- (a favorable process in acetonitrile) to form the N6•- radical anion. Electronic structure calculations indicate that N3• is the active participant in the HAT reaction, suggesting a role for N6•- as a reservoir that regulates the concentration of N3•.

Realizing the Heteromorphic Superlattice: Repeated Heterolayers of Amorphous Insulator and Polycrystalline Semiconductor with Minimal Interface Defects.

An unconventional "heteromorphic" superlattice (HSL) is realized, comprised of repeated layers of different materials with differing morphologies: semiconducting pc-In2 O3 layers interleaved with insulating a-MoO3 layers. Originally proposed by Tsu in 1989, yet never fully realized, the high quality of the HSL heterostructure demonstrated here validates the intuition of Tsu, whereby the flexibility of the bond angle in the amorphous phase and the passivation effect of the oxide at interfacial bonds serve to create smooth, high-mobility interfaces. The alternating amorphous layers prevent strain accumulation in the polycrystalline layers while suppressing defect propagation across the HSL. For the HSL with 7:7 nm layer thickness, the observed electron mobility of 71 cm2  Vs-1 , matches that of the highest quality In2 O3 thin films. The atomic structure and electronic properties of crystalline In2 O3 /amorphous MoO3 interfaces are verified using ab-initio molecular dynamics simulations and hybrid functional calculations. This work generalizes the superlattice concept to an entirely new paradigm of morphological combinations.

Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection.

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group, which makes rapid detection challenging. We have previously shown that fluorescence spectral fingerprinting (FSF) has the potential to provide rapid assessment of SCRA presence directly from street material with minimal processing and in saliva. Enhancing the sensitivity and discriminatory ability of this approach has high potential to accelerate the delivery of a point-of-care technology that can be used confidently by a range of stakeholders, from medical to prison staff. We demonstrate that a range of structurally distinct SCRAs are photochemically active and give rise to distinct FSFs after irradiation. To explore this in detail, we have synthesized a model series of compounds which mimic specific structural features of AM-694. Our data show that FSFs are sensitive to chemically conservative changes, with evidence that this relates to shifts in the electronic structure and cross-conjugation. Crucially, we find that the photochemical degradation rate is sensitive to individual structures and gives rise to a specific major product, the mechanism and identification of which we elucidate through density-functional theory (DFT) and time-dependent DFT. We test the potential of our hybrid "photochemical fingerprinting" approach to discriminate SCRAs by demonstrating SCRA detection from a simulated smoking apparatus in saliva. Our study shows the potential of tracking photochemical reactivity via FSFs for enhanced discrimination of SCRAs, with successful integration into a portable device.

Atom and step economical synthesis of acyclic quaternary centers via iridium-catalyzed hydroarylative cross-coupling of 1,1-disubstituted alkenes.

Quaternary benzylic centers are accessed with high atom and step economy by Ir-catalyzed alkene hydroarylation. These studies provide unique examples of the use of non-polarized 1,1-disubstituted alkenes in branch selective Murai-type hydro(hetero)arylations. Detailed mechanistic studies have been undertaken, and these indicate that the first irreversible step is the demanding alkene carbometallation process. Structure-reactivity studies show that the efficiency of this is critically dependent on key structural features of the ligand. Computational studies have been undertaken to rationalize this experimental data, showing how more sterically demanding ligands reduce the reaction barrier via predistortion of the reacting intermediate. The key insight disclosed here will underpin the ongoing development of increasingly sophisticated branch selective Murai hydroarylations.

Eliminating Transition State Calculations for Faster and More Accurate Reactivity Prediction in Sulfa-Michael Additions Relevant to Human Health and the Environment.

Fast and accurate computational approaches to predicting reactivity in sulfa-Michael additions are required for high-throughput screening in toxicology (e.g., predicting excess aquatic toxicity and skin sensitization), chemical synthesis, covalent drug design (e.g., targeting cysteine), and data set generation for machine learning. The kinetic glutathione chemoassay is a time-consuming in chemico method used to extract kinetic data in the form of log(k GSH) for organic electrophiles. In this work, we use density functional theory to compare the use of transition states (TSs) and enolate intermediate structures following C-S bond formation in the prediction of log(k GSH) for a diverse group of 1,4 Michael acceptors. Despite the widespread use of transition state calculations in the literature to predict sulfa-Michael reactivity, we observe that intermediate structures show much better performance for the prediction of log(k GSH), are faster to calculate, and easier to obtain than TSs. Furthermore, we show how linear combinations of atomic charges from the isolated Michael acceptors can further improve predictions, even when using inexpensive semiempirical quantum chemistry methods. Our models can be used widely in the chemical sciences (e.g., in the prediction of toxicity relevant to the environment and human health, synthesis planning, and the design of cysteine-targeting covalent inhibitors), and represent a low-cost, sustainable approach to reactivity assessment.

B(C6 F5 )3 -Catalyzed E-Selective Isomerization of Alkenes.

Herein, we report the B(C6 F5 )3 -catalyzed E-selective isomerization of alkenes. The transition-metal-free method is applicable across a diverse array of readily accessible substrates, giving access to a broad range of synthetically useful products containing versatile stereodefined internal alkenes. The reaction mechanism was investigated by using synthetic and computational methods.

Machine learning and semi-empirical calculations: a synergistic approach to rapid, accurate, and mechanism-based reaction barrier prediction.

Modern QM modelling methods, such as DFT, have provided detailed mechanistic insights into countless reactions. However, their computational cost inhibits their ability to rapidly screen large numbers of substrates and catalysts in reaction discovery. For a C-C bond forming nitro-Michael addition, we introduce a synergistic semi-empirical quantum mechanical (SQM) and machine learning (ML) approach that allows the prediction of DFT-quality reaction barriers in minutes, even on a standard laptop using widely available modelling software. Mean absolute errors (MAEs) are obtained that are below the accepted chemical accuracy threshold of 1 kcal mol-1 and substantially better than SQM methods without ML correction (5.71 kcal mol-1). Predictive power is shown to hold when the ML models are applied to an unseen set of compounds from the toxicology literature. Mechanistic insight is also achieved via the generation of full SQM transition state (TS) structures which are found to be very good approximations for the DFT-level geometries, revealing important steric interactions in some TSs. This combination of speed, accuracy, and mechanistic insight is unprecedented; current ML barrier models compromise on at least one of these important criteria.

Noncovalent Interactions in the Oxazaborolidine-Catalyzed Enantioselective Mukaiyama Aldol.

Current models for oxazaborolidine-catalyzed transition-state structures are determined by C-H···O-B and C-H···O═S formyl hydrogen bonding between the electrophile and catalyst. However, selectivity in the oxazaborolidine-catalyzed Mukaiyama aldol cannot be fully rationalized using these models. Combined density functional theory and noncovalent interaction analyses reveal a new reaction model relying on C-H···O, C-H···π, and π-π interactions between the nucleophile, electrophile, and catalyst to induce selectivity.

Iron-Catalyzed H/D Exchange of Primary Silanes, Secondary Silanes, and Tertiary Siloxanes.

A synthetic study into the catalytic hydrogen/deuterium (H/D) exchange of 1° silanes, 2° silanes, and 3° siloxanes is presented, facilitated by iron-ß-diketiminato complexes (1a and 1b). Near-complete H/D exchange is observed for a variety of aryl- and alkyl-containing hydrosilanes and hydrosiloxanes. The reaction tolerates alternative hydride source pinacolborane (HBpin), with quantitative H/D exchange. A synthetic and density functional theory (DFT) investigation suggests that a monomeric iron-deuteride is responsible for the H/D exchange.

Comparing the Performances of Force Fields in Conformational Searching of Hydrogen-Bond-Donating Catalysts.

Here, we compare the relative performances of different force fields for conformational searching of hydrogen-bond-donating catalyst-like molecules. We assess the force fields by their predictions of conformer energies, geometries, low-energy, nonredundant conformers, and the maximum numbers of possible conformers. Overall, MM3, MMFFs, and OPLS3e had consistently strong performances and are recommended for conformationally searching molecules structurally similar to those in this study.

Organocatalytic Enantioselective Sulfa-Michael Additions to α,ß-Unsaturated Diazoketones.

Enantioselective sulfa-Michael additions to α,ß unsaturated diazocarbonyl compounds have been developed. Quinine-derived squaramide was found to be the best catalyst to promote C-S bond formation in a highly stereoselective fashion for alkyl and aryl thiols. The easy-to-follow protocol allowed the preparation of 22 examples in enantiomeric ratios up to 97:3 and reaction yields up to 94%. The mechanism and origins of enantioselectivity were determined through density functional theory (DFT) calculations.

Chiral Phosphoric Acid Catalysis: The Terada Model Revisited.

Since Akiyama and Terada independently reported the introduction of chiral phosphoric acids (CPAs) as effective catalysts for Mannich-type reactions in 2004, the field of CPA catalysis has grown immensely. Terada reported in 2008 the first example of the activation of aldehydes by a CPA. Based on density functional theory (DFT) calculations, Terada proposed a dual activation mode for this enantioselective aza-ene-type reaction between an aldehyde and an enecarbamate. In this model, hydrogen bonds between the catalyst's hydroxyl group and the carbonyl oxygen and the catalyst's P═O and the formyl proton were observed; the nucleophile then attacks without coordination to the catalyst. This reaction model provided the mechanistic basis for understanding Terada's reaction and many other asymmetric transformations. In the present study, DFT calculations are reported that identify a lower-energy mechanism for this landmark reaction. In this new model, hydrogen bonds between the catalyst's hydroxyl group and the aldehyde oxygen and the catalyst's P═O and the NH group of the enecarbamate are seen. The new model rationalizes the stereoselective outcome of Terada's reaction and offers insight into why a more sterically demanding catalyst gives lower levels of enantioselectivity.

A molecular communication channel consisting of a single reversible chain of hydrogen bonds in a conformationally flexible oligomer.

Communication of information through the global switching of conformation in synthetic molecules has hitherto entailed the inversion of chirality. Here, we report a class of oligomer through which information may be communicated through a global reversal of polarity. Ethylene-bridged oligoureas are constitutionally symmetrical, conformationally flexible molecules organized by a single chain of hydrogen bonds running the full length of the oligomer. NMR reveals that this hydrogen-bonded chain may undergo a coherent reversal of directionality. The directional uniformity of the hydrogen-bond chain allows it to act as a channel for the spatial communication of information on a molecular scale. A binding site at the terminus of an oligomer detects local information about changes in pH or anion concentration and transmits that information-in the form of a directionality switch in the hydrogen-bond chain-to a remote polarity-sensitive fluorophore. This propagation of polarity-encoded information provides a new mechanism for molecular communication.

Observation of current-induced switching in non-collinear antiferromagnetic IrMn3 by differential voltage measurements.

There is accelerating interest in developing memory devices using antiferromagnetic (AFM) materials, motivated by the possibility for electrically controlling AFM order via spin-orbit torques, and its read-out via magnetoresistive effects. Recent studies have shown, however, that high current densities create non-magnetic contributions to resistive switching signals in AFM/heavy metal (AFM/HM) bilayers, complicating their interpretation. Here we introduce an experimental protocol to unambiguously distinguish current-induced magnetic and nonmagnetic switching signals in AFM/HM structures, and demonstrate it in IrMn3/Pt devices. A six-terminal double-cross device is constructed, with an IrMn3 pillar placed on one cross. The differential voltage is measured between the two crosses with and without IrMn3 after each switching attempt. For a wide range of current densities, reversible switching is observed only when write currents pass through the cross with the IrMn3 pillar, eliminating any possibility of non-magnetic switching artifacts. Micromagnetic simulations support our findings, indicating a complex domain-mediated switching process.

Understanding the mechanism of the chiral phosphoric acid-catalyzed aza-Cope rearrangement.

The first catalytic enantioselective aza-Cope rearrangement was reported in 2008 by Rueping et al. The reaction is catalyzed by a 1,1'-bi-2-naphthol-derived (BINOL-derived) phosphoric acid and achieved high yields and enantioselectivities (up to 97 : 3 er with 75% yield). This work utilizes Density Functional Theory to understand the mechanism of the reaction and explain the origins of the enantioselectivity. An extensive conformational search was carried out to explore the different activation modes by the catalyst and, the Transition State (TS) leading to the major product was found to be 1.3 kcal mol-1 lower in energy than the TS leading to the minor product. The origin of this stabilization was rationalized with NBO and NCI analysis: it was found that the major TS has a greater number of non-bonding interactions between the substrate and the catalyst, and shows stronger H-bond interactions between H atoms in the substrate and the O atoms in the phosphate group of the catalyst.

Amorphous to Crystal Phase Change Memory Effect with Two-Fold Bandgap Difference in Semiconducting K2Bi8Se13.

Chalcogenide-based phase change memory (PCM) is a key enabling technology for optical data storage and electrical nonvolatile memory. Here, we report a new phase change chalcogenide consisting of a 3D network of ionic (K···Se) and covalent bonds (Bi-Se), K2Bi8Se13 (KBS). Thin films of amorphous KBS deposited by DC sputtering are structurally and chemically homogeneous and exhibit a surface roughness of 5 nm. The KBS film crystallizes upon heating at ∼483 K. The optical bandgap of the amorphous film is about 1.25 eV, while its crystalline phase has a bandgap of ∼0.65 eV shows 2-fold difference between the two states. The bulk electrical conductivity of the amorphous and crystalline film is ∼7.5 × 10-4 and ∼2.7 × 10-2 S/cm, respectively. We have demonstrated a phase change memory effect in KBS by Joule heating in a technologically relevant vertical memory cell architecture. Upon Joule heating, the vertical device undergoes switching from its amorphous to crystalline state of KBS at 1-1.5 V (∼50 kV/cm), increasing conductivity by a factor of ∼40. Besides the large electrical and optical contrast in the crystalline and amorphous KBS, its elemental cost-effectiveness, stoichiometry, fast crystallization kinetics, as determined by the ratio of the glass transition and melting temperature, Tg/Tm ∼ 0.5, as well as the scalable synthesis of the thin film determine that KBS is a promising PC material for next general phase change memory.