A heterometallic [LnLn′Ln] lanthanide complex as a qubit with embedded quantum error correction

We show that a [Er–Ce–Er] molecular trinuclear coordination compound is a promising platform to implement the three-qubit quantum error correction code protecting against pure dephasing, the most important error in magnetic molecules. We characterize it by preparing the [Lu–Ce–Lu] and [Er–La–Er] analogues, which contain only one of the two types of qubit, and by combining magnetometry, low-temperature specific heat and electron paramagnetic resonance measurements on both the elementary constituents and the trimer. Using the resulting parameters, we demonstrate by numerical simulations that the proposed molecular device can efficiently suppress pure dephasing of the spin qubits.

We show that a [Er–Ce–Er] molecular trinuclear coordination compound is a promising platform to implement the three-qubit quantum error correction code protecting against pure dephasing, the most important error in magnetic molecules.     

Controlled coherent dynamics of [VO(TPP)], a prototype molecular nuclear qudit with an electronic ancilla

We show that [VO(TPP)] (vanadyl tetraphenylporphyrinate) is a promising system to implement quantum computation algorithms based on encoding information in multi-level (qudit) units. Indeed, it embeds a nuclear spin 7/2 coupled to an electronic spin 1/2 by hyperfine interaction. This qubit–qudit unit can be exploited to implement quantum error correction and quantum simulation algorithms. Through a combined theoretical and broadband nuclear magnetic resonance study, we demonstrate that the elementary operations of such algorithms can be efficiently implemented on the nuclear spin qudit. Manipulation of the nuclear qudit can be achieved by resonant radio-frequency pulses, thanks to the remarkably long coherence times and the effective quadrupolar coupling induced by the strong hyperfine interaction. This approach may open new perspectives for developing new molecular qubit–qudit systems.

By a combined theoretical and broadband nuclear magnetic resonance study, we show that [VOTPP] is a coupled electronic qubit-nuclear qudit system suitable to implement qudit-based quantum error correction and quantum simulation algorithms.     

Dye-sensitized solar cells based on Fe N-heterocyclic carbene photosensitizers with improved rod-like push-pull functionality

A new generation of octahedral iron(ii)–N-heterocyclic carbene (NHC) complexes, employing different tridentate C^N^C ligands, has been designed and synthesized as earth-abundant photosensitizers for dye sensitized solar cells (DSSCs) and related solar energy conversion applications. This work introduces a linearly aligned push–pull design principle that reaches from the ligand having nitrogen-based electron donors, over the Fe(ii) centre, to the ligand having an electron withdrawing carboxylic acid anchor group. A combination of spectroscopy, electrochemistry, and quantum chemical calculations demonstrate the improved molecular excited state properties in terms of a broader absorption spectrum compared to the reference complex, as well as directional charge-transfer displacement of the lowest excited state towards the semiconductor substrate in accordance with the push–pull design. Prototype DSSCs based on one of the new Fe NHC photosensitizers demonstrate a power conversion efficiency exceeding 1% already for a basic DSSC set-up using only the I⁻/I₃⁻ redox mediator and standard operating conditions, outcompeting the corresponding DSSC based on the homoleptic reference complex. Transient photovoltage measurements confirmed that adding the co-sensitizer chenodeoxycholic acid helped in improving the efficiency by increasing the electron lifetime in TiO₂. Time-resolved spectroscopy revealed spectral signatures for successful ultrafast (<100 fs) interfacial electron injection from the heteroleptic dyes to TiO₂. However, an ultrafast recombination process results in undesirable fast charge recombination from TiO₂ back to the oxidized dye, leaving only 5–10% of the initially excited dyes available to contribute to a current in the DSSC. On slower timescales, time-resolved spectroscopy also found that the recombination dynamics (longer than 40 μs) were significantly slower than the regeneration of the oxidized dye by the redox mediator (6–8 μs). Therefore it is the ultrafast recombination down to fs-timescales, between the oxidized dye and the injected electron, that remains as one of the main bottlenecks to be targeted for achieving further improved solar energy conversion efficiencies in future work.

Iron-based photosensitizers for dye-sensitized solar cells with a rod-like push–pull design. Solar cell performance was limited by ultrafast (sub-ps) recombination, but yielded better performance than the homoleptic parent photosensitizer.     

Manifold dynamic non-covalent interactions for steering molecular assembly and cyclization

Deciphering rich non-covalent interactions that govern many chemical and biological processes is crucial for the design of drugs and controlling molecular assemblies and their chemical transformations. However, real-space characterization of these weak interactions in complex molecular architectures at the single bond level has been a longstanding challenge. Here, we employed bond-resolved scanning probe microscopy combined with an exhaustive structural search algorithm and quantum chemistry calculations to elucidate multiple non-covalent interactions that control the cohesive molecular clustering of well-designed precursor molecules and their chemical reactions. The presence of two flexible bromo-triphenyl moieties in the precursor leads to the assembly of distinct non-planar dimer and trimer clusters by manifold non-covalent interactions, including hydrogen bonding, halogen bonding, C–H⋯π and lone pair⋯π interactions. The dynamic nature of weak interactions allows for transforming dimers into energetically more favourable trimers as molecular density increases. The formation of trimers also facilitates thermally-triggered intermolecular Ullmann coupling reactions, while the disassembly of dimers favours intramolecular cyclization, as evidenced by bond-resolved imaging of metalorganic intermediates and final products. The richness of manifold non-covalent interactions offers unprecedented opportunities for controlling the assembly of complex molecular architectures and steering on-surface synthesis of quantum nanostructures.

A real-space characterization of dynamic non-covalent interactions in molecular assemblies and chemical reactions at the atomic bond level.     

Machine learning of solvent effects on molecular spectra and reactions

Fast and accurate simulation of complex chemical systems in environments such as solutions is a long standing challenge in theoretical chemistry. In recent years, machine learning has extended the boundaries of quantum chemistry by providing highly accurate and efficient surrogate models of electronic structure theory, which previously have been out of reach for conventional approaches. Those models have long been restricted to closed molecular systems without accounting for environmental influences, such as external electric and magnetic fields or solvent effects. Here, we introduce the deep neural network FieldSchNet for modeling the interaction of molecules with arbitrary external fields. FieldSchNet offers access to a wealth of molecular response properties, enabling it to simulate a wide range of molecular spectra, such as infrared, Raman and nuclear magnetic resonance. Beyond that, it is able to describe implicit and explicit molecular environments, operating as a polarizable continuum model for solvation or in a quantum mechanics/molecular mechanics setup. We employ FieldSchNet to study the influence of solvent effects on molecular spectra and a Claisen rearrangement reaction. Based on these results, we use FieldSchNet to design an external environment capable of lowering the activation barrier of the rearrangement reaction significantly, demonstrating promising venues for inverse chemical design.

A machine learning approach for modeling the influence of external environments and fields on molecules has been developed, which allows the prediction of various types of molecular spectra in vacuum and under implicit and explicit solvation.     

A novel chemical biology and computational approach to expedite the discovery of new-generation polymyxins against life-threatening Acinetobacter baumannii

Multidrug-resistant Gram-negative bacteria represent a major medical challenge worldwide. New antibiotics are desperately required with ‘old’ polymyxins often being the only available therapeutic option. Here, we systematically investigated the structure–activity relationship (SAR) of polymyxins using a quantitative lipidomics-informed outer membrane (OM) model of Acinetobacter baumannii and a series of chemically synthesized polymyxin analogs. By integrating chemical biology and all-atom molecular dynamics simulations, we deciphered how each residue of the polymyxin molecule modulated its conformational folding and specific interactions with the bacterial OM. Importantly, a novel designed polymyxin analog FADDI-287 with predicted stronger OM penetration showed improved in vitro antibacterial activity. Collectively, our study provides a novel chemical biology and computational strategy to expedite the discovery of new-generation polymyxins against life-threatening Gram-negative ‘superbugs’.

Multidrug-resistant Gram-negative bacteria have been an urgent threat to global public health. Novel antibiotics are desperately needed to combat these ''superbugs''.     

A transferable active-learning strategy for reactive molecular force fields

Predictive molecular simulations require fast, accurate and reactive interatomic potentials. Machine learning offers a promising approach to construct such potentials by fitting energies and forces to high-level quantum-mechanical data, but doing so typically requires considerable human intervention and data volume. Here we show that, by leveraging hierarchical and active learning, accurate Gaussian Approximation Potential (GAP) models can be developed for diverse chemical systems in an autonomous manner, requiring only hundreds to a few thousand energy and gradient evaluations on a reference potential-energy surface. The approach uses separate intra- and inter-molecular fits and employs a prospective error metric to assess the accuracy of the potentials. We demonstrate applications to a range of molecular systems with relevance to computational organic chemistry: ranging from bulk solvents, a solvated metal ion and a metallocage onwards to chemical reactivity, including a bifurcating Diels–Alder reaction in the gas phase and non-equilibrium dynamics (a model S_N2 reaction) in explicit solvent. The method provides a route to routinely generating machine-learned force fields for reactive molecular systems.

An efficient strategy for training Gaussian Approximation Potential (GAP) models to study chemical reactions using hierarchical and active learning.     

Fitting quantum machine learning potentials to experimental free energy data: predicting tautomer ratios in solution

The computation of tautomer ratios of druglike molecules is enormously important in computer-aided drug discovery, as over a quarter of all approved drugs can populate multiple tautomeric species in solution. Unfortunately, accurate calculations of aqueous tautomer ratios—the degree to which these species must be penalized in order to correctly account for tautomers in modeling binding for computer-aided drug discovery—is surprisingly difficult. While quantum chemical approaches to computing aqueous tautomer ratios using continuum solvent models and rigid-rotor harmonic-oscillator thermochemistry are currently state of the art, these methods are still surprisingly inaccurate despite their enormous computational expense. Here, we show that a major source of this inaccuracy lies in the breakdown of the standard approach to accounting for quantum chemical thermochemistry using rigid rotor harmonic oscillator (RRHO) approximations, which are frustrated by the complex conformational landscape introduced by the migration of double bonds, creation of stereocenters, and introduction of multiple conformations separated by low energetic barriers induced by migration of a single proton. Using quantum machine learning (QML) methods that allow us to compute potential energies with quantum chemical accuracy at a fraction of the cost, we show how rigorous relative alchemical free energy calculations can be used to compute tautomer ratios in vacuum free from the limitations introduced by RRHO approximations. Furthermore, since the parameters of QML methods are tunable, we show how we can train these models to correct limitations in the underlying learned quantum chemical potential energy surface using free energies, enabling these methods to learn to generalize tautomer free energies across a broader range of predictions.

We show how alchemical free energies can be calculated with QML potentials to identify deficiencies in RRHO approximations for computing tautomeric free energies, and how these potentials can be learned from experiment to improve prediction accuracy.     

Linking metal–organic cages pairwise as a design approach for assembling multivariate crystalline materials

Using metal–organic cages (MOCs) as preformed supermolecular building-blocks (SBBs) is a powerful strategy to design functional metal–organic frameworks (MOFs) with control over the pore architecture and connectivity. However, introducing chemical complexity into the network via this route is limited as most methodologies focus on only one type of MOC as the building-block. Herein we present the pairwise linking of MOCs as a design approach to introduce defined chemical complexity into porous materials. Our methodology exploits preferential Rh-aniline coordination and stoichiometric control to rationally link Cu₄L₄ and Rh₄L₄ MOCs into chemically complex, yet extremely well-defined crystalline solids. This strategy is expected to open up significant new possibilities to design bespoke multi-functional materials with atomistic control over the location and ordering of chemical functionalities.

A new strategy to design atomically precise multivariate metal–organic frameworks is presented. This is achieved by linking two preformed metal–organic cages via a precisely tuned Rh–aniline interaction.     

The development of a comprehensive toolbox based on multi-level,high-throughput screening of MOFs for CO/N2 separations

The separation of CO/N₂ mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal–organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process – i.e. an optimal material requires fulfillment of several criteria simultaneously – makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials'' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications.

The separation of challenging mixtures through adsorption is a multidimensional problem that requires a holistic approach. Our toolbox combines experiments, molecular and process simulations with data visualization to find optimal, porous materials.     

Enantioselective palladaelectro-catalyzed C–H olefinations and allylations for N–C axial chirality

Enantioselective palladaelectro-catalyzed C–H alkenylations and allylations were achieved with easily-accessible amino acids as transient directing groups. This strategy provided access to highly enantiomerically-enriched N–C axially chiral scaffolds under exceedingly mild conditions. The synthetic utility of our strategy was demonstrated by a variety of alkenes, while the versatility of our approach was reflected by atroposelective C–H allylations. Computational studies provided insights into a facile C–H activation by a seven-membered palladacycle.

Enantioselective palladaelectro-catalyzed C–H alkenylations and allylations were achieved by the means of an easily-accessible amino acid for the synthesis of N–C axially chiral indole biaryls.     

Selective propargylic C(sp3)–H activation of methyl-substituted alkynes versus [2 + 2] cycloaddition at a titanium imido template

The reaction of the titanium imido complex 1b with 2-butyne leads to the formation of the titanium azadiene complex 2a at ambient temperature instead of yielding the archetypical [2 + 2] cycloaddition product (titanaazacyclobutene) which is usually obtained by combining titanium imido complexes and internal alkynes. The formation of 2a is presumably caused by an initial propargylic C(sp³)–H activation step and quantum chemical calculations suggest that the outcome of this unexpected reactivity is thermodynamically favored. The previously reported titanaazacyclobutene I (which is obtained by reacting 1b with 1-phenyl-1-propyne) undergoes a rearrangement reaction at elevated temperature to give the corresponding five-membered titanium azadiene complex 2b.

An unexpected reactivity between a titanium imido complex and internal alkynes was unveiled yielding titanaazacyclobutenes instead of the expected [2 + 2] cycloaddition products.     

Dibenzocycloheptanones construction through a removable P-centered radical: synthesis of allocolchicine analogues

Dibenzocycloheptanones containing a tricyclic 6–7–6-system are present in numerous biologically active natural molecules. However, the simple and efficient preparation of derivatives containing a dibenzocycloheptanone scaffold remains difficult to date. Herein, we report a versatile strategy for the construction of these challenging seven-membered rings using a 7-endo-trig cyclization which is initiated by a phosphorus-centered radical. This approach provides a step-economical regime for the facile assembly of a wide range of phosphorylated dibenzocycloheptanones. Remarkably, we also have devised a traceless addition/exchange strategy for the preparation of dephosphorylated products at room temperature with excellent yields. Therefore, this protocol allows for the concise synthesis of biorelevant allocochicine derivatives.

Dibenzocycloheptanones containing a tricyclic 6–7–6-system are present in numerous biologically active natural molecules.     

Exploiting radical-pair intersystem crossing for maximizing singlet oxygen quantum yields in pure organic fluorescent photosensitizers

Fluorescent photosensitizers (PSs) often encounter low singlet oxygen (¹O₂) quantum yields and fluorescence quenching in the aggregated state, mainly involving the intersystem crossing process. Herein, we successfully realize maximizing ¹O₂ quantum yields of fluorescent PSs through promoting radical-pair intersystem crossing (RP-ISC), which serves as a molecular symmetry-controlling strategy of donor–acceptor (D–A) motifs. The symmetric quadrupolar A–D–A molecule PTP exhibits an excellent ¹O₂ quantum yield of 97.0% with bright near-infrared fluorescence in the aggregated state. Theoretical and ultrafast spectroscopic studies suggested that the RP-ISC mechanism dominated the formation of the triplet for PTP, where effective charge separation and an ultralow singlet–triplet energy gap (0.01 eV) enhanced the ISC process to maximize ¹O₂ generation. Furthermore, in vitro and in vivo experiments demonstrated the dual function of PTP as a fluorescent imaging agent and an anti-cancer therapeutic, with promising potential applications in both diagnosis and theranostics.

Maximizing singlet oxygen quantum yields of a fluorescent photosensitizer for realizing approximately 100% utilization of excitons by precisely controlling the molecular symmetry.     

A comprehensive analysis in one run – in-depth conformation studies of protein–polymer chimeras by asymmetrical flow field-flow fractionation

Polymer-based protein engineering has enabled the synthesis of a variety of protein–polymer conjugates that are widely applicable in therapeutic, diagnostic and biotechnological industries. Accurate characterizations of physical–chemical properties, in particular, molar masses, sizes, composition and their dispersities are critical parameters that determine the functionality and conformation of protein–polymer conjugates and are important for creating reproducible manufacturing processes. Most of the current characterization techniques suffer from fundamental limitations and do not provide an accurate understanding of a sample''s true nature. In this paper, we demonstrate the advantage of asymmetrical flow field-flow fractionation (AF4) coupled with multiple detectors for the characterization of a library of complex, zwitterionic and neutral protein–polymer conjugates. This method allows for determination of intrinsic physical properties of protein–polymer chimeras from a single, rapid measurement.

Precise characterization of structural parameters and their polydispersities of protein–polymer conjugates is performed with rapid analysis using asymmetrical flow field-flow fractionation coupled with multiple detectors.     

Selective crystallization via vibrational strong coupling

The coupling of (photo)chemical processes to optical cavity vacuum fields is an emerging method for modulating molecular and material properties. Recent reports have shown that strong coupling of the vibrational modes of solvents to cavity vacuum fields can influence the chemical reaction kinetics of dissolved solutes. This suggests that vibrational strong coupling might also effect other important solution-based processes, such as crystallization from solution. Here we test this hitherto unexplored notion, investigating pseudopolymorphism in the crystallization from water of ZIF metal–organic frameworks inside optical microcavities. We find that ZIF-8 crystals are selectively obtained from solution inside optical microcavities, where the OH stretching vibration of water is strongly coupled to cavity vacuum fields, whereas mixtures of ZIF-8 and ZIF-L are obtained otherwise. Moreover, ZIF crystallization is accelerated by solvent vibrational strong coupling. This work suggests that cavity vacuum fields might become a tool for materials synthesis, biasing molecular self-assembly and driving macroscopic material outcomes.

Strong coupling of optical cavity vacuum fields and solvent vibrations leads to selective crystallization in a pseudo-polymorphic MOF system.     

Mechanical unfolding of ensemble biomolecular structures by shear force

Mechanical unfolding of biomolecular structures has been exclusively performed at the single-molecule level by single-molecule force spectroscopy (SMFS) techniques. Here we transformed sophisticated mechanical investigations on individual molecules into a simple platform suitable for molecular ensembles. By using shear flow inside a homogenizer tip, DNA secondary structures such as i-motifs are unfolded by shear force up to 50 pN at a 77 796 s⁻¹ shear rate. We found that the larger the molecules, the higher the exerted shear forces. This shear force approach revealed affinity between ligands and i-motif structures. It also demonstrated a mechano-click reaction in which a Cu(i) catalyzed azide–alkyne cycloaddition was modulated by shear force. We anticipate that this ensemble force spectroscopy method can investigate intra- and inter-molecular interactions with the throughput, accuracy, and robustness unparalleled to those of SMFS methods.

Shear force in a homogenizer mechanically unfolds an ensemble set of biomolecular structures.     

Stimuli-responsive temporary adhesives: enabling debonding on demand through strategic molecular design

Stimuli-responsive temporary adhesives constitute a rapidly developing class of materials defined by the modulation of adhesion upon exposure to an external stimulus or stimuli. Engineering these materials to shift between two characteristic properties, strong adhesion and facile debonding, can be achieved through design strategies that target molecular functionalities. This perspective reviews the recent design and development of these materials, with a focus on the different stimuli that may initiate debonding. These stimuli include UV light, thermal energy, chemical triggers, and other potential triggers, such as mechanical force, sublimation, electromagnetism. The conclusion discusses the fundamental value of systematic investigations of the structure–property relationships within these materials and opportunities for unlocking novel functionalities in future versions of adhesives.

Stimuli-responsive temporary adhesives emerge as next-generation multifunctional materials with advantages that include strong temporary adhesion, debonding on demand, and tunable reactivity.     

By-design molecular architectures via alkyne metathesis

Shape-persistent purely organic molecular architectures have attracted tremendous research interest in the past few decades. Dynamic Covalent Chemistry (DCvC), which deals with reversible covalent bond formation reactions, has emerged as an efficient synthetic approach for constructing these well-defined molecular architectures. Among various dynamic linkages, the formation of ethynylene linkages through dynamic alkyne metathesis is of particular interest due to their high chemical stability, linearity, and rigidity. In this review, we focus on the synthetic strategies of discrete molecular architectures (e.g., macrocycles, molecular cages) containing ethynylene linkages using alkyne metathesis as the key step, and their applications. We will introduce the history and challenges in the synthesis of those architectures via alkyne metathesis, the development of alkyne metathesis catalysts, the reported novel macrocycle structures, molecular cage structures, and their applications. In the end, we offer an outlook of this field and remaining challenges.

The recent synthesis of novel shape-persistent 2D and 3D molecular architectures via alkyne metathesis is reviewed and the critical role of catalysts is also highlighted.     

Molecular design of thermally activated delayed fluorescent emitters for narrowband orange–red OLEDs boosted by a cyano-functionalization strategy

The establishment of a simple molecular design strategy to realize red-shifted emission while maintaining good color purity for multi-resonance induced thermally activated delayed fluorescent (MR-TADF) materials remains an appealing yet challenging task. Herein, we demonstrate that the attachment of a cyano (CN) functionality at the lowest unoccupied molecular orbital location of the MR-TADF skeleton can promote attractive red-shifted emission due to the exceptional electron-withdrawing capacity of the CN group, which represents the first example of orange–red MR-TADF emitters. Meanwhile, the linear CN group adopts a coplanar conformation with the MR-framework to restrict structure relaxation associated with rotation, which is beneficial to maintain a small full-width at half-maximum and thus a good color purity. The CNCz-BNCz-based OLED device, which utilizes a TADF sensitized mechanism to accelerate the up-conversion process of triplet excitons in the emitting layer, exhibits an outstanding external quantum efficiency (EQE) as high as 33.7%, representing the state-of-the-art performance for orange–red TADF-OLEDs.

The first example of narrowband orange–red MR-TADF emitters has been developed, which realizes a record-high EQE of 33.7% in OLEDs.