Hydroxylamine (NH2OH) is an important feedstock for oxime production. Coreduction of NOx and aldehydes or ketones enables sustainable one-step oximation by utilizing in situ *NH2OH intermediates but suffers from side reactions and reduced current density due to the presence of multiple reactants in one reactor. Here we decouple oximation into two steps, the electrochemical synthesis of free NH2OH via nitrite (NO2−) electroreduction and the aldehyde or ketone oximation chemical step, circumventing the negative effects (such as site blocking, aldehyde or ketone electroreduction, or crossover) encountered in one-step oximation. By using a Ketjen-black-supported iron phthalocyanine as the catalyst, we achieve an exceptionally high partial current density of free NH2OH (jNH2OH) of 262.9 mA cm−2 (corresponding to productivity of 2.452 mmol cm−2 h−1) in neutral conditions at an industrially relevant current density of 500 mA cm−2. By coupling NH2OH electrosynthesis with subsequent oximation in two steps, nearly stoichiometric oximes are produced with high efficiency and broad applicability. This work paves the way toward a sustainable oxime industry. A sustainable two-step strategy for oxime synthesis in a neutral KHCO3 medium is reported. Free-state NH2OH is initially synthesized via nitrite electroreduction over a Ketjen-black-supported iron phthalocyanine catalyst, followed by a chemical aldehyde or ketone oximation using the electrochemically synthesized NH2OH.

Regulatory sequences encode crucial gene expression signals, yet the sequence characteristics that determine their functionality across species remain obscure. Deep generative models have demonstrated considerable potential in various inverse design applications, especially in engineering genetic elements. Here, we introduce DeepCROSS, a generative artificial intelligence framework for the inverse design of cross-species and species-preferred 5' regulatory sequences in bacteria. DeepCROSS constructs a meta-representation using 1.8 million regulatory sequences from thousands of bacterial genomes to depict the general constraints of regulatory sequences, employs artificial intelligence-guided massively parallel reporter assay experiments in E. coli and P. aeruginosa to explore the potential sequence space, and performs multi-task optimization to obtain de novo regulatory sequences. The optimized regulatory sequences achieve similar or better performance to functional natural regulatory sequences, with high success rates and low sequence similarities with the natural genome. Collectively, DeepCROSS efficiently navigates the sequence-function landscape and enables the inverse design of cross-species and species-preferred 5' regulatory sequences.

Quantum simulators with hundreds of qubits and engineerable Hamiltonians have the potential to explore quantum many-body models that are intractable for classical computers. However, learning the simulated Hamiltonian, a prerequisite for any quantitative applications of a quantum simulator, remains an outstanding challenge due to the fast increasing time cost with the qubit number and the lack of high-fidelity universal gate operations in the noisy intermediate-scale quantum era. Here, we demonstrate the Hamiltonian learning of a two-dimensional ion trap quantum simulator with 300 qubits. We use global manipulations and single-qubit-resolved state detection to efficiently learn the all-to-all-coupled Ising model Hamiltonian, with the required quantum resources scaling at most linearly with the qubit number. We further demonstrate a physically guided learning scheme with the quantum sample complexity independent of system sizes by carefully fitting the anharmonic trap potential. Our work paves the way for wide applications of large-scale ion trap quantum simulators.

A large qubit capacity and an individual readout capability are two crucial requirements for large-scale quantum computing and simulation1. As one of the leading physical platforms for quantum information processing, the ion trap has achieved a quantum simulation of tens of ions with site-resolved readout in a one-dimensional Paul trap2-4 and of hundreds of ions with global observables in a two-dimensional (2D) Penning trap5,6. However, integrating these two features into a single system is still very challenging. Here we report the stable trapping of 512 ions in a 2D Wigner crystal and the sideband cooling of their transverse motion. We demonstrate the quantum simulation of long-range quantum Ising models with tunable coupling strengths and patterns, with or without frustration, using 300 ions. Enabled by the site resolution in the single-shot measurement, we observe rich spatial correlation patterns in the quasi-adiabatically prepared ground states, which allows us to verify quantum simulation results by comparing the measured two-spin correlations with the calculated collective phonon modes and with classical simulated annealing. We further probe the quench dynamics of the Ising model in a transverse field to demonstrate quantum sampling tasks. Our work paves the way for simulating classically intractable quantum dynamics and for running noisy intermediate-scale quantum algorithms7,8 using 2D ion trap quantum simulators.

Synthetic dimension is a potent tool in quantum simulation of topological phases of matter. Here we propose and demonstrate a scheme to simulate an anisotropic Harper-Hofstadter model with controllable magnetic flux on a two-leg ladder using the spin and motional states of a single trapped ion. We verify the successful simulation of this model by comparing the measured dynamics with theoretical predictions under various coupling strength and magnetic flux, and we observe the chiral motion of wave packets on the ladder as evidence of the topological chiral edge modes. We develop a quench path to adiabatically prepare the ground states for varying magnetic flux and coupling strength, and we measure the chiral current on the ladder for the prepared ground states, which allows us to probe the quantum phase transition between the Meissner phase and the vortex phase. Our work demonstrates the trapped ion as a powerful quantum simulation platform for topological quantum matter.

Electrocatalytic upgrading of wasted plastic and renewable biomass represents a sustainable method to produce chemicals but is limited to carbohydrates, leaving other value-added chemicals, such as organonitrogen compounds, being scarcely explored. Herein, we reported an electrocatalytic oxidation strategy to transform polyethylene terephthalate (PET) plastic-derived ethylene glycol (EG) and biomass-derived polyols into formamide, in the presence of ammonia (NH 3 ) over a tungsten oxide (WO 3 ) catalyst. Taking EG-to-formamide as an example, we achieved a high formamide productivity of 537.7 μmol cm −2 h −1 with FE of 43.2 % at a constant current of 100 mA cm −2 in a flow electrolyzer with 12-h test, representing a more advantageous performance compared with previous reports for formamide electrosynthesis. Mechanistic understanding revealed that the cleavage of the C−C bond in the EG was facilitated by nucleophilic attack of in situ formed nitrogen radicals from NH 3 , with resultant C−N bond construction and eventually formamide production. Furthermore, this strategy can be extended to transformation of PET bottle and a series of biomass-derived polyols with carbon number from three (glycerol) to six (glucose), producing formamide with high efficiencies. This work demonstrates a sustainable upgrading strategy of plastic and biomass that may have implications to more value-added chemicals production beyond carbohydrates.

Ethylene glycol is an essential commodity chemical with high demand, which is conventionally produced via thermocatalytic oxidation of ethylene with huge fossil fuel consumption and CO2 emission. The one-step electrochemical approach offers a sustainable route but suffers from reliance on noble metal catalysts, low activity, and mediocre selectivity. Herein, we report a one-step electrochemical oxidation of ethylene to ethylene glycol over an earth-abundant metal-based molecular catalyst, a cobalt phthalocyanine supported on a carbon nanotube (CoPc/CNT). The catalyst delivers ethylene glycol with 100% selectivity and 1.78 min(-1) turnover frequency at room temperature and ambient pressure, more competitive than those obtained over palladium catalysts. Experimental data demonstrate that the catalyst orchestrates multiple tasks in sequence, involving electrochemical water activation to generate high-valence Co-oxo species, ethylene epoxidation to afford an ethylene oxide intermediate via oxygen transfer, and eventually ring-opening of ethylene oxide to ethylene glycol facilitated by in situ formed Lewis acid site. This work offers a great opportunity for commodity chemicals synthesis based on a one-step, earth-abundant metal-catalyzed, and renewable electricity-driven route.

Transformation of carbon dioxide and nitrate ions into urea offers an attractive route for both nitrogen fertilizer production and environmental remediation. However, achieving this transformation under mild conditions remains challenging. Herein, we report an efficient photoelectrochemical method for urea synthesis by co-reduction of carbon dioxide and nitrate ion over a Cu 2 O photocathode, delivering urea formation rate of 29.71±2.20 μmol g −1  h −1 and Faradaic efficiency (FE) of 12.90±1.15 % at low external potential (−0.017 V vs. reversible hydrogen electrode). Experimental data combined with theoretical calculations suggest that the adsorbed CO* and NO 2 * species are the key intermediates, and associated C−N coupling is the rate-determining step. This work demonstrates that Cu 2 O is an efficient catalyst to drive co-reduction of CO 2 and NO 3 − to urea under light irradiation with low external potential, showing great opportunity of photoelectrocatalysis as a sustainable tool for value-added chemical synthesis.

Quantum networks can enable various applications such as distributed quantum computing, long-distance quantum communication, and network-based quantum sensing with unprecedented performances. One of the most important building blocks for a quantum network is a photonic quantum memory which serves as the interface between the communication channel and the local functional unit. A programmable quantum memory which can process a large stream of flying qubits and fulfill the requirements of multiple core functions in a quantum network is still to-be-realized. Here we report a high-performance quantum memory which can simultaneously store 72 optical qubits carried by 144 spatially separated atomic ensembles and support up to a thousand consecutive write or read operations in a random access way, two orders of magnitude larger than the previous record. Due to the built-in programmability, this quantum memory can be adapted on-demand for several functions. As example applications, we realize quantum queue, stack, and buffer which closely resemble the counterpart devices for classical information processing. We further demonstrate the synchronization and reshuffle of 4 entangled pairs of photonic pulses with probabilistic arrival time and arbitrary release order via the memory, which is an essential requirement for the realization of quantum repeaters and efficient routing in quantum networks. Realization of this multi-purpose programmable quantum memory thus constitutes a key enabling building block for future large-scale fully-functional quantum networks.

Quantum spin models have been extensively used to study the properties of strongly correlated systems and to find approximate solutions to combinatorial optimization problems. Trapped-ion systems have reliably demonstrated the quantum simulation of various quantum spin models in one-dimensional chains. The extension of trapped-ion simulators to two dimensions has been an enticing goal for decades. Here we present the quantum simulation of Ising models with two-dimensional ion crystals in a Paul trap. We benchmark the simulator by implementing various spin models with complex interaction networks and adiabatically prepare the corresponding ground states. Spin–spin interactions with different signs and sufficiently large strengths are generated by driving different vibrational modes. We probe the quantum coherence of the simulation by reversing the ramping profile of the transverse field to the initial value and then quantify the probability of returning to the initial state. Then, we test the scalability of the system for a large-scale quantum simulation. Our results show that major portions of the spin states are in the ground state even for highly frustrated spin models.

Electrosynthesis of adipic acid (a precursor for nylon-66) from KA oil (a mixture of cyclohexanone and cyclohexanol) represents a sustainable strategy to replace conventional method that requires harsh conditions. However, its industrial possibility is greatly restricted by the low current density and competitive oxygen evolution reaction. Herein, we modify nickel layered double hydroxide with vanadium to promote current density and maintain high faradaic efficiency (>80%) within a wide potential window (1.5 similar to 1.9V vs. reversible hydrogen electrode). Experimental and theoretical studies reveal two key roles of V modification, including accelerating catalyst reconstruction and strengthening cyclohexanone adsorption. As a proof-of-the-concept, we construct a membrane electrode assembly, producing adipic acid with high faradaic efficiency (82%) and productivity (1536 mu mol cm(-2) h(-1)) at industrially relevant current density (300 mA cm(-2)), while achieving >50 hours stability. This work demonstrates an efficient catalyst for adipic acid electrosynthesis with high productivity that shows industrial potential.

Electrocatalytic reduction of biomass-derived furfural (FF) represents a sustainable route to produce furfuryl alcohol (FA) and 2-methylfuran (MF) as a value-added chemical and a biofuel, respectively. However, achieving high selectivity for MF as well as tuning the selectivity between FA and MF within one reaction system remain challenging. Herein, we have reported an electrode-electrolyte interface modification strategy, enabling FA and MF selectivity steering under the same reaction conditions. Specifically, by modifying copper (Cu) electrocatalysts with butyl trimethylammonium bromide (BTAB), we achieved a dramatic shift in selectivity from producing FA (selectivity: 83.8%; Faradaic efficiency, FE: 68.9%) to MF (selectivity: 80.1%; FE: 74.8%). We demonstrated that BTAB adsorption over Cu modulates the electrical double layer (EDL) structure, which repels interfacial water and weakens the hydrogen-bond (H-bond) network for proton transfer, thus impeding FF-to-FA conversion by suppression of the hydrogen atom transfer (HAT) process. On the contrary, FF-to-MF conversion was less affected. This work shows the potential of engineering of the electrode-electrolyte interface for selectivity control in electrocatalysis.

Nucleophile oxidation reaction (NOR) is emerging as a significant approach for the sustainable production of value-added chemicals. Among the various types, electrocatalytic glycerol oxidation reaction (GOR) stands out as a crucial method for producing C-1 to C(3 )chemicals including formic acid (FA). Non-noble-metal-based (oxy)hydroxides have found extensive use in GOR, yet achieving industrially-demanded current densities (> 300 mA.cm(-2) ) at moderate potentials remains a challenge. It is well documented that GOR catalyzed by (oxy)hydroxides follows an indirect oxidation mechanism. Specifically, the nucleophile, glycerol, undergoes oxidation by the electrogenerated oxyhydroxides with electrophilic adsorption oxygen. Therefore, comprehending the evolution of the electrocatalyst in GOR is critically important. In this paper, we have developed molybdenum-doped nickel oxyhydroxides (Mo-NiOOH) through cyclic voltammetry (CV) activation of nickel molybdate (NiMoO4 ). We demonstrated that Mo species leach from NiMoO4, and the resulting Mo-NiOOH retains the nanosheet array morphology of NiMoO4. We subjected the freshly prepared Mo-NiOOH to systematic characterizations employing techniques such as scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) mapping, Raman spectroscopy, inductively coupled plasma-mass spectrometry (ICP-MS), and X-ray photoelectron spectroscopy (XPS). The above structural characterizations confirm that Mo-NiOOH inherits the nanosheet array morphology of the NiMoO4 precursor with reduced Mo content, thereby indicating the phase reconstruction from oxides to oxyhydroxides post CV activation. Furthermore, the Ni3+/Ni2+ ratio in Mo-NiOOH surpasses that in NiOOH derived from CV activation of Ni(OH)(2). Mo-NiOOH exhibits elevated electrochemically active surface areas (ECSAs) and a higher Ni3+/Ni2+ ratio compared to NiOOH obtained through CV activation of Ni(OH)(2,) facilitating the Mo-NiOOH exhibits higher ratio of Ni3+/Ni2+, higher electrochemically active surface areas (ECSAs) than NiOOH, and facilitated oxidation of Ni2+ to Ni 3+ . Consequently, Mo-NiOOH requires a lower applied potential than NiOOH (1.51 V versus 1.84 V vs . reversible hydrogen electrode (RHE)) to achieve a high current density (400 mA.cm(-2) ). Additionally, Mo-NiOOH demonstrates higher Faradaic efficiency towards formate (FEformate ) in contrast to NiOOH (84.7% versus 59.6%), indicating enhanced carbon- carbon (C & horbar;C) bond cleavage due to Mo doping. Multi-potential step (STEP) experiments indicate that GOR catalyzed by NiOOH and Mo-NiOOH follows a similar indirect oxidation mechanism mediated by oxyhydroxides. Operando electrochemical impedance spectroscopy (EIS) and in situ Raman spectroscopy confirmed that Mo doping in NiOOH accelerates GOR kinetics and the oxidation of Ni2+ to Ni3+ , contributing to the higher activity and formate selectivity of Mo-NiOOH than NiOOH. The strategy of surface modulation of oxyhydroxides through leaching of soluble anions offers guidelines for the rational design of high-performance NOR electrocatalysts.

Water and soil pollution caused by toxic cadmium ions (Cd2+) is a serious threat to animals, plants, and human health. Discovering low-cost mineralizers which can efficiently and stably immobilize Cd2+ ions is therefore imperative for wastewater treatment and soil remediation. In this work, we report the successful development of a novel mineralizer for Cd2+ ion capture. A magnesium-aluminum layered double hydroxide (MgAl-LDH) with a monolayer structure (MgAl-mono) was first prepared and then calcined at 350 degrees C for 4 h to produce a defective MgAl-mono-350. MgAl-mono-350 offered a very high Cd2+ removal capacity (1385.5 mg/g at 25 degrees C) and the ability to reduce the concentration of Cd2+ in aqueous solution from 100 ppm to less than 50 ppb in 15 min (meeting the discharge standard of industrial wastewater). Detailed characterization and computational studies revealed that MgAl-mono-350 possessed abundant oxygen defects, thereby enabling superstable mineralization of Cd2+ via isomorphous substitution process,and the Cd2+ ions are immobilized in the generated CdAl-LDH structure. MgAl-mono-350 also offered outstanding selectivity for Cd2+ ions over other common ions. This work demonstrates the potential of defect-engineered LDH materials for the selective removal of heavy metals from polluted water.

The electro-oxidation of biomass-derivatives offers a sustainable alternative to limited fossil resources by producing valuable carbon-based chemicals. Integrating biomass electro-oxidation with decoupled hydrogen generation from water splitting not only produces valued-added chemicals but also reduces the energy consumption of hydrogen production. However, the development of efficient bifunctional electrocatalysts capable of facilitating both anodic and cathodic reactions remains a challenging task. Herein, we report that coupling cobalt oxide with ruthenium oxide significantly enhances the activities of both anodic and cathodic reactions. As a bifunctional electrocatalyst, the ruthenium oxide/cobalt oxide heterojunction drives simultaneous production of 2,5-furandicarboxylic acid and hydrogen at a low cell voltage of 1.445 V and a current density of 50 mA cm−2, showing great promise for electrochemical biomass upgrading.

Enzymes are characteristic of catalytic efficiency and specificity by maneuvering multiple components in concert at a confined nanoscale space. However, achieving such a configuration in artificial catalysts remains challenging. Herein, we report a microenvironment regulation strategy by modifying carbon paper with hexadecyltrimethylammonium cations, delivering electrochemical carbon–carbon coupling of benzaldehyde with enhanced activity and racemate stereoselectivity. The modified electrode–electrolyte interface creates an optimal microenvironment for electrocatalysis—it engenders dipolar interaction with the reaction intermediate, giving a 2.2-fold higher reaction rate (from 0.13 to 0.28 mmol h −1 cm −2 ); Moreover, it repels interfacial water and modulates the conformational specificity of reaction intermediate by facilitating intermolecular hydrogen bonding, affording 2.5-fold higher diastereomeric ratio of racemate to mesomer (from 0.73 to 1.82). We expect that the microenvironment regulation strategy will lead to the advanced design of electrode–electrolyte interface for enhanced activity and (stereo)selectivity that mimics enzymes.

Electrocatalytic oxidation of renewable biomass (such as glucose) into high-value-added chemicals provides an effective approach to achieving carbon neutrality. CuO-derived materials are among the most promising electrocatalysts for biomass electrooxidation, but the identification of their active sites under electrochemical conditions remains elusive. Herein, we report a potential-dependent structure evolution over CuO in the glucose oxidation reaction (GOR). Through systematic electrochemical and spectroscopic characterizations, we unveil that CuO undergoes Cu2+/Cu+ and Cu3+/Cu2+ redox processes at increased potentials with successive generation of Cu(OH)2 and CuOOH as the active phases. In addition, these two structures have distinct activities in the GOR, with Cu(OH)2 being favorable for aldehyde oxidation, and CuOOH showed faster kinetics in carbon-carbon cleavage and alcohol/aldehyde oxidation. This work deepens our understanding of the dynamic reconstruction of Cu-based catalysts under electrochemical conditions and may guide rational material design for biomass valorization.

High-fidelity two-qubit gates in quantum computers are often hampered by fluctuating experimental parameters. The effects of time-varying parameter fluctuations lead to coherent noise on the qubits, which can be suppressed by designing control signals with appropriate filter functions. Here, we develop filter functions for M{\o}lmer-S{\o}rensen gates of trapped-ion quantum computers that accurately predict the change in gate error due to small parameter fluctuations at any frequency. We then design the filter functions of frequency-modulated laser pulses, and compare this method with pulses that are robust to static offsets of the motional-mode frequencies. Experimentally, we measure the noise spectrum of the motional modes and use it for designing the filter functions, which improves the gate fidelity from 99.23(7)% to 99.55(7)% in a five-ion chain.

The universality theorem in quantum computing states that any quantum computational task can be decomposed into a finite set of logic gates operating on one and two qubits. However, the process of such decomposition is generally inefficient, often leading to exponentially many gates to realize an arbitrary computational task. Practical processor designs benefit greatly from availability of multi-qubit gates that operate on more than two qubits to implement the desired circuit. In 1995, Cirac and Zoller proposed a method to realize native multi-qubit controlled-$Z$ gates in trapped ion systems, which has a stringent requirement on ground-state cooling of the motional modes utilized by the gate. An alternative approach, the M\o lmer-S\o rensen gate, is robust against residual motional excitation and has been a foundation for many high-fidelity gate demonstrations. This gate does not scale well beyond two qubits, incurring additional overhead when used to construct many target algorithms. Here, we take advantage of novel performance benefits of long ion chains to realize fully programmable and scalable high-fidelity Cirac-Zoller gates.

The development of a rechargeable battery that can produce valuable chemicals in both electricity storage and generation processes holds great promise for increasing the electron economy and economic value. However, this battery has yet to be explored. Herein, we report a biomass flow battery that generates electricity while producing furoic acid, and store electricity while yielding furfuryl alcohol. The battery is composed of a rhodium-copper (Rh1Cu) single-atom alloy as anode, a cobalt-doped nickel hydroxide (Co0.2Ni0.8(OH)(2)) as cathode, and furfural-containing anolyte. In a full battery evaluation, this battery displays an open circuit voltage (OCV) of 1.29 V and a peak power density up to 107 mW cm(-2), surpassing most catalysis-battery hybrid systems. As a proof-of-concept, we demonstrate that this battery produces 1 kg furoic acid with 0.78 kWh electricity output, and yields 0.62 kg furfuryl alcohol when 1 kWh electricity is stored. This work may shed light on the design of rechargeable batteries with value-added functionality such as chemicals production.