Beyond metals: theoretical discovery of semiconducting MAX phases and their potential application in thermoelectrics.

MAX phase is a family of ceramic compounds, typically known for their metallic properties. However, we show here that some of them may be narrow bandgap semiconductors. Using a series of first-principles calculations, we have investigated the electronic structures of 861 dynamically stable MAX phases. Notably, Sc2SC, Y2SC, Y2SeC, Sc3AuC2, and Y3AuC2 have been identified as semiconductors with band gaps ranging from 0.2 to 0.5 eV. Furthermore, we have assessed the thermodynamic stability of these systems by generating ternary phase diagrams utilizing evolutionary algorithm techniques. Their dynamic stabilities are confirmed by phonon calculations. Additionally, we have explored the potential thermoelectric efficiencies of these materials by combining Boltzmann transport theory with first-principles calculations. The relaxation times are estimated using scattering theory. The zT coefficients for the aforementioned systems fall within the range of 0.5 to 2.5 at temperatures spanning from 300 to 700 K, indicating their suitability for high-temperature thermoelectric applications.

Magneto-transport in the monolayer MoS2material system for high-performance field-effect transistor applications.

Electronic transport in monolayer MoS2is significantly constrained by several extrinsic factors despite showing good prospects as a transistor channel material. Our paper aims to unveil the underlying mechanisms of the electrical and magneto-transport in monolayer MoS2. In order to quantitatively interpret the magneto-transport behavior of monolayer MoS2on different substrate materials, identify the underlying bottlenecks, and provide guidelines for subsequent improvements, we present a deep analysis of the magneto-transport properties in the diffusive limit. Our calculations are performed on suspended monolayer MoS2and MoS2on different substrate materials taking into account remote impurity and the intrinsic and extrinsic phonon scattering mechanisms. We calculate the crucial transport parameters such as the Hall mobility, the conductivity tensor elements, the Hall factor, and the magnetoresistance over a wide range of temperatures, carrier concentrations, and magnetic fields. The Hall factor being a key quantity for calculating the carrier concentration and drift mobility, we show that for suspended monolayer MoS2at room temperature, the Hall factor value is around 1.43 for magnetic fields ranging from 0.001 to 1 Tesla, which deviates significantly from the usual value of unity. In contrast, the Hall factor for various substrates approaches the ideal value of unity and remains stable in response to the magnetic field and temperature. We also show that the MoS2over an Al2O3substrate is a good choice for the Hall effect detector. Moreover, the magnetoresistance increases with an increase in magnetic field strength for smaller magnetic fields before reaching saturation at higher magnetic fields. The presented theoretical model quantitatively captures the scaling of mobility and various magnetoresistance coefficients with temperature, carrier densities, and magnetic fields.

Unveiling Valence State-Dependent Photocatalytic Water Splitting Activity and Photocathodic Behavior in Visible Light-Active Iridium-Doped BaTiO3.

Despite having favorable energetics and tunable optoelectronic properties, utilization of BaTiO3 (BTO) for photocatalytic reactions is limited by its absorption only in the ultraviolet region. To address this challenge, BTO is doped with iridium (Ir) to induce visible light absorption. The visible light-induced photocatalytic H2 generation efficiency is enhanced by 2 orders of magnitude on selective conversion of the Ir valence state from Ir4+ to Ir3+. To understand such intriguing behavior, valence state-dependent changes in the optoelectronic, structural, and surface properties and electronic band structure are comprehensively investigated. The effect of electron occupancy change between Ir4+ (t2g5 eg0) and Ir3+ (t2g6 eg0) and their energetic positions within the band gap is found to significantly influence H2 generation. Besides this, converting Ir4+ to Ir3+ enhanced the photocathodic current and lowered the onset potential. Results aid in designing photocatalysts to efficiently use low-energy photons for enhancing solar H2 production in these emerging BTO-based photocatalysts. Collectively, the observations made in this work highlight the promising application of Ir3+:BTO in z-scheme photocatalysis.

WS2-Graphene van der Waals Heterostructure as Promising Anode Material for Lithium-Ion Batteries: A First-Principles Approach.

In this work, we report the results of density functional theory (DFT) calculations on a van der Waals (VdW) heterostructure formed by vertically stacking single-layers of tungsten disulfide and graphene (WS2/graphene) for use as an anode material in lithium-ion batteries (LIBs). The electronic properties of the heterostructure reveal that the graphene layer improves the electronic conductivity of this hybrid system. Phonon calculations demonstrate that the WS2/graphene heterostructure is dynamically stable. Charge transfer from Li to the WS2/graphene heterostructure further enhances its metallic character. Moreover, the Li binding energy in this heterostructure is higher than that of the Li metal's cohesive energy, significantly reducing the possibility of Li-dendrite formation in this WS2/graphene electrode. Ab initio molecular dynamics (AIMD) simulations of the lithiated WS2/graphene heterostructure show the system's thermal stability. Additionally, we explore the effect of heteroatom doping (boron (B) and nitrogen (N)) on the graphene layer of the heterostructure and its impact on Li-adsorption ability. The results suggest that B-doping strengthens the Li-adsorption energy. Notably, the calculated open-circuit voltage (OCV) and Li-diffusion energy barrier further support the potential of this heterostructure as a promising anode material for LIBs.

Notch signaling regulates mineralization via microRNA modulation in dental pulp stem cells.

OBJECTIVES: This study investigated the miRNA expression profile in Notch-activated human dental stem pulp stem cells (DPSCs) and validated the functions of miRNAs in modulating the odonto/osteogenic properties of DPSCs. METHODS: DPSCs were treated with indirect immobilized Jagged1. The miRNA expression profile was examined using NanoString analysis. Bioinformatic analysis was performed, and miRNA expression was validated. Odonto/osteogenic differentiation was examined using alkaline phosphatase staining, Alizarin Red S staining, as well as odonto/osteogenic-related gene and protein expression. RESULTS: Fourteen miRNAs were differentially expressed in Jagged1-treated DPSCs. Pathway analysis revealed that altered miRNAs were associated with TGF-ß, Hippo, ErbB signalling pathways, FoxO and Ras signalling. Target prediction analysis demonstrated that 7604 genes were predicted to be targets for these altered miRNAs. Enrichment analysis revealed relationships to various DNA bindings. Among differentially expressed miRNA, miR-296-3p and miR-450b-5p were upregulated under Jagged1-treated conditions. Overexpression of miR-296-3p and miR-450b-5p enhanced mineralization and upregulation of odonto/osteogenic-related genes, whereas inhibition of these miRNAs revealed opposing results. The miR-296-3p and miR-450b-5p inhibitors attenuated the effects of Jagged1-induced mineralization in DPSCs. CONCLUSIONS: Jagged-1 promotes mineralization in DPSCs that are partially regulated by miRNA. The novel understanding of these miRNAs could lead to innovative controlled mechanisms that can be applied to modulate biology-targeted dental materials.

Effect of Repeated Greater Occipital Nerve Block in Patients with Ocular Neuropathic Pain: A Retrospective Observational Study.

Ocular neuropathic pain (ONP) has various etiologies, and patients have various symptoms. The clinical management of patients with ONP has been debated. We aimed to evaluate the effect of repeated greater occipital nerve block (GONB) on ONP based on convergence in the trigeminocervical complex. In this single-center retrospective study, the medical records of 204 patients who were referred to the pain clinic by the ophthalmology department of our hospital and subsequently underwent repeated GONB for chronic ONP between January 2008 and February 2022 were analyzed. They received GONB every two weeks, up to 10 times. Symptoms of ONP were divided into five categories: eye pain, dysesthesias/allodynia, non-eye pain, visual disturbance, and tearing. The primary outcome of this study was the pain relief scale (PRS) score after repeated injections. The differences and magnitude of decrease in the overall pain relief scale score were statistically significant (estimate = -0.55, p < 0.001). There were two patients who had recurrence of ONP and seven patients who had adverse events. According to our study, repeated GONB can reduce symptom severity in patients with ONP. Therefore, it appears that GONB can be considered a multimodal management method for ONP.

Block sparsity promoting algorithm for efficient construction of cluster expansion models for multicomponent alloys.

Multicomponent alloys are gaining significance as drivers of technological breakthroughs especially in structural and energy storage materials. The vast configuration space of these materials prohibit computational modeling using first-principles based methods alone. The cluster expansion (CE) method is the most widely used tool for modeling configurational disorder in alloys. CE relies on machine learning algorithms to train Hamiltonians and uses first-principles calculated data as training sets. In this paper we present a new compressive sensing-based algorithm for the efficient construction of CE Hamiltonians of multicomponent alloys. Our algorithm constructs highly sparse and physically reasonable models from a carefully selected small training set of alloy structures. Compared to conventional fitting algorithms, the algorithm achieves more than 50% reduction in the training set size. The resultant sparse models can sample the configuration space at least 3 × faster. We demonstrate this algorithm on 4 different alloy systems, namely Ag-Au, Ag-Au-Cu, Ag-Au-Cu-Pd and (Ge,Sn)(S,Se,Te).The sparse CE models for these alloys can rapidly reproduce known ground state orderings and order-disorder transitions. Our method can truly enable high-throughput multicomponent alloy thermodynamics by reducing the cost associated with model construction and configuration sampling.

Combining First-Principles Modeling and Symbolic Regression for Designing Efficient Single-Atom Catalysts in the Oxygen Evolution Reaction on Mo2CO2 MXenes.

In this study, we address the significant challenge of overcoming limitations in the catalytic efficiency for the oxygen evolution reaction (OER). The current linear scaling relationships hinder the optimization of the electrocatalytic performance. To tackle this issue, we investigate the potential of designing single-atom catalysts (SACs) on Mo2CO2 MXenes for electrochemical OER using first-principles modeling simulations. By employing the Electrochemical Step Symmetry Index (ESSI) method, we assess OER intermediates to fine-tune the activity and identify the optimal SAC for Mo2CO2 MXenes. Our findings reveal that both Ag and Cu exhibit effectiveness as single atoms for enhancing OER activity on Mo2CO2 MXenes. However, among the 21 chosen transition metals (TMs) in this study, Cu stands out as the best catalyst for tweaking the overpotential (ηOER). This is due to Cu's lowest overpotential compared to other TMs, which makes it more favorable for the OER performance. On the other hand, Ag is closely aligned with ESSI = ηOER, making the tuning of its overpotential more challenging. Furthermore, we employ symbolic regression analysis to identify the significant factors that exhibit a correlation with the OER overpotential. By utilizing this approach, we derive mathematical formulas for the overpotential and identify key descriptors that affect the catalytic efficiency in the electrochemical OER on Mo2CO2 MXenes. This comprehensive investigation not only sheds light on the potential of MXenes in advanced electrocatalytic processes but also highlights the prospect of improved activity and selectivity in OER applications.

Insights into Heterogeneous Catalysis on Surfaces with 3d Transition Metals: Spin-Dependent Chemisorption Models and Magnetic Field Effects.

This Perspective provides an overview of recent developments in the field of 3d transition metal (TM) catalysts for different reactions, including oxygen-based reactions such as the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). The spin moments of 3d TMs can be exploited to influence chemical reactions, and recent advances in this area, including the theory of chemisorption based on spin-dependent d-band centers and magnetic field effects, are discussed. The Perspective also explores the use of scaling relationships and surface magnetic moments in catalyst design as well as the effect of magnetism on chemisorption and vice versa. In addition, recent studies on the influence of a magnetic field on the ORR and the OER are presented, demonstrating the potential of ferromagnetic catalysts to enhance these reactions through spin polarization.

Spin torques and anomalous velocity in spin textures induced by fast electron injection from topological ferromagnets: The role of gauge fields.

A new method for analyzing magnetization dynamics in spin textures under the influence of fast electron injection from topological ferromagnetic sources such as Dirac half metals has been proposed. These electrons, traveling at a velocityvwith a non-negligible value ofv/c(wherecis the speed of light), generate a non-equilibrium magnetization density in the spin-texture region, which is related to an electric dipole moment via relativistic interactions. When this resulting dipole moment interacts with gauge fields in the spin-texture region, an effective field is created that produces spin torques. These torques, like spin-orbit torques that occur when electrons are injected from a heavy metal into a ferromagnet, can display both damping-like and anti-damping-like properties. Finally, we demonstrate that such an interaction between the dipole moment and the gauge field introduces an anomalous velocity that can contribute to transverse electrical conductivity in the spin texture in a way comparable to the topological Hall effect.

Chemical Bonding in Large Systems Using Projected Population Analysis from Real-Space Density Functional Theory Calculations.

We present an efficient and scalable computational approach for conducting projected population analysis from real-space finite-element (FE)-based Kohn-Sham density functional theory calculations (DFT-FE). This work provides an important direction toward extracting chemical bonding information from large-scale DFT calculations on materials systems involving thousands of atoms while accommodating periodic, semiperiodic, or fully nonperiodic boundary conditions. Toward this, we derive the relevant mathematical expressions and develop efficient numerical implementation procedures that are scalable on multinode CPU architectures to compute the projected overlap and Hamilton populations. The population analysis is accomplished by projecting either the self-consistently converged FE discretized Kohn-Sham orbitals or the FE discretized Hamiltonian onto a subspace spanned by a localized atom-centered basis set. The proposed methods are implemented in a unified framework within the DFT-FE code where the ground-state DFT calculations and the population analysis are performed on the same FE grid. We further benchmark the accuracy and performance of this approach on representative material systems involving periodic and nonperiodic DFT calculations with LOBSTER, a widely used projected population analysis code. Finally, we discuss a case study demonstrating the advantages of our scalable approach to extract the quantitative chemical bonding information of hydrogen chemisorbed in large silicon nanoparticles alloyed with carbon, a candidate material for hydrogen storage.

Can magnetotransport properties provide insight into the functional groups in semiconducting MXenes?

Hall scattering factors of Sc2CF2, Sc2CO2 and Sc2C(OH)2 are calculated using Rode's iterative approach by solving the Boltzmann transport equation. This is carried out in conjunction with calculations based on density functional theory. The electrical transport in Sc2CF2, Sc2CO2 and Sc2C(OH)2 is modelled by accounting for both elastic (acoustic and piezoelectric) and inelastic (polar optical phonon) scattering. Polar optical phonon (POP) scattering is the most significant mechanism in these MXenes. We observe that there is a window of carrier concentration where the Hall factor acts dramatically; Sc2CF2 obtains an incredibly high value of 2.49 while Sc2CO2 achieves a very small value of approximately 0.5, and Sc2C(OH)2 achieves the so called ideal value of 1. We propose in this paper that such Hall factor behaviour has significant promise in the field of surface group identification in MXenes, an issue that has long baffled researchers.

Fossil and non-fossil sources of the carbonaceous component of PM2.5 in forest and urban areas.

Atmospheric particulate matter (PM2.5) can damage human health. Biogenic organic compounds emitted from trees may increase the concentration of PM2.5 via formation of secondary aerosols. Therefore, the role of biogenic emissions in PM2.5 formation and the sources of PM2.5 need to be investigated. Dual carbon isotope and levoglucosan analyses are powerful tools to track the sources of total carbon (TC) in PM2.5. We collected a total of 47 PM2.5 samples from 2019 to 2020 inside a pine forest and in urban areas in South Korea. The average δ13C and Δ14C of TC in PM2.5 at the Taehwa Research Forest (TRF) were - 25.7 and - 380.7‰, respectively, which were not significantly different from those collected at Seoul National University (SNU) in urban areas. Contribution of fossil fuel, C3-, and C4- plants to carbonaceous component of PM2.5 were 52, 27, and 21% at SNU, whereas those were 46, 35, and 19% at TRF, respectively. The biomass burning tracer, levoglucosan, was most abundant in winter and correlated with the contribution of C4 plants derived carbon. Results indicate that biogenic aerosols emitted from trees is less likely to be an important source of PM2.5 and that trees can act as a bio-filter to reduce PM2.5.

Computational design of novel MAX phase alloys as potential hydrogen storage media combining first principles and cluster expansion methods.

Finding a suitable material for hydrogen storage under ambient atmospheric conditions is challenging for material scientists and chemists. In this work, using a first principles based cluster expansion approach, the hydrogen storage capacity of the Ti2AC (A = Al, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Zn) MAX phase and its alloys was studied. We found that hydrogen is energetically stable in Ti-A layers in which the tetrahedral site consisting of one A atom and three Ti atoms is energetically more favorable for hydrogen adsorption than other sites in the Ti-A layer. Ti2CuC has the highest hydrogen adsorption energy than other Ti2AC phases. We find that the 83.33% Cu doped Ti2AlxCu1-xC alloy structure is both energetically and dynamically stable and can store 3.66 wt% hydrogen under ambient atmospheric conditions, which is higher than that stored by both Ti2AlC and Ti2CuC phases. These findings indicate that the hydrogen capacity of the MAX phase can be significantly improved by doping an appropriate atom species.

Properties of river organic carbon affected by wastewater treatment plants.

Tracking the sources of organic carbon (OC) is critical not only for understanding riverine carbon dynamics but also for providing management options to improve water quality. We collected water samples from upland forest streams to the mainstream Geumho River (GHR) of South Korea, which included a variety of wastewater treatment plants (WWTP) effluents. We analyzed the concentrations, optical properties, and dual carbon isotope ratios of these samples to identify the sources of OC. Dissolved organic carbon (DOC) was the dominant form of OC in the GHR compared to particulate organic carbon (POC), as the former accounted for 87 % of OC. The concentrations of DOC and POC ranged from 1.2 to 11.2 mg L-1 and from 0 and 3.6 mg L-1, respectively, aside from the livestock WWTP effluent. Dominant fluorescence components were terrestrial humic substances in upper reaches whereas protein-like materials in lower reaches of the GHR whose watershed includes a large city with many WWTPs. Significantly lower Δ14C-DOC and Δ14C-POC were observed in industrial WWTP effluents than the other sites due to the contribution of fossil OC. Livestock WWTP effluents had higher δ13C-DOC and δ13C-POC than most of the sites, possibly due to the animal feed derived from C4 plants such as corn. Fossil OC contributed 29-52 % of [DOC] and 36-56 % of [POC] from industrial WWTP effluents, whereas C4-plants derived OC contributed about half of [DOC] and [POC] from a livestock WWTP effluent. The results suggest that anthropogenic sources of organic carbon could alter river carbon dynamics, and that caution is needed when we interpret isotope ratios of riverine organic carbon, particularly when the river passes through highly populated areas wherein WWTP effluents are large.

Quercetin and Isorhamnetin Reduce Benzo[a]pyrene-Induced Genotoxicity by Inducing RAD51 Expression through Downregulation of miR-34a.

Benzo[a]pyrene (B[a]P) is metabolized in the liver into highly reactive mutagenic and genotoxic metabolites, which induce carcinogenesis. The mutagenic factors, including B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) and reactive oxygen species, generated during B[a]P metabolism can cause DNA damage, such as BPDE-DNA adducts, 8-oxo-dG, and double-strand breaks (DSBs). In this study, we mechanistically investigated the effects of quercetin and its major metabolite isorhamnetin on the repair of B[a]P-induced DNA DSBs. Whole-transcriptome analysis showed that quercetin and isorhamnetin each modulate the expression levels of genes involved in DNA repair, especially those in homologous recombination. RAD51 was identified as a key gene whose expression level was decreased in B[a]P-treated cells and increased by quercetin or isorhamnetin treatment. Furthermore, the number of γH2AX foci induced by B[a]P was significantly decreased by quercetin or isorhamnetin, whereas RAD51 mRNA and protein levels were increased. Additionally, among the five microRNAs (miRs) known to downregulate RAD51, miR-34a level was significantly downregulated by quercetin or isorhamnetin. The protective effect of quercetin or isorhamnetin was lower in cells transfected with a miR-34a mimic than in non-transfected cells, and the B[a]P-induced DNA DSBs remained unrepaired. Our results show that quercetin and isorhamnetin each upregulates RAD51 by downregulating miR-34a and thereby suppresses B[a]P-induced DNA damage.

Universal Ligands for Dispersion of Two-Dimensional MXene in Organic Solvents.

Ligands can control the surface chemistry, physicochemical properties, processing, and applications of nanomaterials. MXenes are the fastest growing family of two-dimensional (2D) nanomaterials, showing promise for energy, electronic, and environmental applications. However, complex oxidation states, surface terminal groups, and interaction with the environment have hindered the development of organic ligands suitable for MXenes. Here, we demonstrate a simple, fast, scalable, and universally applicable ligand chemistry for MXenes using alkylated 3,4-dihydroxy-l-phenylalanine (ADOPA). Due to the strong hydrogen-bonding and π-electron interactions between the catechol head and surface terminal groups of MXenes and the presence of a hydrophobic fluorinated alkyl tail compatible with organic solvents, the ADOPA ligands functionalize MXene surfaces under mild reaction conditions without sacrificing their properties. Stable colloidal solutions and highly concentrated liquid crystals of various MXenes, including Ti2CTx, Nb2CTx, V2CTx, Mo2CTx, Ti3C2Tx, Ti3CNTx, Mo2TiC2Tx, Mo2Ti2C3Tx, and Ti4N3Tx, have been produced in various organic solvents. Such products offer excellent electrical conductivity, improved oxidation stability, and excellent processability, enabling applications in flexible electrodes and electromagnetic interference shielding.

Effective Formation of a Mn-ZIF-67 Nanofibrous Network via Electrospinning: An Active Electrocatalyst for OER in Alkaline Medium.

Finding the active center in a bimetallic zeolite imidazolate framework (ZIF) is highly crucial for the electrocatalytic oxygen evolution reaction (OER). In the present study, we constructed a bimetallic ZIF system with cobalt and manganese metal ions and subjected it to an electrospinning technique for feasible fiber formation. The obtained nanofibers delivered a lower overpotential value of 302 mV at a benchmarking current density of 10 mA cm-2 in an electrocatalytic OER study under alkaline conditions. The obtained Tafel slope and charge-transfer resistance values were 125 mV dec-1 and 4 Ω, respectively. The kinetics of the reaction is mainly attributed from the ratio of metals (Co and Mn) present in the catalyst. Jahn-Teller distortion reveals that the electrocatalytic active center on the Mn-incorporated ZIF-67 nanofibers (Mn-ZIF-67-NFs) was found to be Mn3+ along with the Mn2+ and Co2+ ions on the octahedral and tetrahedral sites, respectively, where Co2+ ions tend to suppress the distortion, which is well supported by density functional theory analysis, molecular orbital study, and magnetic studies.

Immunomodulatory Effect and Bone Homeostasis Regulation in Osteoblasts Differentiated from hADMSCs via the PD-1/PD-L1 Axis.

Human mesenchymal stem cells (hMSCs) are promising candidates for stem cell therapy and are known to secrete programmed death-1 (PD-1) ligand 1 (PD-L1) regulating T cell-mediated immunosuppression. Given the limitations of current stem cell therapy approaches, improvements in immunomodulatory capacity and stem cell differentiation efficacy are needed. In this study, we propose novel strategies to overcome the challenges that remain in hMSC-mediated bone regeneration. We found that PD-1 is highly expressed in osteoblasts, and the PD-1/PD-L1 axis mediated the decreased proinflammatory cytokine expressions in differentiated osteoblasts cocultured with human adipose derived mesenchymal stem cells (hADMSCs). Moreover, the decrease was attenuated by PD-1/PD-L1 pathway inhibition. Osteogenic properties including osteogenic gene expression and calcium deposits were increased in osteoblasts cocultured with hADMSCs compared with those that were monocultured. Osteoblasts treated with PD-L1 and exosomes from hADMSCs also exhibited enhanced osteogenic properties, including calcium deposits and osteogenic gene expression. In our cocultured system that mimics the physiological conditions of the bone matrix, the PD-1/PD-L1 axis mediated the increased expression of osteogenic genes, thereby enhancing the osteogenic properties, while the calcium deposits of osteoblasts were maintained. Our results provide the therapeutic potentials and novel roles of the PD-1/PD-L1 axis in bone matrix for modulating the bone properties and immunosuppressive potentials that can aid in the prevention of bone diseases via maintaining bone homeostasis.

In-phase simultaneous spectral editing of lactate and alanine with suppression of J-coupled lipids by the modified selective multiple quantum coherence sequences.

1H magnetic resonance spectroscopy (MRS) with the multiple quantum coherence (MQC) technique allows for the detection of lactate, an end product of glycolysis, in the environment of lipids. The method can also be used to detect alanine, a byproduct of glutaminolysis. An issue is that when both lactate and alanine are detected together by the MQC technique, a phase mismatch arises between lactate and alanine signals due to off-resonance rotations and the difference in double quantum coherence frequencies between the two molecules. Such phase mismatch can cause errors in spectral fitting and metabolite quantification. In this study, we designed two pulse sequences that eliminate such phase differences of lactate and alanine while suppressing lipid signals by modifications of the Selective Multiple Quantum Coherence (Sel-MQC) sequence, a well-known MQC technique. Using the product operator formalism and the off-resonance rotation matrices, the phase evolutions of lactate and alanine during the spectrally selective pulses and the free precession times of the sequence at the single quantum, double quantum and zero quantum coherence states of these molecules were calculated. The multiple quantum (MQ) evolution time t1 that can remove the phase difference of lactate and alanine at the echo was calculated and fine-tuned with experiments. The lactate and alanine signal intensities and the editing efficiencies from the two modified Sel-MQC sequences were theoretically predicted by using the product operator evolutions and compared with the experimental data. The J-coupled lipid signals were successfully suppressed by both sequences. One of the two developed sequences was applied to a human body with a phantom of lactate and alanine, which resulted in successful in-phase editing of lactate and alanine and suppression of the lipid signals from the body. The study sets an important foundation for the noninvasive detection of lactate and alanine from tumors of cancer patients.